Investigating the Application of Banking Regulation to Online Peer-To-Peer Lending Platforms in South Africa to Counter Systemic Risk

Investigating the application of banking regulation to online peer-to-peer lending platforms in South Africa to counter systemic risk

Tamarin Angela Floyd

Student number 16391871

A research project submitted to the Gordon Institute of Business

Science, University of Pretoria, in partial fulfilment of the requirements for the degree of Master of Business Administration.

6 November 2017

ABSTRACT

The behaviour and activities of online peer-to-peer lending platforms have evolved in different ways across jurisdictions, not fitting neatly within existing financial regulatory frameworks. Together with the growth momentum of the industry and the cases where losses were suffered, this culminated in a call to regulate peer-to-peer lending platforms adequately. The research presents an analysis of online peer-to-peer lending platforms through the lens of banking theory, questioning whether peer-to-peer platforms are behaving like banks and whether they pose systemic risk. These research questions feed into the ultimate research problem: whether online peer-to-peer lending platforms should be regulated like banks with respect to liquidity and capital requirements. Liquidity and capital requirements were designed to stem systemic risk in financial systems and have been praised as effective tools. Qualitative exploratory research was undertaken with 18 experts in the field. Key findings included that the presence of systemic risk is contingent on the operating structure and legal implications of the peer-to-peer platform. In certain cases, systemic risk could be present and as such liquidity and capital requirements should apply. The scope of the research was restricted to the South African financial system due to the unique nuances of its regulatory framework.

KEYWORDS

Online P2P lending platform Systemic risk Banking regulation Liquidity and capital requirements

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DECLARATION

I declare that this research project is my own work. It is submitted in partial fulfilment of the requirements for the degree of Master of Business Administration at the Gordon Institute of Business Science, University of Pretoria. It has not been submitted before for any degree or examination in any other University. I further declare that I have obtained the necessary authorisation and consent to carry out this research.

Tamarin Angela Floyd 6 November 2017

ACRONYMS AND ABBREVIATIONS

B/S Balance sheet (in the context of the code names) Cat(‘s) In the context of the code names, this refers to the categories of P2P operating structure (per section 2.1.4) CEO Chief Executive Officer COO Chief Operations Officer GFC Great Financial Crisis of 2008 Insto’s Institutions (in the context of the code names) MD Managing Director NCA National Credit Act NCR National Credit Regulator P2P Peer-to-peer p. Previous(ly) (in the context of the code names) Req Requirements (in the context of the code names) SEC Securities Exchange Commission SME Small and medium sized enterprise UK United Kingdom US United States of America # Number

* Indicates that a code is inductive

TABLE OF CONTENTS

ABSTRACT ...... ii

KEYWORDS ...... iii

DECLARATION ...... iv

ACRONYMS AND ABBREVIATIONS ...... v

LIST OF TABLES ...... x

LIST OF FIGURES ...... xi

1. CHAPTER 1: INTRODUCTION TO RESEARCH PROBLEM ...... 1 1.1 Background to the research problem ...... 1 1.1.1 Defining FinTech ...... 1 1.1.2 Defining peer-to-peer lending ...... 2 1.1.3 Comparing P2P lenders with traditional banks ...... 3 1.2 Research problem, purpose and motivation ...... 4 1.2.1 Introduction to the research problem ...... 4 1.2.2 Objectives of the research ...... 5 1.2.3 Academic motivation ...... 5

1.2.4 Business motivation ...... 6

1.3 Research scope ...... 7 1.4 Principal findings ...... 8

2. CHAPTER 2: LITERATURE REVIEW ...... 9 2.1 Insight into online P2P lending platforms ...... 9 2.1.1 Existing P2P lending platforms and industry statistics ...... 9 2.1.2 P2P platforms’ functionality and associated risks ...... 12 2.1.3 Online P2P lending platforms consider risks ...... 14 2.1.4 Categorised P2P operating structures ...... 15 2.2 Banking theory ...... 16 2.3 Regulation ...... 18 2.3.1 What is the role of the bank regulator? ...... 19 2.3.2 How are online P2P lending platforms currently regulated across jurisdictions? ...... 19 2.3.3 How are online P2P lending platforms currently regulated in South Africa? 22 2.3.4 Linking banking theory with regulation ...... 24

2.4 Systemic risk ...... 25 2.5 Regulating online P2P lenders like banks...... 29

3. CHAPTER 3: RESEARCH QUESTIONS ...... 31 3.1 Research problem ...... 31 3.1.1 Research question one ...... 31 3.1.2 Research question two ...... 31

4. CHAPTER 4: RESEARCH METHODOLOGY ...... 32 4.1 Choice of methodology...... 32 4.2 Research design elements ...... 34 4.2.1 Population ...... 34 4.2.2 Sampling method ...... 35 4.2.3 Sampling size ...... 36 4.2.4 Unit of analysis ...... 37 4.2.5 Measurement instrument ...... 37 4.2.6 Data gathering process: in-depth semi-structured interviews ...... 37 4.2.7 Pre-test ...... 40 4.2.8 Data analysis ...... 40 4.2.9 Limitations ...... 43 4.3 The quality of the research ...... 43 4.3.1 Credibility ...... 44 4.3.2 Transferability ...... 45 4.3.3 Dependability ...... 45 4.3.4 Confirmability ...... 46

5. CHAPTER 5: RESULTS ...... 47 5.1 Description of the sample ...... 47 5.2 Saturation analysis ...... 49 5.3 Addressing the research questions ...... 50 5.3.1 Research question one: Are online P2P lending platforms behaving like banks? 51 5.3.2 Research question two: Do online P2P lending platforms pose systemic risk to the South African financial system, specifically in the absence of liquidity and capital regulation? ...... 57 5.3.3 Research problem: should online P2P lending platforms be regulated like banks in South Africa, with specific respect to liquidity and capital? ...... 72 5.4 Other findings ...... 85 5.4.1 Different regulation ...... 85

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5.4.2 Sustainability of the business model ...... 86 5.4.3 Insight into the risky nature of online P2P lending platforms ...... 88 5.5 Summary of results ...... 89

6. CHAPTER 6: DISCUSSION OF RESULTS ...... 92 6.1 Sample concerns ...... 92 6.2 Research question one: Are online P2P lending platforms behaving like banks? ...... 93 6.2.1 Financial intermediation theory ...... 93 6.2.2 Other banking theories ...... 94 6.2.3 Comparing the roles of banks and online P2P lending platforms ...... 95 6.3 Research question two: Do online P2P lending platforms pose systemic risk to the South African financial system, specifically in the absence of liquidity and capital regulation? ...... 97 6.3.1 Components of systemic risk in South Africa ...... 97 6.3.2 Liquidity and capital requirements as tools to mitigate systemic risk...... 99 6.3.3 Do online P2P lending platforms pose systemic risk? ...... 100 6.4 Research problem: should online P2P lending platforms be regulated like banks in South Africa, with specific respect to liquidity and capital? ...... 103 6.4.1 The banks regulator’s role ...... 104

6.4.2 Stifling versus enabling regulation ...... 107

6.4.3 The present regulatory framework for P2P lending ...... 107 6.4.4 Whether online P2P lending platforms should bear liquidity and capital requirements ...... 108

7. CHAPTER 7: CONCLUSION ...... 112 7.1 Principal findings ...... 112 7.1.1 Research question one: Are online P2P lending platforms behaving like banks? 112 7.1.2 Research question two: Do online P2P lending platforms pose systemic risk to the South African financial system, specifically in the absence of liquidity and capital regulation? ...... 113 7.1.3 Research problem: Should online P2P lending platforms be regulated like banks in South Africa, with specific respect to liquidity and capital requirements? 114 7.1.4 Summary of principal findings ...... 116 7.2 Implications for stakeholders ...... 117 7.3 Limitations of the research ...... 117 7.4 Suggestions for future research ...... 118

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7.5 Closing ...... 119

8. REFERENCES ...... 120

9. APPENDICES ...... 128 9.1 Appendix 1: Consistency matrix ...... 128 9.2 Appendix 2: Ratings for the referenced journals per the ABS Journal Guide 2015 129 9.3 Appendix 3: Existing online P2P platform metrics ...... 130 9.4 Appendix 4: Ethical clearance approval ...... 132 9.5 Appendix 5: Summary of sample containing interviewees’ metrics ...... 134 9.6 Appendix 6: Cover letter template ...... 139 9.7 Appendix 7: Consent form template ...... 140 9.8 Appendix 8: Interview Guide...... 141 9.9 Appendix 9: Appendix to Interview Guide ...... 143 9.10 Appendix 10: Complete list of code super families, code families and codes 146 9.11 Appendix 11: Complete code list and frequency ...... 154 9.12 Appendix 12: Summary of code occurrence across the sample subgroups . 158

LIST OF TABLES

Table 1: Code summary ...... 42 Table 2: Number of interviewees per sample subgroup ...... 43 Table 3: Summary of code frequency ...... 49 Table 4: Codes relating to bank-like behaviour ...... 52 Table 5: Codes relating to banking theory ...... 54 Table 6: Codes relating to the role of banks ...... 55 Table 7: Codes relating P2P lenders and systemic risk ...... 56 Table 8: Codes relating to systemic risk ...... 58 Table 9: Codes relating to exchange control in South Africa ...... 60 Table 10: Codes relating to liquidity requirements ...... 62 Table 11: Codes relating to capital requirements ...... 64 Table 12: Codes relating to P2P lending and systemic risk ...... 68 Table 13: Codes relating investors ...... 69 Table 14: Codes relating to P2P lending and restricting liquidity...... 71 Table 15: Codes relating to the bank regulator’s role ...... 76 Table 16: Codes relating to P2P lending platforms and liquidity requirements ...... 81 Table 17: Codes relating to P2P lending platforms and capital requirements ...... 84

Table 18: Codes relating to P2P lending risks ...... 89

Table 19: Summary of key data results ...... 90 Table 20: Summary of concepts that relate to principal findings ...... 116

LIST OF FIGURES

Figure 1: Dominant authors driving the literature review ...... 9 Figure 2: Present global P2P platform loan issuance (as at 2015) ...... 10 Figure 3: Global P2P platform loan issuance compounded annual growth rates forecast (as at 2015) ...... 11 Figure 4: Saturation analysis: inductive code creation ...... 50

1. CHAPTER 1: INTRODUCTION TO RESEARCH PROBLEM (Appendices 1 and 3 may refer)

Here following the requirement for the research and how this was achieved through the research objectives are discussed.

Online peer-to-peer lending platforms have gained both momentum and popularity in recent years (Chaffee & Rapp, 2012; Grant Thornton, 2015). Essentially the industry offers a new mechanism via which the supply and demand dynamics for personal loans can act (Chuang, Mo, Chen, & Ye, 2016). The recent growth in total loan extension attracted the attention of risk managers and regulators alike: what risks are at play? How should the industry be regulated (Chaffee & Rapp, 2012; Wang, Shen, & Huang, 2016; Wei, 2015)? Banking theory alerts one to potential similarities between the behaviour of banks and online peer-to-peer lending platforms (Werner, 2016). The research focused on whether or not banking regulation should play a role in the formation of online peer- to-peer lending regulation, specifically in the context of South Africa.

1.1 Background to the research problem

1.1.1 Defining FinTech

Financial Technology (“FinTech”) has several similar definitions from a variety of authors.

Chuen and Teo (2015) referred to “innovative financial services or products delivered via technology”. The term refers loosely to digital innovation in the financial industry. It is associated with creative, agile firms that challenge the traditional methods of conducting business in the financial markets. However, as commented upon by an Investec think tank member, digital innovation also exists within established financial market firms (J. Elliot, personal communication, 16 March 2017).

A report by the International Organisation of Securities Commissions (2017) defined FinTech as “a variety of innovative business models and emerging technologies that have the potential to transform the financial services industry” (p. 2). Douglas (2016) put forward that it is not a new phenomenon to witness non-bank entities perform banking functions. However, he agreed that it is more recently prolific with the wave of FinTech entrants over recent years.

Chuen and Teo (2015) spoke of the LASIC principles which are enabling factors for FinTech: low margin, asset light, scalable, innovative and compliance easy. They deemed these principles as necessary but not sufficient for the successful establishment

of FinTech propositions. Dapp (2014) spoke about how many FinTech offerings to date are built on less knowledge intensive, easily standardisable finance functions.

1.1.2 Defining peer-to-peer lending

The term “peer-to-peer” was referred to as P2P throughout the research. Where the author referred to P2P, she meant in the context of an online P2P lending platform acting as an online marketplace. Reference to platforms means any firm offering P2P lending services primarily via an online digital mechanism. Throughout the research the author makes shortened reference to “P2P lender” and “P2P platform”, in both instances referring to the complete concept of an online P2P lending platform.

A form of FinTech, online P2P lending describes the online marketplace where lenders can transact directly with borrowers without prior relationships and without acting via an intermediary channel, which would ordinarily be a bank. It is a new way of connecting demand and supply for funds (Chuang et al., 2016). Traditional lending is defined as transactions where the lender is institutional. Critically, P2P lending excludes the institutional player (Chaffee & Rapp, 2012).

P2P platforms have established themselves in several markets, primarily being the US, the UK, and China. China specifically has seen P2P lending flourish: by June 2015 there were 2028 P2P platforms and a cumulative total (excluding roll off) of RMB 683.5 billion extended in loans (Chuen & Teo, 2015). By April 2016 there were 4029 P2P platforms and RMB 547.8 billion outstanding in loans. This remains dwarfed, however, by the traditional banking sector in China who had RMB 93.95 trillion in outstanding loans at the end of 2015 (Wang et al., 2016).

The attractions of P2P for lenders and borrowers are superior returns and less expensive borrowing rates respectively (Emekter, Tu, Jirasakuldech, & Lu, 2015). Wang, Shen and Huang (2016) and Wei (2015) commented similarly. There exists scope for P2P lending (and other FinTech platforms) to enter the unbanked market given lower costs and network access (Chuen & Teo, 2015). Chaffee and Rapp (2012) commented that P2P allows capital to flow to economically depressed communities, creating opportunities for its members. Wang, Shen and Huang (2016) found that borrowers in China are accessing loans via P2P platforms at lower interest costs than via the informal finance channels. They emphasised generally the significant impact that P2P lending has had in China in terms of allowing legal access to credit (as opposed to partaking in the informal finance sector). Wei (2015) confirmed with certainty that in China (a) lenders benefit by earning higher returns over shorter investment periods as the lack of regulatory oversight

makes the lending business model cheaper to run and (b) borrowers benefit as P2P platforms provide access to funds that a large portion of SME's and individuals would otherwise be unable to obtain through traditional channels. 60% of loans extended via P2P platforms are between one and three months in term in the Chinese market (Wei, 2015). The market in China is primarily driven by a strong demand side dynamic (borrowers) (Wei, 2015) whilst in the US the investors' (lenders) hunger for superior returns has been a dominant driver of the market growth (Chaffee & Rapp, 2012).

The concept of individuals lending to one another (peer to peer) is not a new one, examples of “fringe” lending arrangements have existed (and continue to exist) for generations in various forms including loan sharks and loans between friends (Namvar, 2013). However, it is the data driven online marketplace that differentiates the FinTech form of P2P (Chaffee & Rapp, 2012), which was the focus of this research. The online element aside, Wang, Shen and Huang (2016) argued that P2P platforms in China differ from microlenders in that they are not focussed on a specific region and that the funds on both sides of the transaction’s equation are granular stemming from an array of individuals, as opposed to the lending side being fairly chunky. A further differentiating factor of online P2P lending from historical examples is the lack of pre-existing personal relationships (Chuang et al., 2016).

The rise and growing popularity of P2P lending in its FinTech form has been partly attributed to the sharp decrease in credit extension following the Great Financial Crisis of 2008, post which traditional lending to consumers fell 6.0% from January 2009 to March 2010 (Chaffee & Rapp, 2012). In response thereto, there has been increased regulatory pressure on traditional banks which has pushed up their cost bases. As phrased by a financial market participant: “The market should manage these issues. Do not regulate the market to the point that participants abandon it for other structures” (CFA Institute, 2015). Moshirian (2011) commented that financial crises often lead to the development of new institutions and regulations.

1.1.3 Comparing P2P lenders with traditional banks

A critical difference between a P2P lending platform and a bank is the credit risk worn by the investor: a depositor at a bank takes on the bank’s credit risk, in other words the investor will not get his/her money back if the bank defaults (ABSA, 2017; First National Bank, 2017; Investec, 2017; Nedbank, 2017; Standard Bank, 2017). The loans that a bank makes to borrowers are distinct relationships from those it has with the depositors (lenders). If a bank makes a loan to a borrower that defaults, this does not affect the bank’s obligation to refund its depositors (Werner, 2016). However, a P2P platform

investor (lender) takes on the credit risk of the underlying borrower directly (Prosper Marketplace, 2017). Should the underlying borrower default (but the P2P platform remain standing), the lender may lose his/her money (FSCS, 2016). For certain P2P platform operating structures, because the lender is transacting through the P2P platform, he/she may bear credit risk to the P2P platform as well (Financial Times, 2015). The legal structures that P2P platforms adopt to effect the lender-to-borrower investment vary across P2P platforms (Chaffee & Rapp, 2012). Section 2.1.4 provides a broad classification of the various operating structures that exist, which pose various risk and legal consequences to the borrowers and lenders transacting therethrough. When one considers banks and P2P lenders through the lens of banking theory, similarities are apparent (refer to section 6.1.1).

1.2 Research problem, purpose and motivation

1.2.1 Introduction to the research problem

The research problem was born out of a cluster of several interactive dynamics: the growth of online P2P lending as an industry (Grant Thornton, 2015; Transparency Market Research, 2016); the lack of adequate regulatory treatment therefore; the various shapes and forms in which P2P platforms are establishing themselves (Chaffee & Rapp, 2012); the interaction of P2P lending within greater financial system; and the risks related thereto for consumers being both lenders and borrowers (Chaffee & Rapp, 2012; Chuang et al., 2016; Emekter et al., 2015; Wang et al., 2016; Wei, 2015). Lastly, P2P lending’s specific regulatory treatment in South African (which is governed by its own unique mix of regulation) was (and remains) in question.

The research problem centred on whether online P2P lending platforms should be regulated similarly to banks with specific respect to liquidity and capital. Although not exhaustive, these two elements have been identified as key tools for proactively minimising systemic risk in the financial system (Roulet & Blundell-Wignall, 2013) and are chief elements of the continually evolving banking regulation guidelines, Basel, put forward by the Bank for International Settlements (2017) (refer to section 2.3). There is limited literature on the specific application of liquidity and capital controls to P2P lending platforms.

The research explored the application of banking theories to online P2P lending and in so doing enriched (but did not solve) the debate as to how P2P lending platforms should be regulated, specifically asking whether a banking type approach should be applied. The research aimed to bolster the body of knowledge around P2P regulation in the

context of banking, regulation and P2P lending in South Africa. A literature bap existed particularly on the latter (consider section 1.4 on the scope of the research).

1.2.2 Objectives of the research

The objective of the research was to explore whether regulation similar to banking regulation, specifically around liquidity and capital requirements, should be applied to P2P platforms. Addressing the objective effectively required breaking it down into key components. Firstly, banking theory was used to analyse the role that P2P lending platforms play in the financial market. This penetrated the matter of whether or not the P2P platform behaviour is akin to a bank. This related to the dynamic that there are various P2P platform operational structures at play that pose different risk and legal implications for borrowers and lenders. The research then explored whether P2P lending platforms pose systemic risk (or could pose given the industry’s growth momentum) to the financial system and in turn its participants. This related to the notion that consumers could be exposed to the P2P platform itself, not only the lender being exposed to the borrower. Once addressed, the findings from these two key areas fed into the overarching research objective of whether or not liquidity and capital requirements should be applied to P2P lenders. This in the context that liquidity and capital requirements have been applied to the banking industry with specific intent to manage systemic risk (Bank for International Settlements, n.d.).

1.2.3 Academic motivation

Online P2P lending platforms are emerging and established in several financial markets across the world. Different markets are adopting different approaches to regulate online P2P lending platforms, ranging from treating P2P platforms like intermediaries, to banks, to securities providers (Financial Times, 2014; Grant Thornton, 2015). Some markets have little or loose regulation whereas others have outright prohibited P2P lending. At the time of the research, France, Germany and Italy were the only examples of financial markets that had opted for P2P regulation fed by banking regulation principles (Grant Thornton, 2015). The US regulator has found it challenging as the concepts of borrowers, lenders, exchanges and securities in the context of online P2P lending do not fit neatly within the traditional definitions (Chaffee & Rapp, 2012). The Chinese regulator has to date adopted a fairly “hands-off” approach, resulting in higher financial risks and fraudulent activities – hence the plea for regulatory oversight (Wei, 2015). The academic debate thus existed (and remains) on how P2P platforms should be regulated and whether it should be globally cohesive. This research explored whether regulation should

specifically align with that applied in the banking realm. The research did not attempt to determine the overarching optimal regulatory regime for P2P platforms.

The call for progress on the issue of regulating online P2P lenders was voiced strongly in the academic arena by Chaffee and Rapp (2012); Chuang, Mo, Chen and Ye (2016); Emekter, Tu, Jirasakuldech and Lu (2015); Wang, Shen and Huang (2016) and Wei (2015). At the time of the research, literature was limited on the specific issue of whether liquidity and capital controls (as drawn from banking regulation) should apply directly to P2P platforms, specifically for the South African market. It is this realm to which the research wished to contribute.

Financial intermediation theory allows one to question whether banks and P2P lenders are dissimilar: they stand between ultimate borrowers and ultimate lenders (Werner, 2016). P2P platforms have established themselves with various legal and operating structures in different jurisdictions (refer to section 2.1.2), in some cases extending beyond the vanilla introductory intermediary role. This led to the first research question: are online P2P lenders behaving like banks? Other theories of banking (fractional reserve, credit creation) enrich the debate as they define banks differently (Werner, 2016). Financial intermediation theory acted as a cornerstone in the research.

1.2.4 Business motivation

The rising popularity of FinTech and specifically online P2P lending lent topicality to the research. However, it is the potential systemic risk posed to financial markets and the lack of protective regulation therearound that make the research relevant in the business context (Wei, 2015).

The research explored whether P2P platforms creates room for systemic risk to breed (Wei, 2015): a growing industry within the greater financial services world operating between (not neatly within) regulations begs attention to this question (Chaffee & Rapp, 2012). This together with the notion that the P2P lenders’ behaviour may mimic that of banks leads one to ask whether liquidity and capital requirements (as tools to mitigate systemic risk in financial systems (Roulet & Blundell-Wignall, 2013)) could be appropriate.

The growth of P2P lending across jurisdictions has not been without incident. Wei (2015) described the financial distress and resultant civil protests in China that arose following the collapse of multiple P2P lending platforms in China in circa 2014 and 2015. This led to financial losses for consumers involved. This indicated how the P2P platform itself

poses risk to consumers; unlike the scenario where it is only the borrower that poses credit risk to the lender. TrustBuddy (Financial Times, 2015) is an example of a Swedish P2P platform that closed, resulting in losses for its consumers (predominantly the lenders).

Therefore, it was the variation in regulation design for P2P platforms across financial markets (Chaffee & Rapp, 2012; Financial Times, 2014); the academic debate on regulation related thereto; the potential systemic risks posed by online P2P lending (Moshirian, 2011; Wei, 2015); and the growth of online P2P lending (Grant Thornton, 2015; Transparency Market Research, 2016) that together formulated the overarching rationale for the research. Further, there was limited literature around whether or not liquidity and capital requirements (banking regulation) have application to P2P platforms and a literature gap existed on online P2P lending in South Africa (see section 1.3). This reinforced the requirement for the research. This drove the formation of the research objective, specifically designed to address the research problem.

1.3 Research scope

As described by Roulet and Blundell-Wignall (2013), the regulations applied to financial markets (usually bounded by country borders) vary. Although similarities are strong, different financial markets have unique nuances in terms of the regulatory bodies that exist, their scopes of authority and the mix of governing legislation. Also, existing literature on P2P platforms has largely focussed on the US, the UK (Chaffee & Rapp, 2012; Emekter et al., 2015) and Chinese (Wang et al., 2016; Wei, 2015) P2P markets. As such, this provided justification tom limit the research to a specific jurisdiction given the unique context of its own regulatory environment. However, high level principles may cross apply to other markets with similar attributes. There existed a gap in literature on P2P lending regulation in South Africa specifically.

Also, South Africa has exchange control regulation in force which largely restricts the interaction of its domestic financial system with foreign ones (Republic of South Africa, 2016), which may lead to the containment of the South African markets within its borders. This could affect the creation and distribution of systemic risk in the South African financial system. However, Moshirian (2011) argued that systemic risk will not be contained until there is one globally consistent regulatory framework in place because the due to the freedom of money flows between nations (refer to section 2.3).

On the basis of these issues, the author limited the scope of the research to the South African market.

1.4 Principal findings

A snapshot of the principal findings as detailed in section 7.1 follows here.

It was found that financial intermediation theory does apply to P2P platforms. A handful of determining factors influence the debate on whether or not a P2P lender is behaving like a bank, being the involvement of the P2P balance sheet in the transactional equation (Roulet & Blundell-Wignall, 2013; Werner, 2016) and the pooling (aggregating) of assets and liabilities on balance sheet which in turn creates the opportunity for maturity transformation (Diamond & Rajan, 2001).

An emergent theme that arose in the data (premised on theoretical elements in the literature) was the question of whether or not lenders transact through P2P platforms with intentions akin to a depositor or an investor. This issue appeared in arguments relating to a bank’s role, systemic risk and the role of the bank regulator.

The data proposed that P2P lending does not presently pose systemic risk in South Africa but it could do so if the industry grows and the systemic risk components are evident in the operating structures of the P2P platforms. These components include the involvement of the balance sheet in the transactional equation (Werner, 2016), interconnectedness (Moshirian, 2012; Staum, 2012), the restriction of liquidity (which in itself is a function of the size of the industry) (Diamond & Rajan, 2001; Fernando &

Herring, 2002), maturity transformation, pooling liabilities, the presence of leverage

(Roulet & Blundell-Wignall, 2013) or the mispricing of risk (Fernando & Herring, 2002).

Ultimately, the research proposed that the application of liquidity and capital requirements to online P2P lending platforms in South Africa is contingent on both the operating structure and the industry growing. Should the balance sheet of the P2P lender be involved in the transactional equation (Werner, 2016), P2P platforms be interconnected within the financial system (Moshirian, 2012; Staum, 2012), pooling be present (Diamond & Rajan, 2001), maturity transformation or leverage be utilised (Roulet & Blundell-Wignall, 2013), the research found that P2P platform should be subject to liquidity and capital requirements. However, these requirements should not necessarily be identical to those dictated by banking regulation.

2. CHAPTER 2: LITERATURE REVIEW (Appendices 1, 2 and 3 may refer)

The literature review provided insight into P2P platforms (including their functionality, structures and industry metrics) and then addressed the key intersecting topics of P2P lending, banking theory, banking regulation (including its role and application) and systemic risk. The topics of regulation and systemic risk are inherently intertwined. The research question considered whether there is application thereof in the realm of P2P lending. The exploration into P2P lending allowed one to appreciate why or when this may be so. The dominant researchers that drove the author’s views in the literature review are summarised in Figure 1 below. The list is not exhaustive; presented in alphabetical order.

Figure 1: Dominant authors driving the literature review

Chaffee & Rapp (2012) Akerlof (1970) Chuang, Mo, Chen & Ye (2016) Beaver (1966) Chuen & Teo (2015) Fernando & Herring (2002)

Dapp (2014) Foster (1986) Risk Emekter, Tu, Jirasakuldech & Lu (2015) Moshirian (2011, 2012) Iyer, Khwaja, Luttmer and Shue (2009) Roulet & Blundell-Wignall (2013) Namvar (2013) Staum (2012) P2P Lending P2P Wang, Shen & Huang (2016) Stiglitz & Weiss (1981) Wei (2015)

Diamond & Rajan (2000) Diamond & Rajan (2001) Douglas (2016) Phillips (1920) Tobin (1963) Werner (2016) Banking & Regulation

2.1 Insight into online P2P lending platforms

2.1.1 Existing P2P lending platforms and industry statistics

Appendix 3 summarises some of the key metrics for selected P2P lending platforms across jurisdictions in order to provide context for the discussions in this research.

The true size of the online P2P lending industry has not been ascertained with confidence given its non-standardised shape across different jurisdictions, its exponential growth in some jurisdictions and the largely unregulated nature of the P2P platforms. However, Transparency Market Research is a research house that published

its estimated numbers in 2016. It estimated that the global P2P lending market was valued at USD 26.16 billion in 2015 and that the forecast growth would lead to a number of USD 897.85 billion by 2024 (Transparency Market Research, 2016). Wei (2015) proposed that the global P2P loan issuance total was USD 2.8 billion in 2013 alone. Morgan Stanley Research released research in 2015 which forecast total loan origination as a range, between USD 150 billion and USD 490 billion by 2020 across the globe (Morgan Stanley Research, 2015).

Figures 2 and 3 that follow below indicate the present versus forecast status of the global P2P lending industry. Morgan Stanley Research (2015) estimated of the present value of the P2P market globally was similar to that of Transparency Market Research: USD 23.7 billion in 2014 estimated by Morgan Stanley Research (Morgan Stanley Research, 2015) versus USD 26.16 billion in 2015 estimated by Transparency Market Research (Transparency Market Research, 2016).

Figure 2: Present global P2P platform loan issuance (as at 2015)

Retrieved from “Can P2P reinvent banking?”, by Morgan Stanley Research, 2015.

Considering the United States specifically: a forecast for the potential market growth of P2P lending is from a total loan origination of USD 5.5 billion in 2014 forecast to grow to USD 150 billion by 2025 (Douglas, 2016). Douglas (2016) commented that whilst the current market size is relatively small the media hype has nonetheless been significant.

Figure 3: Global P2P platform loan issuance compounded annual growth rates forecast (as at 2015)

Retrieved from “Can P2P reinvent banking?”, by Morgan Stanley Research, 2015.

Wei (2015) provided insight into the scale of P2P lending in China: the market grew from 150 online P2P platforms at the beginning of 2013 to about 2028 by mid-2015 with total loans outstanding of RMB 209 billion at the same point in time compared with a cumulative total loan issuance (excluding roll off) of RMB 683.5 billion (Chuen & Teo, 2015). By April 2016 there were 4029 P2P platforms and RMB 547.8 billion outstanding in loans (Wang et al., 2016). This lending market in China is associated with "underground" shadow banking (Wei, 2015). For comparison purposes, the outstanding loans issued by commercial banks in China was RMB 93.95 trillion at the end of 2015 (Wang et al., 2016). In 2014 the net loan issuance in China was USD 19.8 billion (The World Bank, 2017) compared to the estimated P2P lending platform gross loan origination amount of USD 8.9 billion in 2015 (Morgan Stanley Research, 2015). Certainly, this indicates the significance and growth of the P2P lending market in China.

The Alternative Finance Benchmarking Report published by Cambridge Centre for Alternative Finance in 2017 surveyed 66 online alternative lending platforms based in Africa and the Middle East across 46 countries in Africa and 12 countries in the Middle East. It showed that the volume of P2P lending in Africa for the year 2015 was USD 14 million – a fraction of the global total. South Africa accounted for the lion’s share of P2P

lending volumes in 2015, totalling USD 13.8 million. This compares with the net lending by commercial banks in South Africa which was USD 9.98 billion in 2015 (Zhang et al., 2017).

The Alternative Finance Benchmarking Report concluded that 62% of the survey respondents (online alternative finance providers in 46 African countries) agreed that limited regulation existed around alternative financing sources (including P2P lending). However, only 21% of survey respondents explicitly stated that regulation required enhancement (Zhang et al., 2017).

Key industries that were funded by P2P lending in Africa in 2015 consisted of two categories: (a) consumer lending and (b) business lending. The consumer lending was predominantly funding activity in the Real Estate and Housing, then Community and Social Enterprise and lastly Retail and Wholesale industries. Business lending, by contrast, was predominantly funding activity in the Leisure and Hospitality, then Retail and Wholesale and lastly Media and Publishing industries (Zhang et al., 2017).

RainFin is a key player in the South African P2P market. It launched in 2012 (RainFin, 2017) and by 2014 it had 350 customers registering online per day. However, only 10% of those passed the screening process and were admitted to the platform. At the time, about 18 loans totalling R400 000 were originated daily (Bonorchis, 2014). ABSA purchased a 49% stake in the RainFin business in March 2014 but sold it in November 2016. By the end of 2016 RainFin was reportedly originating R1 million of loans per day (Ziady, 2016).

2.1.2 P2P platforms’ functionality and associated risks

The loans made via some P2P platforms in China are guaranteed by banks or insurance houses (Wang et al., 2016). As such, the risks are different to those associated with unsecured P2P lending and the credit risk borne by the lender is not limited to the borrower, as it might be in a true pass-through transaction. P2P platforms that offer principal and interest guarantees were found to have shorter life expectancies and lower survival probabilities (Wang et al., 2016). Further, they find that platforms with no (or little information on) registered capital are risky platforms. Also, the more recently a P2P platform was established, the riskier it is. It is sensible that an established business would have had time to (a) build a capital base and (b) improve its market knowledge and execution. Wang, Shen and Huang (2016) commented that higher loan interest rates via P2P platforms cannot cover the associated default risk adequately. Wang, Shen and Huang (2016) concluded that investors must choose the P2P platforms via which they invest carefully, preferring those with longer survival times, transparent disclosure, a

variant interest rate structure and guarantees from banks or insurance firms. They caution investors against P2P platforms that do not provide full information on registered capital or provide guarantees for the loans themselves. In essence, they implied that investors are safest relying on regulated institutional players.

Access to client data to establish individual credit profiles is an enabling factor for P2P platforms (Chuen & Teo, 2015). Such data can be sourced from various places including social media and transactional banks. P2P lending offers lenders superior returns (Emekter et al., 2015) but lenders are required, often for the first time, to assess the creditworthiness of borrowers themselves. This is a role that is traditionally played by banks. Valuable expertise that traditional banks have are the ability to assess, evaluate and manage risk (Dapp, 2014). This expertise develops from experience and may become intuitive. This expertise is used to (a) assess creditworthiness, (b) gauge the appropriate interest rate and security required commensurate with the specific borrower’s risk, (c) structure the transaction accordingly and (d) pursue the borrower to recover capital in the event of a default. First time lenders may find this daunting and difficult. Wang, Shen and Huang (2016) confirmed that a critically important function performed by financial institutions is the pricing of risk. Emekter, Tu, Jirasakuldechc and Lu (2015) found that low debt-to-income ratios, high FICO scores, low usage of a revolving credit line and a high credit grade were associated with low default risk. Research by Iyer, Khwaja, Luttmer and Shue (2009) found that lenders can only ascertain about one third of a borrower’s credit risk from hard and soft data provided by the borrower. This was further supported by Wang, Shen and Huang (2016) who commented that the lenders and borrowers via P2P lending in China are usually individuals or small businesses with less information to provide to form thorough credit profiles. Also, their capabilities to understand and withstand financial risks are inferior.

As such, information asymmetry exists between lenders and borrowers, which may result in adverse selection (Akerlof, 1970) or moral hazard (Stiglitz and Weiss, 1981). In addition to physical, personal relationships, Emekter, Tu, Jirasakuldech and Lu (2015) commented that banks have several methods at their disposal to enhance the trust that they place in a borrower. These methods include certified accounts, collateral, regular reporting and (sometimes) presence on the board of directors of the borrower. In addition to regulatory capital, certain of these factors increase the transactional cost.

Emekter, Tu, Jirasakuldech and Lu (2015) found that higher interest rates associated with riskier loans (to individuals with lower credit ratings) do not adequately compensate lenders for the increased risk taken on. Wang, Shen and Huang (2016) found similarly.

Further, they advised that in their study US consumers with specifically high credit ratings and income did not partake in the P2P market as actively as lesser rated borrowers. This leaves the lenders on P2P platforms in a quandary: the desirable highly creditworthy borrower chooses not to engage via the P2P platform, leaving lenders to choose from less creditworthy options, knowing that the increased risk related thereto is incommensurate with the increased return.

A lack of liquidity discourages investors. Few P2P providers do create trading platforms to facilitate the trading of P2P loans in the secondary market (Chaffee & Rapp, 2012; Chuang et al., 2016). This provides lenders with some liquidity although it is contingent on the availability of willing buyers. Wei (2015) reinforced the importance of liquidity when he reported that 43.5% of the Chinese P2P platforms that found themselves in trouble between 2011 and 2014 were so due to a cash shortage. This translated into an absolute number of 87 platforms.

Douglas (2016) commented that the people driving FinTech start-ups are more technologists than bankers, that they have risk-taking mentalities and disregard for regulation. Douglas (2016) differentiated between those who were unaware of the regulations and therefore unintentional transgressors versus those who were entirely informed but purposefully ignoring (if not combating) regulations. Douglas (2016) cautioned P2P lenders from disregarding regulations in their start-up phases as the

present-day US regulator is more cautious and less tolerant of innovation in the banking sector compared with how historical instances of how such innovation was addressed by the US regulator (Douglas, 2016). Certainly, consumer protection appears at the forefront of the regulator’s priorities.

2.1.3 Online P2P lending platforms consider risks

P2P platforms do put in place filters and infrastructure to aid lenders with their assessments of borrower creditworthiness. These include matchmaking systems and portfolio recommendations (Emekter et al., 2015) based on lenders’ and borrowers’ data. Moshirian (2011) commented on the importance of financial data to improve financial supervision. Some platforms offer daily operational support, regulatory compliance and fraud detection infrastructure (Chuang et al., 2016). In the event of default, P2P platforms assist the lender with the recovery process by reporting the transaction to credit agencies and appointing vetted collection agencies on behalf of the lender (Emekter et al., 2015). That said, Chaffee and Rapp (2012) maintained that P2P platforms are weak on the recovery front and leave lenders with little or no independent recovery avenues.

In an effort to reduce the shock of borrower default, some P2P platforms diversify investors’ portfolios to reduce their exposure concentration to a single borrower (Prosper Marketplace, 2017). As such, the financial shock resulting from the default of a specific borrower may be less significant. This is evidenced in Wang, Shen and Huang’s (2016) work: by April 2016 the number of lenders outpaces the number of borrower at 2.98 million to 0.8 million in the sample of 4029 P2P platforms that they considered. This indicates how the risky investment is spread across several lenders.

Some P2P platforms speak to loss absorption funds, a concept that is akin to the capital held by a bank. For example, Zopa (2017) advises that it has a Safeguard fund. Investors can opt for the Safeguard option or not. In essence, this begins to look and feel more like a banking transaction.

2.1.4 Categorised P2P operating structures

P2P lending platforms across geographies have structured their operations in various ways. The various operating structures may result in different types and amounts of risk as well different legal positions for borrowers and lenders. The author has categorised these broadly as follows to allow for meaningful conversations about P2P platforms, the accurate application of theory and better organisation of data results.

Category one: clients’ monies are ring-fenced

The loan relationship exists between the lender and the borrower with the P2P platform effectively acting as a facilitation agent. For the interim stage during which the money leaves the lender but before it arrives at the borrower, the P2P lender arranges that monies from lenders are ring-fenced in off balance sheet trust accounts with a separate entity, ordinarily a bank (Dewar & Shilongo, 2017; RainFin, 2017). The P2P platform may have a transactional account in its own name into and out of which monies are transferred to execute the loan or receive monies from clients. For the short period of time that lenders’ money passes through the P2P platform’s transactional account, the lender may be exposed to the credit risk of the P2P platform (in other words, if the P2P platform were to go into liquidation at that point, the lenders’ money would be part and parcel of the liquidation process). As such, the loan relationship exists between the lender and the borrower with the P2P platform effectively acting as a facilitation agent. The lender may bear brief temporary credit risk to the P2P platform.

Although not identical, category one bears similarity with RainFin in South Africa (Dewar & Shilongo, 2017; RainFin, 2017).

Category two: securities issuance

Lenders invest in notes (regulated as tradeable securities) issued by the P2P platform, the repayment terms of which are contingent on the performance of selected borrower loans the P2P platform makes on the other side of its balance sheet. As such, the lender and the borrower do not share a direct legal relationship. The lender is exposed to the P2P platform’s credit risk as it is the note issuer (Prosper Marketplace, 2017). As such, the lender may find that he/she is exposed to both the ultimate borrower and the online P2P lending platform for the same piece of money. In this way, the balance sheet of the P2P lending platform is involved in the transaction between the borrower and the lender. However, to the extent that assets and liabilities are matched on the P2P lender’s balance sheet, there is minimal maturity transformation and minimal leverage on the balance sheet of the P2P lender.

Although not identical, category two bears similarity with Prosper in the United States (Prosper Marketplace, 2017).

Category three: investing in a portfolio of assets In this instance, lenders lend into a pool of loans selected and constructed by the P2P platform. The lenders have not self-selected the beneficiaries of their loans (RateSetter, 2017). The pool may exist on the balance sheet of the P2P lending platform or in an off balance sheet vehicle. The elements of maturity transformation (short term liquidity availability despite the longer dated maturity of the underlying loans), leverage or other

forms of balance sheet complexity may exist.

Although not identical, category three bears similarity with RateSetter in the United Kingdom (RateSetter, 2017).

2.2 Banking theory

Where the author refers to banks throughout this research, she means firms that have obtained banking licenses in their respective markets, are subject to banking regulation and are viewed as banks in the eyes of financial intermediation theory (read on for colour).

The research problem will be addressed through the lens of banking theory. Three key theories exist: financial intermediation, fractional reserve and the credit creation theory (Werner, 2016). The three theories are not necessarily complementary and have gained and lost support from various academic authors over the years. Financial intermediation theory is the present day dominant theory (Werner, 2016).

Financial intermediation theory proposes that banks and non-bank financial intermediaries do not act dissimilarly, collecting and lending out funds (Werner, 2016).

Critically, financial intermediation theory likens all institutions that effect deposit taking and on-lending behaviour, be they banks or otherwise (Werner, 2016). This builds on early work by von Mises’ in 1912 in which he commented that those enacting the lending of money are bankers whilst those whose money is ultimately being lent (depositors) are merely capitalists (Werner, 2016). The theory was furthered over time by Sealey and Lindley (1977); Baltensperger (1980); Riordan (1993); Kashyap, Rajan and Stein (2002); Bernanke and Blinder (1988) and, more recently, Casu, Girardone and Molyneux (2006). This theory is presently fairly popular (Werner, 2016) and certainly provokes thought around the similarities between banks and P2P platforms.

Tobin (1963) commented specifically that banks differ from other financial intermediaries (which in the modern-day context may include P2P platforms) only due to the reserve requirements that they hold, the capital requirements that they need to meet and the interest rate ceilings which cap the rates chargeable on loans. Any financial intermediary adhering to similar regulations would behave in much the same way that banks do (Tobin, 1963). However, Werner (2016) continues that banks own the deposits they gain from clients and show them on the balance sheet as senior ranking liabilities whereas non-bank financial intermediaries (for example, stockbrokers) do not show their clients’ investments on their own balance sheets. This begs the critical question around whether P2P lenders create liabilities on their own balance sheets when accepting funds from lenders. Diamond and Rajan (2001) commented that to the extent that a separate financial intermediary can assume the unfulfilled obligations of a failing intermediary, there is no harm in that entity failing altogether regardless of its balance sheet liabilities. This echoes with the notion of state support for systemically important financial institutions.

Financial intermediation theory is countered by the fractional reserve theory which purports that beyond the financial intermediary role that banks play, the banking system as an aggregate creates money through multiple deposit expansion (Werner, 2016). Fractional reserve theory rests on the money multiplier effect: because each bank is only required to place a percentage of its total deposits with its central bank and can lend out the rest, if each bank does that one after the other acting on the same initial deposit, money is in fact created. However, this effect is reliant on banks acting collectively in the same financial system (Werner, 2016). Per Phillips (1920), what is true for the banking system as a whole is not necessarily true for an individual bank. Under, this theory, a prerequisite for the loans a bank makes are the deposits it gains (Werner, 2016).

By contrast, the credit creation banking theory purports that each individual bank can create money simply through the process of lending. This theory is over a century old but has lost popularity amongst academics since the 1930s. The credit creation theory bears little similarity to either the financial intermediary or fractional reserve theories. It differs in that banks do not first need to gather deposits in order to lend; they are not required to hold reserves; and that an increase in one bank’s assets does not imply an equal decrease elsewhere in the financial system. Instead, credit creation theory purports that banks create money out of nothing via credit extension due to their ability to extend more credit than deposits received (Werner, 2016).

Werner (2016) concluded that the accounting implications on banks’ balance sheets of both the financial intermediation and fractional reserve theories expose their flaws. He was ultimately in support of credit creation theory. However, he argued further in favour of Quantity Theory of Credit which guides the direction of credit in favour of only those transactions that support nominal GDP.

The premise of P2P lending is that the platform offers a meeting place for lenders and borrowers to interact directly (Chaffee & Rapp, 2012; Chuang et al., 2016). As such, P2P platforms appear not to fall into the realm of credit creation theory as they do not intend to lend money without borrowing it first. Fractional reserve theory speaks to the collective ability of banks to create money as the same initial amount is deposited and on-lent

multiple times (Werner, 2016). As P2P lenders are presently not subject to reserve requirements with central banks in most jurisdictions in which they operate (Grant Thornton, 2015), this theory’s application is limited. Financial intermediation theory, however, has application in the P2P world as banks are defined as entities that borrow in order to lend out (Chuang et al., 2016; Werner, 2016). Review section 2.3.2 for more colour on the presently prevailing regulatory regimes for P2P lending.

As such, the research questions on P2P lending have been analysed through the lens of banking theory, specifically financial intermediation theory.

2.3 Regulation

Chaffee and Rapp (2012) commented that because P2P platforms’ models differ, it is difficult to create a single coherent regulatory regime. As mentioned, regulators in various countries are debating and designing regulatory schemes to govern the P2P presence in their markets without necessarily aligning with one another (Financial Times, 2014; Grant Thornton, 2015).

It was clear from the work by Wei (2015) and the losses suffered by consumers to date in various jurisdictions that regulation is required in the P2P lending industry to ensure the safety of consumers, both borrowers and lenders.

2.3.1 What is the role of the bank regulator?

The role of the regulator in banking is a matter on which both the academic and regulatory fraternities have views. Chaffee and Rapp (2012) spoke about the importance of lending regulation to ensure that borrowers maintain manageable levels of indebtedness and are treated fairly with respect to interest rates charged. On the other side of the investment equation, the protection of investors is also important.

Moshirian (2011) advised that the role of central banks (a key body in the economic and banking regulatory framework), traditionally referred to as the lenders of last resort, has expanded beyond inflation and growth targeting since the Great Financial Crisis (“GFC”) of 2008; it now includes a mandate to ensure financial stability and to implement the macro prudential policy to safeguard as such. This connects with the liquidity and capital requirements that the Bank for International Settlements has outlined in the Basel framework (Bank for International Settlements, n.d.). The South African Reserve Bank (n.d.-b) advised that its bank regulation intentions are to achieve an efficient, sound banking system in the interests of depositors and the economy as a whole. This echoes with the principles of depositor protection and systemic risk containment. Its strict reach covers those banks that have been issued with banking licenses. However, it monitors the activities of non-bank entities that it believes could affect the financial stability of the South African market. Moshirian (2011) went so far as to criticise regulators for acting either too little, too slowly or inappropriately with regard to what could have been done prior to financial crises past, specifically the Great Financial Crisis of 2008. The research considers this angle specifically: the regulator’s responsibility to ensure financial stability in its financial system.

Roulet and Blundell-Wignall (2013) commented that the arrangement, powers and overlaps of supervisory bodies which govern activities in a financial market varies between financial markets. The players include central banks, consumer protection agencies, prudential regulators, the courts and international regulatory bodies.

2.3.2 How are online P2P lending platforms currently regulated across jurisdictions?

In the US, the Securities Exchange Commission (SEC) decreed that online P2P lending platforms must register under the Securities Act of 1933. As such, the resultant

investments made by lenders on the P2P platform shall not be protected by the Federal Deposit Insurance Corporation (FDIC), unlike deposits with banks (Chuang et al., 2016). Importantly, this differentiates between an investor and a depositor: investors choose to invest in securities governed by the SEC whilst a depositor places money with a bank protected by the FDIC. The borrower side of the P2P lending equation is governed by banking law (Chaffee & Rapp, 2012). However, akin to the situation in South Africa, there is limited protective legislation in the United States for commercial lending (non- consumer lending) (Douglas, 2016). This implies a "businesses can look after themselves" approach by the US regulator.

In the case of Reves v. Ernst & Young, 494 U.S. 56 (1990), the Court found the definition of a “security” to be broad: “any instrument that might be sold as an investment”, but went onto exclude certain categories that do not fall under securities law. As such, notes issued under P2P lending arrangements are presumed securities although on a case by case basis a particular note may be excluded should it fall into one of the Court’s defined categories. Douglas (2016) outlined the requirements on P2P platforms when issuing notes regulated as securities by the SEC: an evaluation of the ultimate lender to ensure his status as a sophisticated investor (implying that he is not a depositor); solicitation to a wide array of unrelated investors (thus avoiding concentration risks); and the degree to which the lender is reliant on the P2P platform to administer the notes. Douglas (2016) was unclear as to how effectively these measures are being implemented. The reliance on the P2P platform to ensure that lenders are sophisticated investors is hefty. P2P notes where the borrower seeks to raise capital for business purposes and the lender seeks primarily to make a profit will most likely be deemed securities (Chaffee & Rapp, 2012). Should P2P platforms wish to avoid the securities regulation, one avenue could be to exclude the note issuing bank from the lending arrangement. Alternatively, the overarching regulating body in the US could be the Consumer Financial Protection Bureau, whose primary role in lending regulation is to ensure that borrowers do not over indebt themselves and are not charged exorbitant interest rates. However, this approach may neglect to protect the interests of the lenders as investors. Chaffee and Rapp (2012) put it bluntly as “Proper Marketplace [a P2P lender in the US] wants all the benefits of selling securities without the robust regulatory protections for investors [lenders]”.

In the US, both state by state and overarching federal regulations apply to financial entities and intermediaries. To avoid having to comply with several pieces of regulation pertaining to credit extension, bank licensing and consumer protection, several P2P lenders adopted what has become a popular approach. A P2P lender would partner with

a bank who originated the loan to the lender. The P2P platform managed the marketing, facilitation and maintenance the direct client relationship. Shortly after the origination of the loan by the bank, the P2P lender would purchase the loan from the bank. This approach recently came under fire in the courtrooms in several states where the courts called it a clear bypass tactic and that the P2P platform was in essence the true lender (Douglas, 2016). Indicative of the pressure in the industry, SoFi applied for a banking license with the Utah state authorities in the US in June 2017. However, they have since withdrawn their application (Reuters, 2017).

P2P platforms are regulated by the Financial Conduct Authority (FCA) in the UK and, similarly to the US, lenders are not protected by the state as depositors. However, the Financial Services Compensation Scheme may protect lenders for up to GBP 50 000 who suffer losses as a result of “unsuitable advice” but not losses arising purely from the default of the underlying credit risk (FSCS, 2016). The FSCS has provides protection for depositors with banks and building societies for up to GBP 85 000 (FSCS, n.d.). Similar to the case in the US with SoFi, in 2017 Zopa also applied to the UK regulator for a banking license. It has raised GBP 32 million to date toward the minimum estimated capital requirement of GBP 150 million (Hosking, 2017). Both cases present evidence of the pressure on P2P lenders to clarify and remain on the side of the line that determines whether or not they are banks. It also indicates that becoming a bank is no mean feat as the compliance with capital requirements are weighty. P2P lenders in Germany are required to comply with banking regulation, which many do by partnering with an established bank (Fellow Finance, 2017).

Wang, Shen and Huang (2016) and Wei (2015) provided insight into the regulatory environment in China, where there has been limited, lax regulation around P2P lending for many years. In December 2015, the regulators proposed, in draft form, that P2P platforms should behave and be regulated as information (not credit) intermediaries; no minimum registered capital requirements would apply; and local financial authorities should take the leading role in supervising P2P platforms (Wang et al., 2016). Wang, Shen and Huang’s (2016) view was that the China Banking Regulatory Commission (CBRC) should take the leading role in P2P regulation in China; minimum entrance requirements should apply to P2P platforms; registered capital should be enforced (regardless of whether the P2P platform be an information or credit intermediary); certain transactions and borrowers should be prohibited; and the transparent provision of complete information should be strictly enforced. The last point speaks to the eradication of asymmetric information.

Wang, Shen and Huang (2016) explored whether P2P platforms in China should be regarded as information intermediaries rather than credit intermediaries. They found that P2P platforms do not provide sufficient information for lenders to make fully informed investment decisions and as such the P2P platform is acting as a credit intermediary rather than an information intermediary. The views were mixed: Wei (2015) countered the view when he found that the regulation applied to P2P lenders in China should be in line with their primary function as a provider of information not credit. This begs the question on whether P2P platforms should then be regulated as credit intermediaries or information intermediaries. Both link with the theory of financial intermediation and the debate hints at the importance of consumer protection. The distinction is important: to the extent that the P2P platforms is acting as a credit intermediary, lenders look to the P2P platform for delivery. To the extent that the P2P platform is acting as an information intermediary, lenders are acting as informed investors.

Chaffee and Rapp (2012) recommend a multifaceted approach to regulating P2P lending, much like traditional lending via banks, whereby different state and federal bodies would regulate different aspects of the P2P market. They are of the view that the Government Accountability Office report in the US failed to address the critical concerns at hand (Chaffee & Rapp, 2012). They sympathise with the regulators to some extent as P2P lending platforms confuse the existing definitions of securities, exchanges and issuers. This speaks directly to the requirement for research in the field of regulating online P2P platforms. 2.3.3 How are online P2P lending platforms currently regulated in South Africa?

2.3.3.1 The Banks Act

A key piece of legislation of which P2P lenders in South Africa are congisant is the Banks Act. The South African Banks Act of 1990 (and the Banks Amendment Act of 2015) defines the business of a bank as:

- The taking of or soliciation for deposits from the general public; - The taking of money from the public (including corporates) with an undertaking to repay said money on demand or otherwise, conditionally or unconditionally, with or without interest (Republic of South Africa, 2015).

With this in mind, the regulation proceeds to dictate that no person (justistic or natural) shall perform the business of a bank unelss that person (or entity in practical terms) is a public company and registered as a bank in terms of the Banks Act. Critical to this

definition is the understanding of the term “deposit” in the context of the Banks Act: in essence it is an amount of money paid by one person to another subject to an agreement which dictates that the amount will be repaid with or without a premium, on demand or on specificed dates or subject to specific circumstances. The definitoin is a broad one and ignores the element of consumer intention (to deposit or to invest?). FinTech companies in South Africa are at risk of digressing the Banks Act without intention (Dewar & Shilongo, 2017).

A critical element of the Banks Act of 1990 is the required compliance of banks in South Africa with the liquidity and capital adequacy ratios as defined in the act (Republic of South Africa, 2015), the principles of which are in turn drawn from the Basel III (presently) framework as drafted by the Basel Committee on Banking Supervision (Bank for International Settlements, n.d.). The Basel III framework is a global volunatry best practices framework desinged specifically to improve financial stabitlity in financial systems where banks are the dominant players (Bank for International Settlements, n.d.). Regulators in jurisdictions across the globe have incorporated Basel III principles into their own regulations. These requirements translate into ratios that banks need to meet and report to the South African Reserve Bank (Republic of South Africa, 2015). The liquidity related ratios in essence require banks to hold sufficient cash reserves to meet short term obligations. Also, they mitigate the amount of maturity transforamtion that banks are permitted to perform on balance sheet (in other words, the difference between short term liabilites and long term assets). The capital adequacy ratios require banks to hold specific amounts and types of capital (equity) such that the loss buffer on a bank’s balance sheet is (in theory) large enough to withstand financial distress and absorb losses without affecting despositors (Bank for International Settlements, n.d.).

A P2P lending platform that is setup akin to the categtory one operating strucutre in essence is not involving its balance sheet by accepting deposits and as such broadly avoids the reach of the Banks Act.

2.3.3.2 The National Credit Act of 2005 (“NCA”)

The NCA is overseen by the National Credit Regulator (“NCR”). Broadly speaking, it is the legislation that advocates consumer protectionism. The act applies to all persons (juristic or natural) whose net asset value is less than R1 million. It dictates that any party (juristic or natural) which lends money must register with the NCR as a credit provider. At present, the NCA does apply to P2P lending platforms and requires them to register as credit providers. As a registered credit provider, P2P lenders are subject to the NCA’s constraints around fees, charges, interest and credit vetting processes (Dewar &

Shilongo, 2017). However, the problematic element of the NCA is that it requires all the lenders via the P2P platforms to register as credit providers as well (Dewar & Shilongo, 2017), which is nonsensical for the P2P business model given the granular, low quantum, high volume nature of the retail consumer loans that P2P platforms traditionally generate.

The role and structure of the NCA and NCR are not dissimilar to the Consumer Financial Protection Bureau in the US (Chaffee & Rapp, 2012). However, South Africa has opted to place P2P lending under the curatorship of the NCR whilst the US has opted specifically not to do so, instead placing P2P lending under the umbrella of the SEC. The US approach allows for the practical continuation of P2P lending to retail individual borrowers, whilst the South African approach renders this largely impractical.

The only P2P platform operating structure present in South Africa at present is the category one operating structure (as defined for descriptive purposes by the author). As such, P2P lenders in South Africa are subject to the NCA but not to the Banks Act (Dewar & Shilongo, 2017).

2.3.4 Linking banking theory with regulation

Werner (2016) provided insight into the reign of the fractional reserve theory of banking in the late 1900s and as such the focus of regulation on reserve requirements. The more recent dominance of financial intermediation theory is strongly associated with the development of capital adequacy regulation. Whether capital adequacy regulations are effective or not depends on one’s view of the control of money supply. Financial intermediation theory of banking purports that banks are not able to change money supply whereas credit creation theory of banking propositions the opposite and as such deems capital adequacy regulation futile. If banks can continue to expand monetary supply (whether capital adequacy regulation is applied or not) and as such inflate asset prices, it follows that boom-bust financial crises remain a threat despite capital requirements (Werner, 2016).

Because Werner (2016) ultimately supported the credit creation theory his consequential argument was that as banks are able to create money, they are also able to create capital and meet capital adequacy ratios without simultaneously restricting their lending capacity. As such, in Werner’s (2016) view, meeting capital adequacy ratios is not in itself comfort that financial crises shall be averted. This is at odds with the view purported by Roulet & Blundell-Wignall (2013) who argued that whilst liquidity and capital requirements (as defined by banking regulation) may not eradicate systemic risk, they do mitigate it.

2.4 Systemic risk

Where the author refers to systemic risk through the research, she means in the financial sense.

Systemic risk arises when the financial distress or failure of a participant in the financial market causes significant disruption to the wider financial system and economic activity because of either the size, complexity or system interconnectedness with other financial market participants (Moshirian, 2012). As such, the transmission of financial losses, distress or collapse from one financial market participant to the next via interrelated transactions poses system wide distress. This was referred to as contagion by Staum (2012). Roulet and Blundell-Wignall (2013) referred to systemic risk in the context of macro prudential policy: prudential tools put in place to limit systemic financial risk. They continued that the root causes of systemic risk originate from three activities, namely maturity transformation, leverage and credit intermediation. These activities are instigated in the financial markets by a variety of players, not banks alone. They noted that the relative size of players in the financial system is an influential factor, where bigger players pose more risk.

Regarding maturity transformation, Diamond and Rajan (2001) confirmed that it has long been the business of a bank to aggregate and manage liquidity mismatches and as such meet the liquidity needs of the market; in essence managing maturity transformation. They argued that the existing theories of banking do not adequately explain a bank's ability to perform the liquidity mismatch management function in a fashion superior to both insurance firms and investment funds.

In the early days of defining the term financial distress, Beaver (1966) put it as the liquidation, insolvency or bankruptcy of a firm in favour of a creditor, or simply the default on loan and preference share obligations by a firm. Foster (1986) differed in his view, commenting that bankruptcy is a legal event. He defined financial distress as unresolvable liquidity problems leading to the restructuring of firms’ operations and structure. The views connect the elements of (a) risk of default (a firm failing to make good on its obligations) and (b) a shortage of liquidity with the state of financial distress, which runs the risk of spreading if systemic risk is present in the financial system (as above). This illustrates the rationale behind liquidity requirements: if forced to hold adequate liquid reserves to meet short term liabilities, the risk of a liquidity shortage is reduced.

Fernando and Herring (2002) commented that literature has traditionally attributed market collapses to the formation of an asset bubble and/or severe information asymmetry. They argue that this applies particularly to complicated financial products where information asymmetry presents opportunity for exploitation. Emekter, Tu, Jirasakuldech and Lu (2015) inferred that P2P lending opens the door for information asymmetry to exist.

However, Fernando and Herring (2001) continued differently, saying that a shift in market participants expectations of liquidity availability can also contribute (at times significantly so) to the deterioration of a market. Their work was done with particular reference to perpetual preference shares, a type of financial instrument. They voiced a concern that similar dynamics could apply to unseasoned financial products, specifically those that are rolled out with the hopeful expectation that secondary markets will develop to provide expected or required liquidity. Fernando and Herring (2002) connected the concepts of confidence and liquidity, saying that it is when investors lose confidence in the liquidity availability of a market (often in the form of secondary market trading) that distress may intensify. Importantly, it is when investors expect liquidity that they subsequently find they cannot realize that this scenario applies. Fernando and Herring (2002) specified the type of liquidity shock that should concern one most: systemic liquidity shocks that result in a permanent state of illiquidity. This ties together the concepts of systemic risk, liquidity issues and financial distress.

In essence, Fernando and Herring (2002) proposed that it is confidence that fuels liquidity and vice versa, a pivotal and at times precarious relationship. They concluded that inflated market prices (bubble behaviour) and information asymmetry are likely but not necessary factors for market collapse. When investors do not realise liquidity they expect or require, that in itself is sufficient to trigger financial distress and potential market collapse. It is therefore critical that the type of investor that enters a market and what he/she requires is matched with what the market can offer (Fernando & Herring, 2002). Diamond and Rajan (2000) reinforced that the banking system's capital structure is vulnerable to runs on the bank, hence the criticality of confidence in the system.

Werner (2016) spoke of the workings of the interbank system: for every increase on the asset side of one bank’s balance sheet there should be an equal increase on the liability side of another bank’s balance sheet. As such, banks that share a financial system are intrinsically interconnected. To the extent that banks lend out money at similar rates and share the distribution of customers, interbank assets and liabilities can be netted off and create credit exponentially without losing money (this connects with the credit creation

theory). This is supported by Staum (2012), who noted that removing a bank from the system would result in “holes” in other banks’ balance sheets. This echoes with Moshirian (2012) point on losses due to connectivity. Moshirian (2011) spoke about the G20’s decree that the Bank for International Settlements (BIS) should work closely with the Financial Services Board (FSB) and similar institutions to implement macro- prudential tools that allow improved coordination between banks, shadow banks and other financial institutions in the interest of mitigating systemic risk.

Roulet and Blundell-Wignall (2013) highlighted liquidity and capital requirements as critical tools to counter systemic risk and as such important factors to consider for the regulation of banks. Wei (2015) cited low levels of capital as one of the key reasons why Chinese P2P platforms were folding during 2014 and 2015. The Basel Committee of Banking Supervision’s (BCBS) subsequent focus thereon during its drafting of the Basel international regulatory framework for banks, with the intention of combatting systemic risk, is testament to this (Bank for International Settlements, n.d.). Guided by the Basel framework, banking regulation (for example the Dodd-Frank Act of 2010 in the US) as a financial protectionism mechanism has intensified since the GFC in 2008. One of its intentions is to contain systemic risk by stipulating requirements for banks and financial market participants which may lessen the impact they have on one another in an event of default (Moshirian, 2011).

Werner (2016) commen ted that banks’ compliance with capital adequacy requirements does not necessarily avert financial crisis. Rather, central bank guidance of bank credit extension and systems together with a market populated with small banks goes further toward mitigating financial risk and supporting stable growth. However, this contradicts with the financial intermediation theory and the view of the Bank for International Settlements (n.d.).

Not in combat with capital requirements but rather with the intention of voicing an alternative, Diamond and Rajan (2000) commented that diversification offers an alternative to bank capital as a risk mitigation tool. However, this was in the context of idiosyncratic not systemic risk. Wei (2015), however, did comment explicitly that the diversification of P2P loan portfolios could reduce the build-up of systemic risk.

Chaffee and Rapp (2012) spoke of the stifling effect of overregulation of P2P platforms in the US, where some believe it is inhibiting the industry’s ability to grow. Grant Thornton (2015) commented that the oversight of P2P lending by the Financial Conduct Authority in the UK may well lead to several P2P platforms exiting the industry due the cost of compliance. However, this is countered by the view that underregulated financial

services industries pose risk to the system (Wei, 2015) as they grow quickly and then crash. The case of TrustBuddy, a Swedish P2P platform founded in 2009, evidenced this: it grew quickly in a largely unregulated environment in Sweden and subsequently went bankrupt (Financial Times, 2015). Moshirian (2011) commented that it is the lack of effective regulation that allows financial risk to breed. With specific reference to the Chinese market, Wei (2015) also confirmed that P2P lending is a high-risk game. He commented on the irony of its relative popularity in China (much more so compared with other markets) versus the unregulated space in which it has grown. To Wei's (2015) mind, remaining unregulated is dangerous. Wei (2015) connected the concepts of P2P lending, systemic risk and shadow banking.

Multiple credit risk exposure for lenders is a concern. Despite individuals taking on risk to one another via the P2P loan, the P2P platform and the note issuing bank (in the case of Prosper Marketplace (2017), for example) indicates that a lender takes on risk to all three parties: the P2P intermediary, the note issuing bank and the ultimate individual borrower to whom the default terms of the note are referenced (Chaffee & Rapp, 2012). As such, one might argue that a lender is taking on more risk than had he lent to the bank alone. However, the creditworthiness of a bank compared with borrower through a P2P platform differs. In the TrustBuddy case, at the point of bankruptcy, GBP 21 million of lenders’ money was trapped in the platform. This raised the debate about ringfencing client monies (Financial Times, 2015).

This leads to the question as to what effect it may have on the broader financial system if P2P loan books continue to grow in either disjointed or loosely regulated spaces. In April 2016, 40% of China’s P2P platforms were deemed problematic (Wang et al., 2016).

Wei (2015) illustrated that there are numerous examples of Chinese P2P platform owners stepping in to repay the lender when the borrower defaults. This indicated a divorce between the lender and borrower and interposed the P2P platform as a credit counterparty. Whether explicit in the contract or not, the lenders therefore looked to the P2P platform to gauge the creditworthiness of the transaction. When defaults started to climb and dozens of P2P platforms were folding around 2014 (circa 275 P2P platforms were "in trouble" of which 115 folded) civil anger climaxed in protests demanding that the industry be adequately regulated (Wei, 2015).

At their cores, traditional banks are borrowers for shorter terms at lower margins and lenders for longer terms at higher margins (Diamond & Rajan, 2001). It is these activities, the bank guaranteed nature of deposits (regardless of the performance of investments), the mismatches therebetween and the balance sheet implications (Werner, 2016) that

attract the compliance and capital requirements from bank regulators (Bank for International Settlements, n.d.). To imagine that borrowers and lenders can meet without the impact of such regulations is initially bizarre: on the plus side, the regulations exist to protect lenders (and the broader financial system) from the risk of capital loss (Bank for International Settlements, n.d.; Republic of South Africa, 2015) and borrowers from abuse (Dewar & Shilongo, 2017) whilst on the downside compliance with regulations is costly (Grant Thornton, 2015). Traditional banks are increasingly costly organisations to run due to capital regulations and compliance requirements (Chuen & Teo, 2015). Emekter, Tu, Jirasakuldech and Lu (2015) confirmed that P2P lending is a riskier investment for lenders compared with traditional alternatives. To add practicality to the concept: The Alternative Finance Benchmarking Report surveyed 66 online alternative lending platforms in 46 African countries and 12 Middle East countries. Its survey concluded that 38% of survey respondents were concerned about default rates of loans on the P2P platforms, 36% were concerned about the collapse of a major platform whilst 42% feared changes in regulation (Zhang et al., 2017). This is indicative of a real-world concern about the risks posed by P2P lending platforms.

With respect to the effects of exchange control on systemic risk, it is known that the mandate of the South African Reserve Bank is to mitigate systemic risk within the South African financial system (South African Reserve Bank, n.d.-c). The South African exchange control regulation largely restricts the interaction of its domestic financial system with foreign ones (Republic of South Africa, 2016), which may lead to the containment of financial risk within the South African market. However, Moshirian (2011) argued that, despite individual country’s efforts to mitigate systemic risk through exchange control regulation, this cannot be achieved until there is one globally consistent regulatory framework in place because the free flow of money between nations persists. Roulet and Blundell-Wignall (2013) spoke about the “impossible trinity”: a financial market (or country) cannot have an open capital account and a managed exchange rate whilst maintaining independent monetary policy. Also, open capital accounts expose economies to the liquidity shocks associated with capital in flight. Roulet and Blundell- Wignall (2013) put these forward as potential justifications for exchange control measure.

2.5 Regulating online P2P lenders like banks

The regulation of P2P lending platforms in critical markets like the US, UK and China does not include liquidity and capital regulation in a fashion similar to banks (Chaffee & Rapp, 2012; FSCS, 2016; Wang et al., 2016). Given the evolution of the P2P lending industry and the nature of financial intermediary role that they are enacting, the questions

arose as to whether P2P lending platforms are behaving like banks, whether they pose systemic risk and as such should attract appropriate regulation, specifically liquidity and capital controls, to mitigate the systemic risk threat.

The research considered P2P platforms through the lens of banking theory, specifically financial intermediation theory, in order to understand whether P2P platforms are in essence behaving as banks and whether they pose similar systemic risks as banks, set in the context of the interplay between banking theory, regulation and systemic risk.

P2P platforms in South Africa are presently not taking on and guaranteeing deposits and as such are not deemed banks in the eyes of the South African Reserve Bank (Dewar & Shilongo, 2017). However, the evolving nature of the P2P lending industry, its growth momentum and the various P2P platform operating structures that have developed across jurisdictions indicated that a complete understanding was required to appreciate the various scenarios that could unfold in the South African market.

3. CHAPTER 3: RESEARCH QUESTIONS

Leading from Chapters 1 and 2, it has been noted that the P2P lending industry is growing and evolving; P2P platforms exist in a variety of forms (various operating structures per section 2.1.4); and that there exists a call from academia for appropriate regulation of P2P platforms (per section 1.2.3), the shape of which is unclear. Banking theory (section 2.2) allowed the author to analyse the behaviour of P2P platforms and consider the (possible) effects therefrom in the context of systemic risk (section 2.4). To the extent that P2P platforms fit with banking theory and systemic risk is found to be a threat, it may be prudent to apply liquidity and capital requirements (as drawn from banking regulation) to mitigate the systemic risk (section 2.3.4).

The author pursued specific research questions in order to address the overarching research problem: should online P2P lending platforms be regulated like banks in South Africa, with specific respect to liquidity and capital? The research problem and the research questions are summarised as follows:

3.1 Research problem

Should online P2P lending platforms be regulated like banks in South Africa, with specific respect to liquidity and capital requirements?

3.1.1 Research question one

Are online P2P lending platforms behaving like banks?

3.1.2 Research question two

Do online P2P lending platforms pose systemic risk to the South African financial system, specifically in the absence of liquidity and capital regulation?

The independent variables are depicted by the two research questions: whether or not P2P platforms are behaving like banks and whether or not they pose systemic risk. The dependent variable is described in the research problem: whether or not P2P platforms should be regulated like banks. As such, the causality flows from the research questions to the research problem: if the research questions are affirmed, it follows that P2P platforms should be regulated like banks.

The research was conducted in the academic realm of macroeconomics, specifically finance and banking.

4. CHAPTER 4: RESEARCH METHODOLOGY (Appendices 1 and 4 to 12 may refer)

The author sought to establish whether P2P lending platforms should be regulated like banks in South Africa. Here following the selected methodology, being qualitative exploratory research, is described and justified as appropriate to investigate the research problem. The research design elements (including population and sampling) and the data analysis process are addressed in detail. Lastly, the quality of the research is interrogated.

4.1 Choice of methodology

The author proposed that it was a matter not easily commoditised by units of measurement (alignment with theory, assessing behaviour, identifying systemic risk) and that contextual factors played a significant role. Further, online P2P lending platforms are a relatively new concept and the constituent parts (borrowers, lenders, securities and exchanges) do not fit neatly into existing regulatory definitions (Chaffee & Rapp, 2012). Online P2P lending is in its infancy as an industry in South Africa, with the first P2P platform launched in 2012 (RainFin, 2012). As such, the author sought expert opinion as to whether P2P platforms fitted within the scope of banking theory. Also, systemic risk manifests itself in financial distress followed by potential collapse (Moshirian, 2011;

Staum, 2012), which are infrequent high impact events in financial markets. The author therefore adopted a qualitative approach. It is the views of (driven by the factors valued by) the individuals interviewed (Whitaker, 2016) that aid the body of knowledge to determine whether P2P platforms fit within the theory of banking and realm of banking regulation.

At the time of the research, it was (and may remain) unclear whether P2P lending platforms are mimicking bank behaviour in the eyes of financial intermediation theory. Also, whether P2P lending platforms pose systemic risk. Consequently, the research was exploratory.

The author elected qualitative, exploratory data, believing it to be the best fit to investigate the research question as an insider perspective was required (Whitaker, 2016) to fully appreciate how and why P2P platforms could be behaving like banks and why they may pose systemic risk. The questions at hand are intricate debates in the financial field, attracting the attention of esteemed academics and industry practitioners. It is their experience and in-depth knowledge that sets their views apart in value from others. As such, the interviewees’ frames of reference (Whitaker, 2016) were important

for the research as their experience and foresight in the field allows readers of the research to better appreciate the interlinked effects of the components at play. Creswell (2013) reinforced this saying qualitative research allows for the interviewees’ meanings and subjective views to be heard and analysed. In this light, in-depth semi-structured interviews were fitting as the research strategy (Whitaker, 2016).

Industry metrics were obtained to create the context in which the results could be analysed. Such data included the various legal and financial structures used by P2P platforms to effect transactions; the quantum of P2P loan books; and the risk mitigation structures put in place by P2P platforms. Please refer to section 2.1.4 and Appendix 3 for details thereon.

The author applied mono data method being qualitative with data collection via in-depth semi-structured interviews. The author created approximately 13.5 hours of audio during the interview process. The audio files and subsequent transcripts from the in-depth semi- structured interviews (Saunders & Lewis, 2012) were the key source of data (refer to the “Data gathering” section) which were analysed in the context of the literature and the P2P lending industry metrics. Shenton (2004) confirmed that triangulation compensates for the limitations of a particular method. The author relied on the mixture of literature, P2P lending industry data and multiple interviewees from a variety of trades to corroborate findings.

Whilst the research was not intended as a short-term snapshot, the concept of online P2P lending is relatively recent in academia and limited with respect to South Africa. The author’s research timeline was dictated. As such, the timeframe for the research is cross- sectional (Saunders & Lewis, 2012).

The approach of the research included elements of both deduction and induction. The theory of banking, specifically financial intermediation, was applied. Literature on the other related concepts (systemic risk, regulation, P2P lending) also shaped the approach. As such, existing theory was used to shape the lens through which the matter was analysed and guided the data collection process, hence a strong deductive drive (Saunders & Lewis, 2012). Several of the questions in the interview guide were born from the theory: investigating systemic risk, banking regulatory elements and the application of banking theories to P2P lending platforms. These questions and the subsequent analysis of the responses thereto embodied the deductive portion of the research (Saunders & Lewis, 2012). However, an inductive element existed in parallel: the exploratory nature of the research and interviewing of experts in the field to discover insights on the research questions was a bottom-up inductive approach (Creswell, 2013).

The questions posed to interviewees included “whether” P2P platforms are behaving like banks or pose systemic risk, often investigating the opinion of the expert on unclear matters. As such, the research was partly inductive (Saunders & Lewis, 2012). Creswell (2013) provided comfort saying that qualitative research involves complex reasoning that going between both deductive and inductive approaches. The author’s primary approach was deductive. However, given the lack of research that compares P2P lending directly with banking and also in the context of South Africa, an inductive influence was sensible.

The research philosophy was one of pragmatism (Saunders & Lewis, 2012): the exploratory nature of the research required that the author acted nimbly throughout the research process to ensure that maximum value was gained during data collection and that relevant supplementary issues were duly considered. As such, the author acted as required in various contexts to address the research question in a valuable way, placing central emphasis on the research question and objectives (Saunders & Lewis, 2012). Creswell (2013) commented that the qualitative research route requires an emerging evolving design. The author therefore maintained an open mind to the influence of the inductive components on the research throughout the process. Beyond pragmatism, the research philosophy contained an element of critical realism, as it holds true that if P2P lending platforms were found to pose systemic risk, said risk existed independently of our knowledge thereof and our subjective processing of the indications of its existence required consideration (Saunders & Lewis, 2012).

4.2 Research design elements (Refer to Appendix 1 for the Consistency Matrix)

4.2.1 Population

The population was skilled professionals working (or having previously worked) in the trades of banking, lending, risk management or regulation in South Africa, both male and female, regarded as experts in their trades. The skilled professionals must have had (or continued to have) exposure to P2P lending. As such, the qualifying criteria at the time of the research were as follows: a) the skilled professionals were regarded as experts in their field by the working community; b) their areas of knowledge and skill had relevance to P2P lending; and c) they must have had (or continued to have) exposure to P2P lending.

This aligned with work by Ericsson (2006) where he described certain criteria to identify experts which included their social reputation, accumulated accessible knowledge and their length of experience in the area.

In this light, the author contested that the skilled professionals would provide relevant insight into the research questions posed as experts in their fields.

4.2.2 Sampling method

Non-probability sampling methods were utilised. Overarchingly, the author pursued the purposive sampling method of criterion sampling as the author strategically selected the skilled professionals who fitted the population criteria (Miles & Huberman, 1994) and conducted interviews with those skilled professionals. Creswell (2013) confirmed that criterion sampling is useful for quality assurance.

Stratified purposeful sampling was applied insofar as the author sought interviewees across the range of trades (banking, lending, risk management and regulation) which required seeking interviewees across institution types (banks, other financial intermediaries, legal firms, risk management firms, financial consultancies and regulatory bodies) (Creswell, 2013). Although not evenly distributed, the author pursued interviewees until such a time that all the trades and all the institution types were represented in the sample.

Quota sampling also played a role as the author continued the research process until such a time that the sample size was considered healthy (Saunders & Lewis, 2012), which was gauged by literature (below) and the saturation levels apparent from the coding. Refer to 5.2 for details on the saturation analysis.

In order to gauge whether the selected skilled professionals fulfilled the abovementioned population criteria, the author applied two key factors when selecting skilled professionals: (1) position(s) held at either a banking, financial intermediary, lending, law, risk management firm or regulatory body and (2) years’ experience in the trade. The author pursued skilled professionals that held middle to upper level positions only at banks, other financial intermediaries, legal firms, risk management firms, financial consultancies and regulatory bodies with at least ten years’ experience in the industry or in his/her trade. This aligned with Ericson’s (2006) view that experience in the area of expertise should at least exceed ten years. Ericson (2006) purported that it is experience relating specifically to cognitive work that develops experts, not automatic work. It was with this in mind that the author targeted skilled professionals holding middle to upper level positions at their institutions.

The selection of skilled professionals ensured that (a) they were regarded as experts in their field by the working community; (b) their areas of knowledge had relevance to P2P lending; and (c) they must have had (or continue to have) exposure to P2P lending. In

this light, the author contested that the skilled professionals would provide relevant insight into the research questions posed.

See section 5.1 and Appendix 5 for detailed descriptions of the 18 interviews and 19 interviewees that make up the sample. Two interviewees shared a joint interview and were considered as one unit of analysis, hence 18 interviews presented as transcripts were coded and analysed.

The bankers interviewed were spread across various functions: treasury management, regulation, product development, credit risk and proprietary trading. Often, the bankers’ knowledge spread across several aspects of lending and regulation as their roles required them to act in the cross section between those spheres. The regulators that were interviewed, by contrast, had specific knowledge relating to relatively narrow spheres.

Digital business people were particularly familiar with P2P lending platforms as they had both researched and considered them from business investment points of view. The author found that digital teams were often set up as think tanks with innovation mandates and were housed elsewhere in the broader financial groups, separate from the primary businesses. This was done to minimise conflict of interest and to create open space for creative exploration.

4.2.3 Sampling size

Insight from Guest, Bunce and Johnson (2006) advised that twelve interviews are required as a sample size when in-depth interviews are the data collection method of choice. At that point, an author can expect data saturation. However, the author was cognisant of the insight from Morse (2000) that the research design, nature of the topic and quality of data can also influence data saturation. The broader the scope of the study, the longer it will take to reach saturation. There are risks in both directions: narrowing one’s focus too soon or too late. The scope of this study was limited to South Africa and was therefore relatively narrow. If the research questions are not obvious and are composed of principles that are difficult to understand and analyse (as the author believed was the case), more data points are required (Morse, 2000). On this basis, the author proposed increasing the number of interviews. The quality of data affects the saturation point insofar that better quality data (rich dialogue, clear insight into the research questions) will lead a researcher to saturation sooner (Morse, 2000). The author gauged this as the data collection progressed and believes that the conversations held with interviewees were indeed rich with insight and informed opinion. Morse (2000) proposed that grounded theory studies (which combines deductive and inductive

approaches (Saunders & Lewis, 2012)) may require 20 to 30 interviewees, with the possibility that each interviewee is interviewed more than once. Although the research design is not one of grounded theory, the author was cognisant that the research incorporates both deduction and incaution. Ultimately, the number of interviews and the quality of data will determine the amount of usable data (Morse, 2000). As such, the author targeted a sample size of 15 interviewees with a minimum of one interview per person.

In the end, the author pursued 19 interviews of which 18 were usable (the 19th remaining incomplete and as such was excluded from the sample). It was a combination of the author’s desire to gain a variety of opinions from various industry standpoints that drove her to continue pursuing interviews beyond the initially perceived saturation. This aligned with the application of stratified purposive sampling.

4.2.4 Unit of analysis

The unit of analysis was the views of a single skilled professional in the sample. Interview nine was a single unit of analysis although it included two interviewees. Because they shared a joint interview and spoke to shared views, the author elected to combine them as a single unit of analysis.

4.2.5 Measurement instrument

The author drafted an interview (discussion) guide to act as the research measurement instrument. It spoke of the key themes that the author wished to explore. Refer to Appendix 8 for the interview guide. In addition to the interview guide, interviewees were provided with the “Appendix to the interview guide” (Appendix 9) which summarised (a) broad categories describing the various operational structures of P2P lending platforms (per section 2.1.4) and (b) key elements of the banking theories considered in the research.

4.2.6 Data gathering process: in-depth semi-structured interviews

The author enacted the data collection and analysis processes. Shenton (2004) commented that the qualifications, background, and experience of the author are thus of importance to ensure credibility, perhaps of equal importance as the methodology applied. The author is qualified in the fields of finance and economics, which allowed her to grasp and penetrate certain of the key concepts at hand. At the time of the research, the author had eight years’ experience in the field of banking, risk management and regulation, thus was intimately familiar with certain of the critical issues the research sought to address. Creswell (2013) confirmed that qualitative research relies on the

researcher as a key data collection instrument and that his/her biography and biases may influence the data collection and analysis.

First, the author identified eligible skilled professionals who fitted the population criteria as detailed in section 4.2.2. Establishing a complete sampling frame was not a feasible endeavour for the author. An accurate list of all the adequately knowledgeable, experienced skilled professionals across the relevant trades (banking, lending, risk management and regulation) that have had exposure to P2P lending was not easily known. However, the author drafted a healthy sampling frame of eligible skilled professionals (as described under “Population”) which she formulated using a combination of publicly available professional information, relationships and referrals. The author investigated the interviewees thoroughly in advance to ensure their adequacy as experts in their fields and to ensure the author’s own best preparation for the interviews, setting herself up to extract maximum value.

Once satisfied with the eligibility of the targeted interviewee, the author commenced engagement with him/her. Initial contact was made either by phone, email or in person. A cover letter detailing the nature and context of the research, the researcher’s association with GIBS and contact details (for researcher and supervisor) was sent to the interviewee together with the interview guide and the appendix to the interview guide (refer to Appendices 8 and 9). As is desirable, this allowed the interviewee to review and

consider the questions ahead of the interview, as impromptu spontaneous answers from interviewees can prove less insightful (Saunders & Lewis, 2012). The author suspected that the opposite would apply: considered responses would be most beneficial. The author plans to both record the interviews (with due permission) and take notes during the sessions should key points arise or themes appear evident.

Interviews were set up well in advance most times via direct communication with the interviewee (on the odd occasion, a personal assistant aided with diary arrangements). As far as possible, face-to-face interviews were conducted. Location choice was driven by the interviewee as the author wished to ensure that interview process was both convenient and enjoyable. Several video conference and telephone interviews were conducted due to diary constraints, geographical location or interviewee preferences. Although these interviews remained effective in terms of addressing all the interview questions and sparking debate, Creswell (2013) noted that the downside to telephone interviews is that the author does not witness the informal communication, like body language and facial expressions.

The author adopted formal attire for the interviews and presented a printed pack of the interview documents upon arrival (Saunders & Lewis, 2012). Mack, Woodsong, MacQueen, Gust and Namey (2011) advised that that the interviewer should bear in mind that many an interviewee will be new to the interview process. As such, the interviewer (the author) should encourage the interviewee to speak without restraint, advise that the interviewer hopes to gain insight from the interviewee’s knowledge and that it is the interviewee’s personal opinion that is sought (there is no right answer). Importantly, the interviewee must be fully aware that the process is voluntary and he/she may opt out at any point (Mack, Woodsong, McQueen, Guest, & Namey, 2011). As such, the interview commenced with a “thank you”, an introductory brief on the purpose and nature of the research, an appeal that the interviewee should speak frankly and a statement that participation was voluntary. The author asked for permission to record the interview and, granted that the interviewee was comfortable to proceed, asked that the interviewee sign the consent form (Appendix 7) (Saunders & Lewis, 2012).

In-depth semi-structured interviews were conducted containing a mix of category, list and open questions (predominantly the latter) as laid out in the interview guide. Per Creswell (2013), the interview questions were open-ended and general, relating to the concepts that the author believed to be central to the research. The author opted for semi-structured interviews as the research was exploratory: the author was uncertain about what the answers from the interviewees would be and some of the questions were complicated (Whittaker, 2016). The first few questions were category and list questions to confirm the skilled professional’s fit with the population criteria (positions held at the institution; years’ experience in the trade; have had exposure to P2P lending). The interview questions then moved to specifying and probing questions to appreciate (a) why P2P lending platforms may or may not be behaving like banks in the context of banking theory (specifically financial intermediation theory) and (b) whether systemic risk should be of concern. In this way, sequencing was applied (Whitaker, 2016). The category questions later allowed the author to later analyse fundamental differences between the various sample subgroups. Statistical analysis was not performed on the categorical data. The author recorded the interviews using audio recording software on a smart phone device and took ad hoc notes throughout the interview process. The primary source of data was the audio files.

The interplay of P2P lending, banking theory, regulation and systemic risk resulted in rich intricate debate, as is evident in the literature review and the transcripts. At times, the author chose to vary the order in which the questions were answered to best suit the flow of the conversation. The author often probed further on intriguing or unclear

propositions so as to gain maximum insight from the conversations and to ensure that she truly grasped the interviewees’ messages (Saunders & Lewis, 2012).

4.2.7 Pre-test

The author conducted two interviews as a pilot test to assess the clarity of the interview guide, ensure that questions were not leading, test the questions’ ability to accurately target the required data, the emotional effect that questions had on interviewees and, importantly, to hone the author’s interview technique (Saunders & Lewis, 2012). The pilot test allowed the author to approximate the time required for a typical interview (Saunders & Lewis, 2012), which was circa 45 minutes. The two pilot interviewees fulfilled the population criteria and satisfied the sample requirements. Post the two pilot interviews, the author noted that there were insignificant changes to the interview guide, that the two interviews had been fairly similar and that rich insight had emerged. At a later stage, midway through the 18 interviews, the author further noted that the differences between the pilot interviews and first half of the interviews was insurmountable. As such, the author included the pilot interviews in the sample. To ensure that this did not compromise the data, the author extended the sample to include more interviews than planned.

4.2.8 Data analysis

The author appointed a professional transcriber to transcribe the audio files and produce typed transcripts, one per interview. The author commenced this process midway through the interviews to ensure adequate time management. Each transcript noted the following: interview number, audio file reference, interview date, interview place and the duration of each interview. Each interview was saved as a separate document file (Saunders & Lewis, 2012). Unlike the audio files, the transcripts ensured the anonymity of the interviewees as names and indicative information relating to the interviewees’ identity were removed. As such, a third-party reader of the transcript would not be able to ascertain the identity of the interviewee. In this way, the author could ensure the confidentiality of the interviewees as only she was aware of the interviewees’ true identity. The author checked all the transcripts against the audio files and her own notes to ensure the accuracy and anonymity of their content.

4.2.8.1 Coding process and notes

The author’s coding process was thorough, relying upon ATLAS.ti software to house the data, capture the codes, render the coded transcripts and apply analysis tools thereto. Prior to the coding of the transcripts, the author drafted a list of deductive codes drawn from the literature review that represented a range of feasible responses to the questions

in the interview guide. The deductive codes are listed in Table 1 and totalled 58. The deductive codes were categorised into code families that aligned with certain theoretical categories (concept buckets) which were then further categorised into super families which represented key themes that emerged from both the literature and the results (Saunders & Lewis, 2012; Whittaker, 2016; Saldana, 2015). This was consistent with the dual deductive-inductive approach to the research (Creswell, 2013).

Transcripts (reflecting the written version of the audio files from the interviews) were then loaded into ATLAS.ti and coded chronologically from interview one to interview 18. As the coding process unfolded, inductive codes organically arose from the interviews. The inductive codes are listed in Table 1 and totalled 78. All inductive codes were preceded by the asterisk (“*”) in the code name. The creation of inductive flows waned as the author continued through the interviews. Please refer to section 5.2 to view the saturation analysis relating to both the deductive and inductive codes. The inductive codes allowed the author to gain deeper insight into the mix of the interlinked issues and to identify where they related to theoretical concepts, some of which had already been considered in the literature review.

To clarify: the author applied a primarily deductive approach to the research whilst working harmoniously with the inductive influence given the exploratory nature of the research. To the coding process specifically, the author applied both deductive and

inductive approaches, where the initial list of deductive codes proved to be inadequate. Several of the inductive codes that arose during coding process tied back to pieces of literature that had been considered beforehand. However, it was unclear prior to coding whether or where certain theoretical concepts would apply directly to the interview responses. As such, several of the inductive codes connected the literature (aligning with the greater deductive drive of the overall research) whilst a handful of inductive codes remained entirely inductive in nature and did not connect with the literature review. Although literature may exist thereon, it was originally thought to be outside of the scope of this research. This process echoed with Creswell’s (2013) view that qualitative research often requires the researcher to move back and forth between deductive and inductive approaches, applying complex reasoning along the way.

Ultimately, the author was exhaustive in the coding process: all relevant concepts and quotes were coded, regardless of their frequency of occurrence across the spectrum. A total of 136 codes were used during the data analysis. Both during the coding process (where sensible) and once complete, the author revisited the code families and super families to ensure the consistent categorisation of both deductive and inductive codes

into families (concept buckets) and super families (themes). A total of 12 code families were formed deductively. A variety of the inductive codes aligned with existing deductive families, where the inductive codes expanded the reach of the concept. However, a handful of inductive codes led to the formation of four inductive code families, identifying concepts that the author had not yet considered in the scope of the research. The 16 code families can be viewed in Appendix 10.

Table 1: Code summary

Code Summary Number of deductive codes 58 Number of inductive codes 78 Total number of codes 136

The transcripts (each one representative of an interviewee, in one case two interviewees in a joint interview) were named such that each one illustrated the relevant characteristics of the interviewee, including title (where it reflected academic relation), position at institution and the type of institution that the interviewee worked for. The latter was indicative of the interviewee’s trade. In ATLAS.ti, the transcripts were categorised into groups where each group represented a trade: banking, lending, risk management or regulation. These are sample subgroups. Importantly, the sample subgroups were not constructed as mutually exclusive: although an interviewee may have worked for a bank, his/her trades (areas of knowledge and skill) may have included banking, lending and risk management. To ensure that interviewees were correctly categorised according to their trade (symptomatic of his/her area of expertise), the author (as the researcher) included a question at the beginning of the interview to confirm what the interviewee’s specific trade was. Thus, the author relied on data to categorise interviewees according to their trade(s). In addition to the four trades, two additional sample subgroups were created being an academic subgroup and a FinTech subgroup. Interviewees who had achieved a PhD or more (Professorship) were included in the academic sample subgroup. Interviewees who worked in the realm of FinTeh were included in the FinTech sample subgroup. The six sample subgroups allowed for meaningful data analysis when comparing their views of. Because each sample subgroup housed a different number of interviewees (one sample subgroup may have contained 13 interviewees whilst another contained nine), the author compared the percentages of interviewees in a subgroup that supported certain codes (this is evident in Chapter 5).

Table 2: Number of interviewees per sample subgroup

Sample subgroups Banking 13 Lending 9 Risk Management 13 Regulation 8 Academic 5 FinTech 8

The author presented the data using quotes, tables indicating overall code frequency, code occurrence per interview, tables showing the various groupings of the code families and transcripts and graphs. Therefrom the author was able to draw key insights and views (Whittaker, 2016) as to whether or not online P2P lending platform are behaving like banks and whether or not they pose systemic risk to the South African financial system, as discussed in Chapter 6.

4.2.9 Limitations

Limitations of the research included that the data was difficult to access given that it was not publicly available nor easily commoditised. Data on the balance sheet treatment and nature of the loan books of privately held P2P platforms across jurisdictions would have allowed the author to analyse the accounting treatment of P2P loans on balance sheets as dictated by regulatory governance.

Because P2P lending platforms are relatively new in South Africa (RainFin, 2017) and occasions of financial distress are relatively infrequent, the author’s ability to consider the relationship between regulation, systemic risk and P2P lending in times of financial distress was limited. As such, the research findings were largely theoretical in nature. Should South Africa experience a time of financial distress relating to online P2P lending platforms in the future, an analysis of the consequences therefrom can be corroborated with this research.

The author’s ability to source suitable skilled professionals for the sample was largely driven publicly available data and her extended professional network in Johannesburg, confirming that the sampling method was not random.

4.3 The quality of the research

Building on Lincoln and Guba’s founding work on qualitative research, Shenton (2004) spoke of the four elements that support the trustworthiness of qualitative research:

credibility, transferability, dependability and confirmability. In addressing these elements, one may counter the scepticism around the trustworthiness of qualitative research.

4.3.1 Credibility

Credibility of qualitative research relates to a true picture being presented on the matters being penetrated by the research (Shenton, 2004). This relates to the concept of internal validity (a term more commonly used in the context of quantitative research): the validity of the data refers to the extent that it accurately measures what is intended to be measured (Shenton, 2004; Whittaker, 2016). This first depends on the skilled professionals selected by the author. Some comfort is gained here in that skilled professionals in appropriate trades holding middle to upper positions with at least ten years of industry experience were selected. Secondly, the validity of the data is affected by the specific questions asked in the interview. As such, it is critical that the author (a) selected skilled professionals that certainly meet the population criteria and (b) asked questions that allowed the author to penetrate matters relating to the research questions directly to their cores. This speaks to the content validity (does the interview guide provide enough data to answer the research question?) and the construct validity (do the questions actually collect data on the issue they are intended to measure?) of the interview guide (Saunders & Lewis, 2012).

The data were enhanced by the rich dialogue in the interviews. Shenton (2004) and Creswell (2013) described several methods via which credibility thereof could be enhanced. Here follows a description of those that are pertinent to this research. Triangulation involves cross checking findings with data from other methods and sources. The author consistently moved between literature, P2P lending industry data and the research data results to formulate and corroborate findings. With respect to a variety of sources, the author consistently cross-checked the data between interviewees and believed that this was enhanced by the interviewees’ various trades as the same matters were considered from a variety of different angles. Iterative questioning on the key topics ensured that accurate insights were gained from different angles, diminishing the probability of miscommunication or deliberate falsehoods. The briefing of interviewees beforehand may have reduced the anxiety that they may have experienced. Ensuring the honesty of interviewees is important (Shenton, 2004). This was encouraged by emphasising voluntary participation, the independence of the author (without an agenda relating to P2P lending or related issues) and the option for interviewees to opt out during the process. Frequent debriefing sessions with the author’s supervisor and a peer review process were also tactics employed to aid the credibility (Shenton, 2004),

voiding the opportunity for the author to complete the process from beginning to end engulfed by her bias (known or unknown). These considerations together enhanced (although they may not have perfected) the congruency of the data with reality, which improves its credibility and therefore the overall trustworthiness of the research (Shenton, 2004).

4.3.2 Transferability

Creswell (2013) and Shenton (2004) advised that transferability (akin to external validity) is the degree to which the research findings can be cross applied to future research in other situations. This has been enhanced as the author described in rich detail the context and environment of the interviews (full content cover in audio and text, place and timing) and the interviewees (their backgrounds, education, experience). As such, future researchers can gauge whether the findings of this qualitative research are transferable to their research if shared characteristics exist (Creswell, 2013). Appendix 5 provides full detail on the number and location of interviews, the number and length of data collection sessions and the overall period of time of data collection (Shenton, 2004). Shenton (2004) cautioned against an infatuation with transferability to the extent that all inconsistencies in the data are brutally interrogated, when in fact multiple realities may exist which echoes with the very essence of qualitative research: context is important.

As the field of P2P lending in South Africa is relatively new (RainFin, 2017), the author suspected that the findings of the research could be useful to other authors in the field. However, as the scope was limited to South Africa; this may restrict its transferability to other economies that are not constructed similarly (consider the nature of an emerging market and the effect of exchange control).

4.3.3 Dependability

Dependability (akin to reliability) speaks to the consistency of the research findings: can they be repeated by another researcher who carries out a similar methodology? This is one of the more difficult elements for qualitative researchers to achieve and is argued to be closely linked with credibility (Shenton, 2004). Shenton (2004) advised that the author should provide extensive detail on three key elements to strengthen dependability: the research design, operational data collection processes and the reflective appraisal, which leads to the formation of findings. The author has addressed all three elements, providing thick detail on each. Concerns around the reliability of the data can be further allayed considering that a near identical process was applied for each interview (Whitaker, 2016): initial personal contact, an email briefing, an introductory word by the author and a recorded semi-structured interview conducted by the same interviewer (the

author). However, as the interviews were only semi (not fully) structured, the conversations varied, as did the level of penetrative detail provided by interviewees.

4.3.4 Confirmability

When addressing confirmability (akin to objectivity), the author must ensure that the research findings stem from the data collected (being the experiences of and insights from interviewees) and are not skewed by the author’s own bias (Shenton, 2004). Shenton (2004) commented that objectivity in quantitative research is confirmed by relying on non-human data collection and provision. In qualitative research this is impossible as it is founded on human interaction. Creswell (2013) also confirmed that the researcher is a key instrument in the data collection bias, unknowingly affecting the data collection with his/her social biography and bias. In order to monitor the effect of bias throughout the process, Shenton (2004) encouraged researchers to include reflective commentary in their research which described their evolution of thought on the research questions. This concept is linked with progressive subjectivity, ensuring that the author’s formation of findings is continuously drawn from the data as it is collected and analysed. It is important that researchers admit to their own views and biases which will allow readers of the research to appreciate the lens through which the reflective commentary is formed. Shenton (2004) also promoted the use of audit trails of both the data process and the evolution of thought toward findings to allow readers to gauge the

confirmability. The author bolster confirmability by saving various versions of the work- in-progress research document and supplementary data analysis files throughout the research process from January 2017 to November 2017, such that an audit trail exists that reflects the author’s journey as initial thoughts, findings and eventually insights were born, moulded and finalised.

Given the dual nature of the research as inductive in a new field, the author approached the process with an open mind as she was uncertain as to whether regulating P2P lending platforms like banks was sensible in the context of banking theory and systemic risk in South Africa. As such, objectivity (Whitaker, 2016) is partially reinforced as the exploratory nature of the research implied that the answer was unknown to the author. This is further reinforced by Mack, Woodsong, MacQueen, Guest and Namey (2011) in their work on qualitative research.

In closing Chapter 4, the author deemed the choice of methodology appropriate for the exploratory research, the process elements were considered in fine detail and the research quality was enhanced where achievable by the author.

5. CHAPTER 5: RESULTS (Appendices 5 and 8 to 12 may refer)

Chapter 5 provides rich detail on the interviewees that constituted the sample (Creswell, 2013) and illustrates the saturation achieved in the research. It then presents the data results ordered by the research problem and questions. The interview guide questions are addressed under each specific research question to which they relate. The key findings are summarised at the end of Chapter 5.

5.1 Description of the sample

The sample selection process is described in detail in sections 4.2.2 and 4.2.3. Sections 4.2.6 and 4.2.8.1 provide insight into the data gathering and coding processes. This section builds thereon describing the final sample and reiterating any concerns therewith.

Please refer to Appendix 5 for a complete summary of the sample group, including metrics across the interviewees’ trades, experience, skills and education.

The sample consisted of experts in the trades of banking, lending, regulation and risk management who had been (or were) exposed to P2P lending and could apply their knowledge and experience to the exploratory questions on online P2P lending platforms. The concept of P2P lending spreads across all the four fields. The interviewees were gauged as being experts by three tangible measures:

- they worked in or with institutions that related to one of the four trades, including banks, financial intermediaries, lending firms (including P2P lenders), legal firms, risk management firms or regulatory bodies; - they occupied mid-level to senior positions at their institutions; - they had a minimum of ten years relevant industry work experience.

The sample consisted of 18 interviews with skilled professionals with knowledge and expertise in their trades of banking, lending, risk management and regulation.

There were six interviewees who had in excess of 20 years’ experience in their trades at the time of the interviews. Three interviewees had less than 10 years’ experience in their trades. However, each was a valuable interviewee: the first (interviewee eight, labelled “Founder_FinTech Consultancy_170717” in ATLAS.ti) had eight years of relevant industry experience at the time of the interview. However, the interviewee had founded, managed and worked in a FinTech consultancy by the interview date, a feat indicative of his expert knowledge relevant to the research. As such, the interviewee was included in the sample. The second (interviewee 12, labelled “Founder MD_P2P Lender_280717” in

ATLAS.ti) has founded and runs an online P2P lending platform in South Africa. Given the rarity of P2P platforms in South Africa, this experience was deemed valuable. The last (interviewee 18, labelled “Financial Stability Analyst_Regulator_140817” in ATLAS.ti) was a member of a regulatory body investigating how P2P lending platforms should be regulated in South Africa. The author found that there were few such people in the regulatory authorities (interviewee 16 was also a member of a regulatory body involved with investigation into P2P lenders).

In terms of the types of institutions where the interviewees worked at the time of the interviews:

- three were at financial intermediaries (investment firms); four were at banks; - five were in a financial services group (spanning multiple businesses), specifically three of which were in a digital FinTech division; - one was at a legal firm; three were at alternative lending firms (two of which were at P2P lenders); - the last two were at regulatory bodies.

Regards the positions of significance held by particular interviewees:

- interviewee four was the central treasurer of a bank; - interviewee five was the Global Head of FinTech and Innovation for a financial

services group;

- interviewee six was the Chief Digital Officer for a financial services group; - interviewee seven was the CEO of Life Insurance for a financial services group; - interviewee eight worked for a financial intermediary but had previously founded and ran (and was still involved with) a FinTech consultancy in South Africa; - combined interviewees nine (two people in one joint interview) were the co- founders as well as CEO and COO respectively of a P2P lender in South Africa; - interviewee 10 was the Chief Investment Officer of an investment firm and was previously the Head of the Corporate Investment Bank division of a bank; - interviewee 11 was the Global Head of Digital Operations; - interviewee 12 was the Founder and MD of a P2P lender in South Africa; - interviewee 14 was the founder and director of an alternative lending business in South Africa; - interviewee 15 was the founder and Chief Executive at an investment firm; - interviewee 17 was the CEO and Executive Director of a financial services group.

Regards the education levels of the interviewees:

- five interviewees had studied up to the Honours level (several with various other qualifications); - eight had studied a Masters’ degree; - three interviewees had attained a Doctorate (PhD); - two had attained Professorships.

Overall, the sample represented a sound spread of educated, involved, skilled, experienced professionals across the trades of banking, lending, risk management and regulation.

5.2 Saturation analysis

The usage of the 136 codes (both deductive and inductive) was spread across the 18 interviews as illustrated in Table 3. The top part of Table 3 shows the total usage of a code across all the data. For example, the average number of times that a code was used in total during the coding process was 11. The bottom part of Table 3 refers not to the total usage of a code but rather to the number of interviews in which it occurred. For example, the average number of interviews in which a code occurred (at least once or more in that interview) was six.

Table 3: Summary of code frequency

Total code usage across data Minimum 1

Maximum 49 Average 11 Median 8

# interviews in which code occurred Minimum 1 Maximum 17 Average 6 Median 5

The author applied dual deductive and inductive coding processes. As such, she considered saturation from several angles.

Given that 58 deductive codes were created and used in the coding process. The majority of the concepts drawn from literature relating to the research were captured in the coding process (Strauss & Corbin, 1990) either through deductive or inductive codes. As such, the author was comfortable that theoretical saturation had been reached (Strauss & Corbin, 1990).

Morse (2000) indicated that saturation occurs when the researcher no longer hears new data in the interviews which correlates with a decline in the number of new inductive codes created per interview. Because inductive codes played an important role in the data analysis process, the author made use of a saturation analysis to indicate that data saturation had been reached. It is evident from Figure 4 that saturation was reached at around interview 14.

Figure 4: Saturation analysis: inductive code creation

Data saturation analysis 20 18 15 15 10 10 6 7 7 5 3 2 3 2 1 - 1 1 1 - 1 - - Number of codes createdcodesNumberof 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 Consecutive interview numbers

# new codes created

5.3 Addressing the research questions

A reminder of the penultimate research problem at hand: should online P2P lending platforms be regulated like banks in South Africa, with specific respect to liquidity and capital? To address the research problem, two research questions were considered. The presentation of the results of the data analysis are structured around the two research questions and then, from that foundation, the research problem.

The author applied a dual deductive-inductive coding process whereby she moved from theory to themes (represented as super code families) to categories (represented as code families) to codes for the deductive approach. The author applied the opposite for the inductive approach, moving from codes to categories (code families) to themes (super code families) (Saldana, 2015). As such, a thematic data analysis methodology was applied. In parallel, the author made use of summative content analysis as she interpreted the context of and drew keywords from the content (audio files converted into transcripts), then examining that data utilising some counting and comparisons (Shannon, 2005).

5.3.1 Research question one: Are online P2P lending platforms behaving like banks?

There were three key questions in the interview guide that prompted discussion and sought views with regard to the first research question, being questions 14, 15 and 19.

5.3.1.1 Interview question 14

“Question 14: In your view, are online P2P lending platforms behaving like banks? [category question: yes or no] Please elaborate. [open question]”

The codes relating hereto were grouped under the code family “P2P Behaviour”. Of the deductive codes, 13 of the 18 interviewees believed that online P2P lending platforms are not like banks whilst nine interviewees suggested that they are indeed like banks. Four interviewees commented specifically that category one type P2P lenders are not similar to banks whilst another four interviewees commented that some P2P lender categories are like banks. This dispersion alerted the author to the concept that the operating structure of the online P2P lending platform influences its association with banking behaviour.

Two inductive codes of interest arose in relation to whether online P2P lending platforms’ behaviour is similar to that of a bank. Firstly, six interviewees noted that P2P lending activity is akin to securitisation . These comments were made largely in the context of category three which talks to the pooling of funds. The pooling may occur on or off the balance sheet of the financial intermediary. The comparison to securitisation by employees was in the context of pooled funds off balance sheet. The CEO of a financial services group (including banking, asset management and client advisory) commented that:

P17: Dr_CEO_Financial Services Group “Category 3 is like securitization or a bank. If it’s a third-party trust, is like a securitization. If it’s a principal, it’s like a bank.”

P13: Prof_Director FinTech Regs_Law Firm “The moment you take deposits and promise to repay some or other part of the money you receive, that is the business of the bank.”

Secondly, six interviewees commented that P2P lenders’ behaviour is akin to that of a fund. These comments were made largely in the context of category three, wherein P2P loans are pooled into portfolios. This included a comment from an interviewee employed at a regulatory body, saying that an application of Collective Investment Schemes Act

(the regulatory framework for funds in South Africa) to online P2P lending platforms has indeed been considered. The principal treasurer at a bank noted that:

P 4: Head Central Treasury_Bank “…it is closed terms a unit trust type of structure.”

Whilst another interviewee whose regulatory knowledge is extensive noted that:

P 3: Dr_Head Insurance_Funds_Credit_Bank “…how was a P2P lending platform any different to a money market fund or a credit fund, which would invest in lending assets and would sell that risk down to investors through units…”

A strong theme that emerged was the linkage between the balance sheet involvement of the P2P lender and whether the behaviour of a P2P lender was similar to a bank. The author ran code co-occurrence analyses on the four deductive codes (identifiable by the lack of the “*” prefix to their names) in Table 4 (all of which are codes referring directly to whether or not P2P behaviour is similar to that of a bank) pairing each one with the code “B/S Involvement” (meaning that the balance sheet of the P2P lender is involved in the transaction between ultimate lender and ultimate borrower). The author found that ten out of 18 interviewees made statements where both codes occurred. Certain of these co-occurring code pairs are shown here following:

P 1: Product Developer_Bank “…the difference, having understood the operating models of these peer-to-peer lenders, would be that it doesn’t sit on their balance sheet. Whereas in the banking system it does sit on the balance sheet.”

P13: Prof_Director FinTech Regs_Law Firm “…the platform borrows money from the Lenders (the Lebusa’s, the Tammy's) and on-lends it to Borrower and Anonymous, because that is squarely the business of a bank. You cannot borrow money to on-lend.”

P17: Dr_CEO_Financial Services Group “…category 2 definitely it’s a bank.”

Table 4: Codes relating to bank-like behaviour

Code Total code # of interviews in usage which code occurred *P2P is like securitisation 11 6 *P2P like a fund 8 6

*Pooling & P2P loan selection is like bank 5 4 P2P Cat I is not like a bank 7 4 P2P like a bank 26 9 P2P not like a bank 26 13 Some P2P Cat's are like a bank 6 4

5.3.1.2 Interview question 15

“Question 15: Which of the following banking theories, if any, can be applied to online P2P platforms’ behaviour? [category question: financial intermediation theory, fractional reserve theory, credit creation theory, none of the above] Please elaborate. [open question]”

Three deductive codes describing the three key banking theories (as outlined in the literature review) had application to question 15. These are shown in Table 5. A strong finding was that 16 out of 18 interviewees believed that financial intermediation theory (a banking theory) can be applied to online P2P lending platforms. This thinking stemmed largely from the risk management sample subgroup. Seven interviewees believed that credit creation theory may have application whilst only one interviewee believed that fractional reserve theory had application to online P2P lending platforms.

“Credit creation” cooccurred with “Leverage B/S”, which indicated that the theory of credit creation was associated with the concept of leverage. The quote indicates as such:

P15: Prof_Founder Director Portfolio Manager_Investment Firm “It might have some application depending on how P2P is behaving and even if it wasn’t aggregated, it wasn’t a deposit taker, it could still create credit by going and showing the aggregated assets and gearing up against that aggregated assets, so that would create [credit].”

An interesting inductive code that arose from the conversations was “Applies to non- banks”. This code was created when the Chief Digital Officer at a financial services group commented that the role of banks is changing, leading to the thinking that theories which are branded banking theories in academia may have application to non-bank financial entities. In this context, 10 of the 18 interviewees commented that banking theories may have application beyond banks. Of particular interest was a comment by an interviewee employed at a regulatory body, who associated the risk posed by P2P lending with shadow banking (an inductive code).

P16: Senior Risk Analyst_Regulator “…shadow banking banner they are looking [at], there is a term non-bank financial entity, or something like that, so it’s view and my understanding that that those different theories are being discussed as to non-bank financial entities.”

Interviewee 11 who worked in the digital team for a financial services group at the time of the research associated P2P lending with the concept of disruption, linking this to why theories that are traditionally banking theories may be applied to non-bank players.

P11: Global Head Digital Operations_Financial Group “…with all of the disruption that is happening where you have got a large number of non-banking players coming into this market I think everything you are saying is valid. I think we can’t confine ourselves any longer to traditional banking models…”

Five out of 18 interviewees made reference to disruption whilst seven made reference to disintermediation. This was likened by interviewees with the behaviour and intentions of present day online P2P lending platforms’ behaviour.

However, this notion was disputed by a Professor in Economics who was the founder and is the present director of an investment firm. He stated that financial intermediary theory (as a banking theory) has long applied to his business model (investment management) which is not one that is associated with disruption.

Table 5: Codes relating to banking theory

Code Code family Total code # interviews in which usage code occurred *Applies to non-banks Banking theory 12 10 *Disintermediation P2P behaviour 9 7 *Disruption P2P behaviour 9 5 Credit creation theory Banking theory 9 7 Financial intermediation Banking theory 22 16 theory Fractional reserve theory Banking theory 1 1

5.3.1.3 Interview question 19

“Question 19: Do you think that there is a fundamental difference between the risks posed to the financial system created by (a) banks (who guarantee depositors’ funds) versus (b) online P2P lending platforms (who facilitate the meeting of lenders and borrowers), considering each of the three broad categories for the P2P operating structure? [category question: yes or no] Please elaborate. [open question]”

There are two code families that applied primarily to this question. The first is that of the role a bank plays (“*Banks’ role”, an entirely inductive code family) and the second is “P2P systemic”, which contains both deductive and inductive codes that refer to the risks that a P2P lending platform poses both in absolute and relative terms (compared to a bank). The overlap between the two code families yielded insight into how the interviewees perceived the difference or similarity between the risks posed to the financial system by banks versus online P2P lenders.

When asked whether they perceived the risks posed by banks versus P2P lenders to be different, interviewees first sought to unpack what a bank’s role and risk proposition is. This led to numerous conversations about the socio-economic role that banks play (voluntarily raised by eight interviewees out of 18), relating to transactional enablement (three interviewees), being a critical store of value for savers (nine interviewees) and being an enabling mechanism for the implementation of central bank monetary policy (three interviewees). The inductive codes relating to banks’ role are shown in Table 6. These codes are entirely inductive: the interviewee did not prompt discussion on any of these topics, they arose organically and independently across a large chunk of the sample base. This was indicative of the importance of the banks’ role.

Worth noting was that the socio-economic role of banks appeared to be a point on which multiple groups of interviewees agreed, with a fairly even spread of conversation on the

matter across the academic, banking, lending, regulation and risk management sample subgroups; the usage of the code “Socio-economic role” varied between 10 and 13 instances across the five groups.

Table 6: Codes relating to the role of banks

Code family: *Banks’ role Total code usage # interviews in which code occurred *Agency role 2 1 *Confidence 17 8 *Monetary policy enablement 4 3 *Socio-economic role 16 8 *Store of value 14 9 *Transactional enablement 7 3

Against this backdrop, interviewees went on to explore the difference in risks posed to the financial system by banks versus online P2P lending platforms. Certain of the deductive codes and one inductive code from the code family “P2P systemic” have been included in Table 7. The views were varied: eight interviewees commented that online P2P lenders are riskier (and therefore pose higher risk to the financial system) than

banks whilst seven commented that online P2P lenders are less risky than banks (and therefore post less risk to the financial system). Once again, the conversations highlighted that the responses varied depending on the operating structure of the P2P lender. As such, the operating structure categories featured strongly in the interviewees responses, often shifting their views. Eight interviewees commented that a category one P2P lender posed less risk, whilst five interviewees commented that pooling risk (a feature of category three) creates more risk. “*Pooling creates more risk” cooccurred twice with the inductive code “*Taking risk not aware of”, which refers to the concern that lenders invested in a pool are not fully informed of the explicit details of the investment. This is illustrated by the following quote from a member of a regulatory body:

P18: Financial Stability Analyst_Regulator “…investors start investing and if there’s no transparency in what they are investing in then that is a potential risk”.

Table 7: Codes relating P2P lenders and systemic risk

Code Total code usage # interviews in which code occurred *Pooling creates more risk 6 5 *Taking risk not aware of 5 2 Cat I is lower risk 11 8

P2P less risky than bank 8 7

P2P riskier than bank 11 8

Interviewee one surmised her views succinctly as below. Her views around the comfort that bank regulatory protection mechanisms provide were echoed by three other interviewees.

P 1: Product Developer_Bank “…there is more risk around P2P [lending] versus a bank in the context of servicing the same need of borrowing and lending in the industry, [in] that P2P lending in itself, regardless of the platform that it is been executed through, poses higher risks. So, I think that the fact that it is not as regulated or controlled as in the banking industry. The credit scoring models that these P2P lenders use could vary significantly from what the banks are forced to and regulated to abide by. There is risk in that, obviously, if these P2P lenders have defaults that they do not have any form of insurance that the banking sector has. They do not have any recourse [like] the banking sector does, I say "bail out", they wouldn’t have that. They don’t have support from the regulator or from the government in that

regard. And I think they pose higher risks because they are not regulated, their ability to be a little bit more negligent around the criteria for lending and the opportunity for potential borrowers and lenders to be fraudulent on this technology.”

Interviewee 14 commented that the culture of the P2P industry (predominantly outside of South Africa) is one of a risk-taking nature.

P14: Founder Director_Alternative Lending “…banks are highly regulated around the stuff that we spoke about earlier, liquidity and capital rates and all that kind of stuff. P2P platforms are new age, they are hungry, a lot of them are run by younger very aggressive tech ex- bankers who are there to disrupt and make a point…”

5.3.2 Research question two: Do online P2P lending platforms pose systemic risk to the South African financial system, specifically in the absence of liquidity and capital regulation?

Interview questions nine, 10, 12, 13, 16, 17, 18 and 20 all sought to address research question two. Questions nine and 10 explored the interviewees’ interpretation of systemic risk and its presence in South Africa. Questions 12 and 13 asked interviewees whether the thought that the banking regulations on liquidity and capital management did indeed mitigate systemic risk. Questions 16 to 18 queried whether online P2P lending platforms posed or could pose systemic risk in South Africa. Question 20 questioned the issue of whether or not online P2P lending platforms were restricting (or could restrict) liquidity, as the issue of liquidity is intricately related to systemic risk (refer to section 6.2.2 for analysis on the liquidity element).

5.3.2.1 Interview question nine

“Question nine: How do you define systemic risk in a financial system? [open question] What indicators exist that alert you to its presence? [open question]”

Four code families relating the super family “Systemic risk” were utilised in responses to this question, being “*Systemic risk other” (an inductive code family), “Interconnectedness”, “Leverage” and “Size” (the last three including mixes of deductive and inductive codes).

Two strong themes that emerged when answering question nine were “*Size of industry” and “Interconnected”. Each code featured in 14 out of 18 interviews where interviewees were defining systemic risk. It was noteworthy that the deductive code “Size of player

matters”, which referred to the size of a specific entity in the financial system, featured less, appearing in 11 interviews. Whereas the inductive code “*Size of industry” was certainly more dominant and central to several discussions. “Even small players” is a code that refers to how even those entities in a financial system that are relatively insignificant in size can affect the other members of a financial system due to their interconnectedness with the system. Seven out of 18 interviewees made reference thereto.

Relating to “Interconnectedness” was the concept of “Contagion / domino effect”, which spoke to the spread of distress between entities in a financial system due to their interconnectedness. “Contagion / domino effect” featured in 11 interviews.

“Leverage B/S” was a deductive code that also featured strongly in 10 interviews of 18. Relating to this is the inductive code “*Leverage amplifies risk”, featuring in two interviews.

Two inductive codes that arose in relation to defining systemic risk and were related to one another are “*Non-diversifiable” and “*Loss through no action of own”. Each one featured across four out of 18 interviews.

Two other inductive codes that are similar in meaning arose, being “*Bubble in mkt” and “*Mispricing of risk”, featuring in five and one interview(s) out of 18 respectively.

Table 8: Codes relating to systemic risk

Code Code family Total code # interviews usage in which code occurred *Bubble in mkt *Systemic risk other 8 5 *Leverage amplifies risk Leverage 5 2 *Loss through no action of Interconnectedness 7 4 own *Mispricing of risk *Systemic risk other 4 1 *Non-diversifiable Interconnectedness 4 4 *Size of industry Size 42 14 Banking system Interconnectedness 14 8 Contagion / domino effect Interconnectedness 18 11 Even small players Size 11 7 Interconnected Interconnectedness 44 14 Leverage B/S Leverage 25 10 Size of player matters Size 34 11

5.3.2.2 Interview question 10

“Question 10: In your view, are the systemic financial risks in South Africa largely contained within its own financial system given the exchange control regulation? [category question: yes or no] Please elaborate. [open question]”

The code family “Exchange Control” applied directly to question 10. It contained a mix of deductive and inductive codes.

Eight out of 18 interviewees stated that the presence of exchange control regulations in South Africa does mitigate systemic risk whilst five interviewees outright stated that it made no difference. Six interviewees agreed that it played a role but was not primarily responsible for any systemic risk mitigation in South Africa. Despite this disparity, 11 out of 18 interviewees confirmed that South Africa experienced less severe effects from the Great Financial Crisis (“GFC”) of 2008. This was a view strongly held by the academic subgroup, 80% of whom raised the notion. The codes "Mitigate systemic risk in SA" and "*GFC had less impact on SA" cooccurred four times, with the following notable quote:

P 7: CEO Life Insurance_Financial Group “…when sub Prime happened, I know that almost every single one of the banks had applications rejected to move some of their assets into sub-Prime assets with additional return on the risk. So that prevented almost like a contagion effect to

the SOUTH AFRICAN market.”

Certain interviewees went further and broke it down into inward risk flows (via the purchase of foreign investments by South Africans) and outward risk flows (via the purchase of South African assets by foreigners). Exchange control regulations cap the former but not the latter (Republic of South Africa, 2016.). This led to the creation of the inductive codes “*Restrict risk imports” but “*Export risk freely”, which was voluntarily raised by five and one interviewees respectively.

The inductive code “*Sound system protection in SA” arose in six interviews and put forward the view that exchange control was given undue credit for the muted reaction to the GFC in the South African markets. The thinking from interviewees was that it was not exchange control alone (or at all) that protected the South African financial system but rather the superior and advanced regulatory controls that were already in place in South Africa at the time of the GFC. This view was alleged primarily by the academic sample group, 60% of whom raised it.

As an aside, this connected with the view of a director at a legal firm who is an expert on the regulatory landscape affecting not only P2P lenders but alternative lenders as a

whole. She specified the regulatory coverage of P2P lenders in South Africa by the NCA as unique when she said that:

“I think your credit act [NCA] with all its faults and how poorly administered it is, gives / protects against a kind of a CHINA situation. In fact, so much so Tammy, that before I started working doing work for the Asian Development Bank there was a guy who was the [National Credit] Regulator here, called Gabriel Davel, I don’t know if you ever remember him. Now he was flown all over the world to speak about this wonderful piece of legislation that we [South Africa] had.”

The codes "Plays a role, not only / primary" (referring to whether exchange control mitigates systemic risk in South Africa) and "*Sound system protection in SA" were related in four quotes, captured by the following:

P13: Prof_Director FinTech Regs_Law Firm “I am not sure that it can be seen as the saviour of or the great reason that we came off as well as we did.”

A second insightful inductive code that arose was “Excon amplifies domestic risks”. Four out of 18 interviewees were of the view that the presence of exchange controls made the domestic (South African) financial system more vulnerable to its own implosions due to the concentration of players and enhanced interconnectedness in the system. This was captured by the following quote:

P 2: Head Credit Investments_Bank “…the lack of depth in the financial markets that we have here in South Africa being four major commercial banks and obviously one or two smaller investment banks. It does open us up to a potential domestic financial crisis if we have [this] amount of depth [and] alternative liquidity is not, cannot be sourced.”

Table 9: Codes relating to exchange control in South Africa

C-ode Code family Total # interviews code in which usage code occurred *Excon amplifies domestic risks Exchange Control 7 4 *Export risk freely Exchange Control 1 1 *GFC had less impact on SA Exchange Control 12 11 *Sound system protection in SA *Reg views 16 6 *Restrict risk import Exchange Control 6 5 Makes no difference Exchange Control 11 5 Mitigate systemic risk in SA Exchange Control 13 8

Plays a role, not only / primary Exchange Control 9 6

5.3.2.3 Interview question 12

“Question 12: In your view, does banking regulation on liquidity management mitigate systemic financial risk? [category question: yes or no] Please elaborate. [open question]”

Part of the code family “Liquidity requirements” related to question 12. A strong response of 14 out of 18 interviewees stated that liquidity requirements (as dictated by bank regulation) do indeed mitigate systemic risk in South Africa, including interviewee 16, who worked for a regulatory body at the time of the research:

P16: Senior Risk Analyst_Regulator “…depositors need to be able to deposit and exchange their money and we need to ensure that whatever the liquidity ratios are [that] banks are able to fulfil their obligations…”

However, this was countered by three interviewees who said that liquidity requirements do not mitigate systemic risk and another four interviewees proactively noted that the intention of liquidity (and/or capital) regulations (being to mitigate systemic financial risk) had not been effective. The two codes "Liq req don't mitigate systemic risk" and "*Intention but not reality liq / cap regs mitigate systemic risk" were connected five times, indicated by the following quote:

P 9: Co-founders CEO COO_P2P Lender “…delays a systematic failure but fundamentally you have to fix your risk by ensuring that there is no risk, right. Liquidity doesn’t fix the risk.”

With respect to the rationale behind the code "*Intention but not reality liq / cap regs mitigate systemic risk", the author noted that it cooccurred with "*Regulation lags" three times, suggesting that it is the delayed implementation of regulation that allows the market to adapt away from the regulatory net, thus regulations do not necessarily achieve their honourable intention. This insight is represented by the quote:

P15: Prof_Founder Director Portfolio Manager_Investment Firm “…each time the regulator puts the hurdle higher, the regulated finds a way of sort of rearranging the furniture, shifting the rules, or twisting the requirement, building a new product or establishing a way to get things on or off-balance sheet.”

The issue of confidence arose in the conversations about liquidity. Interviewees proposed that it is ultimately the loss of confidence by depositors and investors in a bank that causes depositors and investors to panic and demand their funds at the same time. This causes a “run on the bank” which may lead to a liquidity shortage over a short period of time which could ultimately result in the bank’s failure. The two codes capturing this are "*Liquidity takes down banks" and "*Loss of confidence / panic / run on the bank", which cooccurred twice and were both supported mainly by the academic sample subgroup (60% and 80% respectively made reference thereto). The following quote by a central treasurer at a South African bank summed up the matter:

P 4: Head Central Treasury_Bank “We know what the obvious risk in banking is: that you put too many long-dated assets on book, fund them very short, do it in a very leveraged fashion, don’t have enough capital backing up either, so when your assets’ performance goes south you just find yourself in a liquidity risk situation where you can’t fund your book. [There are] ongoing commitments in the short term and there is a run on the bank. [There is] loss in confidence and everybody is pulling their cash [out] which exacerbates the situation and you don’t have time to bail out.”

Interviewees went on to propose that the presence of liquidity requirements overseen by the bank regulator inspire confidence in depositors and investors alike which prevents

the form of panic that can drain banks’ short-term liquidity reserves. This was an indicative code raised by four interviewees. Another interviewee commented that the ratios reported by banks as required by liquidity regulations act as an early warning system if a bank is in trouble. Indeed, confidence was quoted by interviewees as being the glue behind the banking system. The two codes “Banking system” and “*Confidence” (each raised in eight interviews) were related five times. A quote by the CEO of a financial services firm summed it up:

P17: Dr_CEO_Financial Services Group “…it’s a system built on confidence at the end of the day and then the confidence goes and then you end up in crisis. That is what you have got to do, is that you make sure. By letting Lehman’s go they lost the confidence of the public. If they bailed Lehman’s out, you know, [it said] that government will help.”

Table 10: Codes relating to liquidity requirements

Code Code family Total # interviews code in which code usage occurred *Confidence *Banks' role 17 8

*Intention but not reality liq / cap Capital requirements 6 4 regs mitigate systemic risk & Liquidity requirements *Liq regs early warning Liquidity requirements 1 1 *Liq req are a confidence tool Liquidity requirements 8 4 *Liquidity takes down banks Liquidity 8 4 *Loss of confidence / panic / run Liquidity 23 9 on the bank Liq req don't mitigate systemic Liquidity requirements 7 3 risk Liq req mitigate systemic risk Liquidity requirements 23 14

5.3.2.4 Interview question 13

“Question 13: In your view, does banking regulation on capital adequacy requirements mitigate systemic financial risk? [category question: yes or no] Please elaborate. [open question]”

Part of the code family “Capital requirements” applied here. The notion that capital requirements mitigate systemic risk was supported by 17 out of 18 interviewees, an even stronger response than that to liquidity requirements supporting systemic risk (14 out of 18). 100% of both the academic and the regulation subgroups were in support of the notion. Three interviewees countered saying that capital requirements do not mitigate systemic risk. The same four interviewees as mentioned under question 12 noted that neither liquidity nor capital requirements mitigated systemic risk as they were intended to do.

The concept of default risk arose in seven interviews whilst the capital as a loss buffer for default risk arose in eight interviews. It cooccurred with "Cap req mitigate systemic risk" five times, producing a quote wherein interviewee two claimed that liquidity is the threat (linking with the code “*Liquidity takes down banks”) and that capital requirements cannot necessarily protect against that. He said that:

P 2: Head Credit Investments_Bank “…the biggest systemic risk that I always look at is liquidity. The banks have failed before with high capital ratios, good NPL's [non-performing loans]. What makes them fail is liquidity. What makes the bank system fail is liquidity.”

The notion that the enforcement of capital requirements by the bank regulator also acts as a confidence tool for depositors and investors in the banking system was voluntarily raised by three interviewees (“*Cap req are confidence tool”). It cooccurred with “*Liq req are a confidence tool” to product the following quote:

P14: Founder Director_Alternative Lending “…it does provide a layer of comfort to all the other people in the ecosystem…”

Table 11: Codes relating to capital requirements

Code Code family Total # interviews code in which code usage occurred *Cap req are confidence tool Capital requirements 6 3 *Intention but not reality liq / Capital requirements & 6 4 cap regs mitigate systemic risk Liquidity requirements Cap req don't mitigate Capital requirements 3 3 systemic risk Cap req mitigate systemic risk Capital requirements 21 17 Default risk Capital requirements 10 7 Loss buffer Capital requirements 14 8

5.3.2.5 Interview questions 16 and 17

“Question 16: In your view, do P2P lending platforms presently pose systemic financial risk in the financial system? [category question: yes or no] Does the operating structure of the P2P platform (consider the three broad categories) affect this? [category question: yes or no] Please elaborate. [open question]”

“Question 17: In your view, do P2P lending platforms create systemic financial risk in the financial system such that they could they pose systemic financial risk in the future?

[category question: yes or no] Does the operating structure of the P2P platform (consider the three broad categories) affect this? [category question: yes or no] Please elaborate. [open question]”

Question 16 interrogated the present state whilst question 17 interrogated the potential future state of P2P lenders posing systemic risk. As online P2P lending is presently a relatively small new industry in South Africa (RainFin, 2017), consideration of the future state is relevant as P2P lending has grown significantly (and quickly) in other jurisdictions (Transparency Market International, 2016).

A strong response was that online P2P lenders do not presently pose systemic risk to the South African financial system, with 17 out of 18 interviewees confirming that this was the case with one interviewee claiming that P2P lenders do presently pose systemic risk. 14 out of 18 interviewees made reference to the absolute and relative size of P2P lending market compared with the overall lending market in their interviews. A strong connection emerged between these two codes, where "No systemic risk from P2P now"

cooccurred with "*Size of industry" 16 times. The repetitive view was captured by interviewee eight, the founder of a FinTech consultancy:

P 8: Founder_FinTech Consultancy “…the proportion of P2P lending is relative to total asset in total loans in the market it’s still very, very, very small.”

However, 11 interviewees thought that P2P lenders could pose systemic risk in the future contingent on the presence of certain elements. Four interviewees felt that there would not be any systemic risk from P2P lenders in the future; their view was not now and not ever. The risk management subgroup did not support this notion, with only 8% of its members making reference to the code “No systemic risk from P2P in future”. The codes “P2P could pose systemic risk in future” and “*Size of industry” cooccurred 13 times, again indicating the significance of the industry size as a factor. The interviewee that captured it best said:

P14: Founder Director_Alternative Lending “Seven years from now I think it may be slightly different but right now there is no risk at all. However, after seeing some of the activity in Europe and what has gone on, potentially if they continue growing in the same way, it could be.”

Regards the contingent elements that could spur P2P lenders to create systemic risk: eight interviewees felt that the category one operating structure (a true facilitation role) posed less risk. One interview explicitly stated that should the balance sheet of the P2P lender be involved in the lending transaction (being a category two or three operating structure), then the P2P lender could pose systemic risk. Four interviewees out of 18 interviewees commented that the core underlying assets facilitated by P2P lenders (often being personal unsecured loans) are of a high-risk nature to start with. “*Leverage B/S” and “P2P could pose systemic risk in future” cooccurred twice, indicating the association of leverage with P2P lending’s potential to pose systemic risk. Maturity transformation (which is associated with restricting liquidity, refer to section 5.3.2.7) cooccurred with “P2P could pose systemic risk in future”. Five out of 18 interviewees commented that the pooling of investments and risk (akin to operating structure category three) increased the amount of risk present whilst eight interviewees countered that notion advising that diversification (through pooling) in fact reduces risk, a view fairly evenly shared across the sample subgroups.

Interviewees proposed that an investment into a diversified pool of P2P loans is less risky for the investor than a bilateral loan with one borrower. Hence diversification could

reduce probability of a binary outcome for the investor. The term binary outcome refers to the two possible investment outcomes that a lender may have: (a) the borrower repays the loan and the investor earns the pre-agreed return or (b) the borrower does not repay the loan and the investor likely earns zero (as the recovery rate on personal loans was deemed low). "*Binary outcome" cooccurred with "*Diversification reduces risk" and produced the following quote:

P 7: CEO Life Insurance_Financial Group “Which is why one-to-one, sort of unknown to unknown, lending types scenarios poses as, for me, what should be regulated against. Because you know, so I have no issue with P2P and lending platforms if it is sort of a many-to-one type of situation, because then you at least get a diversified pool.”

Once again, the “*Size of industry” was a strong response from interviewees. It connected with the concept of P2P lenders posing systemic risk where interviewees stated that should the industry grow then it could contribute to the systemic risk in the system. As the CEO of a financial services group put it:

P17: Dr_CEO_Financial Services Group “…if you get a big percentage of lending off balance sheet outside of securitized vehicles and a lot of savings that go, (because this is savings, you call it P2P but

it is really savings) [are] going into the stuff, even if it is corporate. Corporates say

“I want more return on my free cash” and they start putting money into the P2P stuff because they think that they are getting a fancy return. I think that at a point in time as it gets large it becomes systemic.”

The data regarding P2P lenders posing systemic risk in the future was connected with the size of the industry. The data regarding the growth rate of the industry was connected with the presence of institutional investors into the assets offered by P2P lending platforms. “Insto’s” is a shortened term used for institutions in the coding process. Institutions could imply a multitude of large predominantly financial players. What the term specifically excludes is individuals, also referred to as retail investors in finance terminology. The codes "*Grow faster with insto's" and "P2P could pose systemic risk in future" were connected by the following quote:

P14: Founder Director_Alternative Lending “In EUROPE, what happened was when they started getting going they got this platform up and running, there were borrowers who came running in but there

weren’t enough lenders and what they did, many of the big players, is they started going to institutions…”

The above quote by interviewee 17 raised a critical question: do lenders (investors) view P2P loans as an alternative to bank deposits? Detail on the issue is provided under interview question 11 (section 5.3.3.1).

Seven interviewees voluntarily raised the issue of shadow banking. The concept was mentioned evenly across the six sample groups. This connects with the concept of P2P lending potentially posing systemic risk as it is the concern of interviewees working in regulation and the market alike that risks which are ordinarily governed by a certain regulatory regime may occur in altered format outside of that regime. The central treasurer of a South African bank put it succinctly as:

P 4: Head Central Treasury_Bank “…you worry more about what is happening outside the regulated banking space, the shadow banking space, where shadow unregulated players are essentially playing the same game without the same degree of regulation. If they had to fail given the size of some of the players they could bring the system down with them.”

Another interesting inductive code that arose during these conversations was that of online P2P lenders being tested in a time of financial crisis, where interviewees felt that the online P2P lending platforms had not yet weathered a storm. This was captured in the code “*Test in stress event” which arose across five interviews and was predominantly supported by the lending sample subgroup where 56% of its members agreed on the matter. Further, interviewees commented that the P2P business model posed risks as the P2P did not have a vested interest (being its own capital invested) in originating and managing good quality risk. This was captured in the code "*P2P only lose reputation in crisis", which occurred in four interviews. The two issues were linked by interviewee 14, the founder and director of an alternative lending firm. He said that:

P14: Founder Director_Alternative Lending

“How does that platform survive, how do your portfolios survive? And they are right because the P2P lenders haven’t been around enough and they don’t have [loan] books that are seasoned enough to make that call.”

Table 12: Codes relating to P2P lending and systemic risk

Code Code family Total # interviews code in which usage code occurred *Binary outcome P2P risks 6 2 *Diversification reduces risk P2P risks 15 8 *Grow faster with insto's P2P risks 2 2 *High growth rate P2P risks 7 1 *High risk underlying P2P risks 8 4 *If B/S involved then systemic risk P2P systemic 3 1 *Pooling creates more risk P2P systemic 6 5 *Shadow banking P2P behaviour 12 7 *Size of industry Size 42 14 *Test in stress event P2P risks 8 5 Cat I is lower risk P2P systemic 11 8 No systemic risk from P2P in future P2P systemic 10 4 No systemic risk from P2P now P2P systemic 49 17 P2P could pose systemic risk in future P2P systemic 39 11 P2P poses systemic risk now P2P systemic 1 1

5.3.2.6 Interview question 18

“Question 18: Do you think that the systemic risk exists as a result of P2P lending activity but not at the level of the online P2P lender? [category question: yes or no] Please elaborate. [open question] Might that imply that another party in the investment equation should be subject to liquidity and capital requirements? [open question]”

Interviewees commented that institutional investors are prominent in the P2P lending arena. A distinction between the opposite asset appetites of the institutions: (a) institutions that originate risk (lend money) and seek methods via which to distribute excess of that risk and (b) institutions that seek risk as they are not originating (sufficient) assets of their own. The data indicated that institutions under (a) may utilise P2P platforms as distribution mechanisms to sell assets (get rid of excess risk). In such a situation, the institution would play the role of the borrower via the platform. This led to the creation of the inductive code “*Diffs distribution channel for insto's”, which was voluntarily raised by six interviewees. Institutions under (b) would play the role of the lender via the P2P platform, effectively taking on risk through lending money. This was illustrated by the following quote from the co-founders of a South African P2P lender:

P 9: Co-founders CEO COO_P2P Lender “…it happens every day. [Anonymous] have people who want buy loans from [P2P platform] on [P2P platform] into a warehouse and they want to raise money

to buy those loans. So, if they raise money from the public they are in the Banks Act, which is right, they should be. But they raise money by going and getting just two or three non-public parties who understand and there is no guarantee, then they not in the Banks Act.”

The notion that P2P lenders should not bear liquidity and capital requirements but that someone in the investment equation should led to the creation of the inductive code “*Investors should bear cap / liq req” which was mentioned by three interviewees. For context, the comments were made with a category one operating structure in mind. Interviewee seven illustrated this view:

P 7: CEO Life Insurance_Financial Group “You know what you almost want to do is that the capital requirement shouldn’t be on the platform, it should be on the investor. Then the investor should make sure that they keep enough cash behind, for that they, again, they are not gambling the house away.”

A last notable inductive code that arose from this question was that of creating distinct regulations per investor type, as various investor types have various risk appetites and investment intentions. Typical investor types in finance terminology may include: retail individuals (including high net worth individuals) and wholesale (institutions and corporates). The code “*Regs for distinct investor types” arose in two interviews, represented by the below quote. It echoes with the thinking that lenders (as investors) are not always equipped to make adequate risk-reward decisions.

P13: Prof_Director FinTech Regs_Law Firm “…our legislation, unlike that of AUSTRALIA, doesn’t draw a distinction between the sophisticated, unsophisticated retail, wholesale except by exemption.”

Table 13: Codes relating investors

Code Code family Total # interviews code in which usage code occurred *Diffs distribution channel for insto's P2P risks 14 6 *Regs for distinct investor types *Reg views 3 2 *Investors should bear cap / liq req Capital 3 3 requirements & Liquidity requirements

5.3.2.7 Interview question 20

“Question 20: Do you think that online P2P lending platforms are restricting liquidity in the financial system? [category question: yes or no] Does the operating structure of the P2P platform (consider the three broad categories) affect this? [category question: yes or no] Please elaborate. [open question]”

Nine out of 18 interviewees stated that P2P lenders are restricting liquidity and one interviewee specifically carved out that P2P lenders are restricting liquidity for savers. The view on restricting liquidity was skewed toward the regulation sample subgroup, where 63% of its members concurred on the matter. The codes "Not restricting liquidity" (which arose in two interviews) and "*Size of industry" cooccurred three times, indicative of the factors that led to interviewees beliefs that P2P lending is not restricting liquidity. As the founder of a FinTech consultancy put it:

P 8: Founder_FinTech Consultancy “P2P market is not big enough for that, in my opinion so, no, not at all.”

However, a surprise inductive code was “*Create liquidity”, which nine interviewees ardently advocated was the case. Nine interviewees specifically stated that P2P lending creates liquidity for borrowers. This thinking was driven by the FinTech sample subgroup, where 75% and 88% (respectively) of the two subgroups raised the point. As interviewee one put it:

P 1: Product Developer_Bank “…from a concept of credit lending I think it is not restricting market liquidity. I think it is facilitating market liquidity.”

There were several factors related to the restriction or creation of liquidity by P2P lending. These included that listed notes offer relatively more liquidity (raised by one interviewee), akin to a category two operating structure. One interviewee mentioned that pooled funds offer more liquidity, similar to a category three operating structure. Three interviewees noted that the presence of a secondary market aids liquidity. Interviewee two summarised a handful of these factors when he said:

P 2: Head Credit Investments_Bank “…there could be a measure of liquidity restriction because of the lock in periods and the investments rely on the underlying exposures in the P2P lending vehicle. But I think [it is] depending on the structure. The risk will be a little bit less, and that [restriction of liquidity] would be most I imagine in one-to-one lending, and least in where there is a portfolio of those tradeable securities.”

An interviewee that was a regulator at the time of the research was also in favour of a secondary market:

P16: Senior Risk Analyst_Regulator “…key questions is always whether there is a secondary market for specific P2P lenders product. And so, I think that it might be restricting liquidity if there is no big secondary market, so I suppose yes.”

The codes “Restrict liquidity” and “Maturity transformation” cooccurred four times, yielding the below quote by interviewee 10, previously the head of an investment bank. He tied together the concepts of a liquidity gap (due to maturity transformation), restricted liquidity and the involvement of institutions.

P10: Dr_p.Head Investment Bank “…if that mismatch that you have just mentioned, if that broadens that is where the liquidity crunch is going to come in, if you have institutions behind…”

The cooccurrence of the codes "*Liquidity takes down banks" and "Maturity transformation" yielded the following insightful quote by the CEO of a financial services group:

P17: Dr_CEO_Financial Services Group

“…that means that there have to be acceptable backup policies provided by the

Central Bank where you can take pools of assets and repo them to the Central bank who obviously haircut the pool because in a time of crisis banks you may not have access to liquidity.”

Table 14: Codes relating to P2P lending and restricting liquidity

Code Code Total code # interviews in family usage which code occurred *Create liquidity Liquidity 12 9 *Create liquidity for borrowers Liquidity 14 9 *Funds flow through banking system Liquidity 1 1 *Liquidity takes down banks Liquidity 8 4 *Listed notes offer more liquidity Liquidity 3 1 *Pool offers more liquidity Liquidity 3 1 *Restrict liquidity for savers Liquidity 1 1 *Secondary mkt creates liq Liquidity 4 3 Maturity transformation Liquidity 18 8 Not restricting liquidity Liquidity 3 2 Restrict liquidity Liquidity 18 9

5.3.3 Research problem: should online P2P lending platforms be regulated like banks in South Africa, with specific respect to liquidity and capital?

The remaining questions from the interview guide that have not been addressed above all relate to the research problem directly. The relevant interview questions were 11, 21 and 22.

5.3.3.1 Interview question 11

“Question 11: In your view, which functions should the bank regulator ensure? [category question: depositor protection, investor protection, systemic financial risk containment, none of the above, other] Please elaborate. [open question]”

Previously in Chapter 5, the data addressed the concept of whether or not liquidity and capital requirements are influencing systemic risk. However, the question remains as to what functions fall within the ambit of the bank regulator. This is relevant in order to first understand whether or not a non-bank entity like a P2P lender should fall within the ambit of the bank regulator and then interrogate whether liquidity and capital requirements (as bank regulations) should apply to P2P lending.

The code family “Banking regulator role” was the predominant code family that applied here. It included three deductive and three inductive codes. Depositor protection emerged as a strong theme appearing in 15 interviews. It was strongly advocated by the academic sample subgroup where 100% of the group referred to it. The percentage of the group that referenced depositor protection was above 85% for four other sample groups, being banking, FinTech, lending and regulation. As an aside, interviewees made frequent reference to the explicit versus implicit depositor guarantees that central banks provide which varies across jurisdictions (see section 6.2.3.2). Question 11 did not seek to ascertain whether or not bank deposits should be outright guaranteed by the central bank. Question 11 sought to understand the in-principle mandate and responsibility of the bank regulator. Notable quotes on depositor protection included:

P13: Prof_Director FinTech Regs_Law Firm “South Africa is looking at depositor protection because we are a member of the Financial Stability Board, an FSB international measure and it is one of the, I wouldn’t say injunction, but it is one of the things we have been told to look at.”

Interviewee three linked the notions of depositor protection and the socio-economic role of the bank with specific reference to transactional enablement.

P 3: Dr_Head Insurance_Funds_Credit_Bank “It is purely enablement to money. So those people are typically included within the definition of the depositors but as a bank is it is important for a regulator to retain the soundness of the bank to protect individuals who are in that bank for merely transactional purposes. Obviously, depositors [are] the same thing.”

The concept of moral hazard arose in during the discussions about depositor protection. The inductive code “*Moral hazard” occurred five times in interviews and was supported most by the academic sample subgroup (40% of the group made mention of it). The issue raised was that explicit depositor protection from the central bank for bank deposits may lead either depositors or banks to take risks that they otherwise wouldn’t have. The following quote summarised this as:

P13: Prof_Director FinTech Regs_Law Firm “…the big debate around depositor protection is again that could run counter to proper risk management.”

Systemic risk management as the role of the bank regulator was a close second to depositor protection, appearing in 12 interviews. Notably, systemic risk containment was strongly supported by the academic sample group (80%) but weakly supported by the FinTech sample group (25%). Systemic risk and depositor protection cooccurred seven times, introducing the notion of their interrelatedness.

P 5: Global Head FinTech Innovation_Financial Group “…depositor protection and systemic financial risk containment. Those are the primary objectives in terms of regulating bank along with the other objectives things like price stability. Not related to the supervision of banks more or less to the supervisor of the economy as a whole.”

Both the co-founders of a South African P2P lender and the previous head of an investment bank proposed that depositor protection should be the root focus of the bank regulator and that systemic risk mitigation would be a consequence thereof.

P 9: Co-founders CEO COO_P2P Lender “…the number one role of the regulator which would ensure that the depositors money is protected. I think above all else that should be the main one. If you are protecting people’s deposits then everything else would flow from that. So, risk containment, all that stuff, is almost irrelevant if you have protected deposits.”

P10: Dr_p.Head Investment Bank

“Depositors is a consumer protection element but the main focus on insuring depositors is not so much the consumer protection but the systemic risk protection because it’s a run on the bank.”

The notion of investor protection appeared to be a debate. It only occurred in three interviews, indicating a weak sense from the 18 interviewees that it is the role of the bank regulator. The academic sample subgroup did not support the notion at all (0%). The three responses were evenly spread across the other sample subgroups.

Interviewees did not feel that investors should go unprotected altogether, however interviewees thought that the regulation they required was outside of the scope of the bank regulator and sat elsewhere in the regulatory regime. This led to the creation of the inductive code “*Different reg framework for investors”, which occurred in seven interviews. Notable quotes in this regard included:

P 4: Head Central Treasury_Bank “I don’t think a bank regulator should be entering investor protection. These days you tend to split investor protection into a separate pillar into a twin peak type philosophy to make sure that guys don’t get ripped off.”

P 5: Global Head FinTech Innovation_Financial Group “…it is important that you have things like market conduct regulations and don’t

necessary believe that they need to be the same as the banking regulator.”

P 8: Founder_FinTech Consultancy “…you need to ensure that appropriate products are been sold to appropriate people. That then also lends itself to investor protection in the sense that just by mispricing the risk of individuals who you are lending to, the company is publicly listed, there is a knock-on effect and that does [have] systemic issues broadly speaking.”

Markedly, a few quotes connected with the idea of consumers (both borrowers and lenders) with the need to be sophisticated and informed, therefore able to appreciate the risks and the rewards of a P2P loan. This ties in with the notion of financial literacy in South Africa.

P 7: CEO Life Insurance_Financial Group “…you [will] most probably find that you do need more consumer protection so that they know what they are going into on the one hand. And they almost need to make sure that people are investing, and aren’t investing everything that they have, and they know what they are doing, and there is some level of

sophistication and protection that the people have in terms of what the borrowing laws are [so] that people are only getting lent money when necessary.”

This further related to the deductive code “*Lenders ability to measure risk” which occurred in nine interviews and received most of its support from the FinTech sample subgroup (63% of the sample group spoke about it). It cooccurred with “*Different reg framework for investors” once, producing the following quote:

P 8: Founder_FinTech Consultancy “…people need to be financially literate to agree, and fully understand, to be able to participate in financial markets. So, I think that to a degree again it is not so black and white, it’s not about mass financial inclusion. I think that there has to be, when you are talking about money, there has to be a very clear understanding of the risks that are inherent in whatever is happening from all parties, particularly from those that are less financially literate.”

The inductive code “*Deposit substitute” carried significance in this context. This concept was raised inductively fairly early in the interview process by interviewee three. The interviewees proposed that the intention of the P2P lender is important: does he seek a deposit (being a safe store of value for his/her money) or does he/she seek an investment opportunity (implying that he/she is cognisant of the risks and willing to take them for the potential return)? To the extent that a lender through an online P2P lending platform seeks the latter, being an investment, then he/she will fall under the umbrella of “Investor protection” which interviewees confirmed is not the role of the bank regulator. This led to the creation of the inductive code “*Investors at risk for own calls” which occurred across 11 interviews. Certain interviewees went further to say that to the extent that a consumer is an investor and therefore at risk for his/her own calls, the market shall then self- regulate as the risk and rewards relating to certain investments affect investors. This was captured by the inductive code “*Market self regulation” which occurred in three interviews only. “*Investors at risk for own calls” and “*Market self regulation” cooccurred three times. One interviewee summarised it as:

P 3: Dr_Head Insurance_Funds_Credit_Bank “I am less concerned about investor protection. The market must discipline.”

“*P2P growing on yield hunt” occurred in five interviews and shared the view of interviewees that the industry has grown because lenders seek better yields than those paid by traditional investments. This implies that lenders are acting as investors.

However, should a lender either seek a store of value or a place for safekeeping for his money through an online P2P lending platform, then he/she falls under the banner “Depositor protection” which interviewees felt strongly is the role of the bank regulator. “*Deposit substitute” featured in nine interviews and received most of its support from the FinTech sample subgroup throughout the interview process (67% of the group referred to it).

“Deposit substitute” and “*Investors at risk for own calls” cooccurred with three times. A notable quote was:

P 7: CEO Life Insurance_Financial Group “…those are life savings, emergency type money. Compared to someone who is doing a P2P lending proposition, it is almost always going to be surplus amounts and amounts of investments.”

The codes "*Deposit substitute" cooccurred with "Lenders' inability to measure risk" producing the following quote:

P17: Dr_CEO_Financial Services Group “…you are dealing with savings. People don’t know how to look after themselves when it comes to money.”

A last prominent inductive code that arose was “*Capital adequacy / quality B/S”, which refers to a balance sheet that is in good condition: adequate capital to act as loss buffers and well managed risk books with high quality properties. This related to the code “*Bad quality / high risk loan books” which refers to the concern that the types of loans that P2P platforms facilitate or issue are inherently risky in nature. This entirely inductive notion was raised by five interviews and received support predominantly from the academic, FinTech and regulation sample groups. “*Capital adequacy / quality B/S” cooccurred with “Systemic risk containment” three times. The essence was captured by an interviewee as:

P17: Dr_CEO_Financial Services Group “…bank regulators need to understand what creates systemic risk and to me it is the quality of the balance sheet.”

Table 15: Codes relating to the bank regulator’s role

Code Code family Total # interviews code in which code usage occurred *Bad quality / high risk loan books P2P risks 16 6

*Capital adequacy / quality B/S Bank regulator role 10 5 *Deposit substitute P2P behaviour 26 9 *Different reg framework for *Reg views 12 7 investors *Investors at risk for own calls Bank regulator role 23 11 *Market self regulation *Reg views 14 3 *Moral hazard *Reg views 10 5 *P2P growing on yield hunt P2P risks 6 5 *Regs for distinct investor types *Reg views 3 2 Depositor protection Bank regulator role 37 15 Investor protection Bank regulator role 3 3 Lenders' inability to measure risk P2P risks 20 9 Systemic risk containment Bank regulator role 25 12

5.3.3.2 Interview question 21

“Question 21: Do you think that online P2P lending platforms should bear similar regulation to banks with respect to liquidity requirements? [category question: yes or no] Does the operating structure of the P2P platform (consider the three broad categories) affect this? [category question: yes or no] Please elaborate. [open question]”

All of the interview questions preceding questions 21 and 22 in the interview guide tested the foundational principles and created the context for these two critical questions.

Overarchingly, the code family “Liquidity requirements” applied to this question. Only three interviewees outright stated that P2P lenders should bear liquidity requirements generally. A notable quote was:

P 1: Product Developer_Bank “…to the extent that these P2P lending platforms become more blurred [and] to the effect that there are institutional investors, then I think that they would have to be regulated in a very similar fashion [to] financial institutions…”

The broad response against liquidity requirements for P2P lenders (“P2P should not bear liq req”) was equally minimal with two interviewees mentioning it.

However, many interviewees stated that P2P lenders should bear liquidity requirements conditional on specific elements, most of which were connected with the operating structure of the P2P lender. In total, there were 33 instances of use of the collection of codes in Table 16 across the 18 interviewees speaking broadly to when and why P2P lenders should bear liquidity requirements. The interviewees views were:

- Five interviewees commented that if the balance sheet of the P2P lender was involved in the transaction, then the P2P lender should be subject to liquidity

requirements. This speaks largely to the category two and three operating structures. Per section 2.1.4, the category two operating structure for P2P lending assumes that the balance sheet is involved but remains fairly bland with no leverage or structuring. An interviewee commented on this as:

P 7: CEO Life Insurance_Financial Group “…where the company is writing you a note as opposed to “I am putting [you] into a trust in passing”, then they should be holding some form of liquidity on that side so that when it comes to getting the cash [then] the cash is available for it to happen on that basis. So, if they want to go via a model where they are creating ownership in the middleman type process, then I think that there is going to have to be liquidity requirement.”

- Two interviewees claimed that if the P2P lender promises liquidity and itself is obligated to deliver thereon, it should bear liquidity requirements. The co- founders of a South African P2P lender summarised this succinctly as:

P 9: Co-founders CEO COO_P2P Lender “…the minute you start making a return, offering a return, offering a guarantee, the minute you start even creating some liquidity pooling or pretending that you’ve got one then you need to have liquidity to give people what you promised.”

- Four interviewees clearly stated that if the P2P lender constructed certain liquidity transformation (akin to maturity transformation) then it should bear liquidity requirements. The following quote is indicative of this:

P 4: Head Central Treasury_Bank “…there is less liquidity transformation so [is] the risk in the system and you need less liquidity regulation.”

- Three interviewees noted that if the P2P lender’s balance sheet is involved in the transaction and it is leveraged, then the P2P lender should bear liquidity requirements. - Five interviewees commented that if the P2P lender’s balance sheet was involved in the transaction and the balance sheet showed any signs of complexity, then the P2P lender should be subjected to liquidity requirements. Two interviewees provided insight on these two points as follows:

P10: Dr_p.Head Investment Bank “…if these P2P lending platforms become more like banks, and particularly in [operating structure] category 3, certainly the same would apply [like] banks and not just as far as liquidity is required but also capital requirement.”

P18: Financial Stability Analyst_Regulator “It would be liquidity requirements, I think, that are similar to banks where the banks were conducting the activities similar to those of the platforms. Like securitization.”

- Three interviewees stated that if the P2P lender pools risk, it should be subject to liquidity requirements.

P 6: Global Chief Digital Officer_Financial Group “…those who are trying to securitize or pool things on balance sheet, they will likely be subjected to the same type of governance as banks because they are operating far closer to a bank than the direct retail-to-retail model…”

The element of balance sheet involvement infers a guarantee or a promise to the counterparty contingent on the entity remaining solvent, reflected as a liability on the entity’s balance sheet (Werner, 2016) (refer to section 2.4). In other words, the category two operating structure for the P2P lender includes an obligation to repay the lender simply because the lender’s money sits on the balance sheet of the P2P lender. The concept of obligations (be they of a liquidity or return nature) was captured with the code “Guarantees / promises”, which occurred across seven interviews and, intriguingly, supported most by the FinTech sample group (63% of the group referred to the concept). As the FinTech contingent put it:

P 9: Co-founders CEO COO_P2P Lender “Any lender of record needs to be regulated if they are making promises to people (who have given them money) about returns.”

P 6: Global Chief Digital Officer_Financial Group “If the model is, “but we also guarantee your stuff” they have to be subjected to both capital and liquidity once.”

P 5: Global Head FinTech Innovation_Financial Group “The promise of liquidity that the platform makes to the end investor is what becomes relevant to liquidity. If I can demand my funds on an event…”

The case of the category one P2P lender (being operating structure per section 2.1.4) was much clearer. The category one P2P lender’s balance sheet is not involved in the ultimate transaction between borrower and lender; it acts purely as an introductory and facilitation agent. Ten out of 18 interviewees confirmed that category one P2P lenders should not bear liquidity requirements; only one interviewee proposed that they should. 38% of the regulation sample group concurred that category one P2P lenders should not bear liquidity requirements; this group’s voice was the loudest in this regard. Notable quotes included:

P 5: Global Head FinTech Innovation_Financial Group “I don’t think so because unless you are doing it off your balance sheet, unless you are doing it with your own money. The whole reason that liquidity and capital management is there in the first place is to protect the depositors’ funds.”

P 8: Founder_FinTech Consultancy “…if they are providing just matching, bringing two markets together, not necessarily. Then they are acting more like a broker.”

P15: Prof_Founder Director Portfolio Manager_Investment Firm “But in [category] one and in [category] two the P2P isn’t creating credit. The P2P isn’t levering the balance sheet. You have got assets that equal 100 on the one side and you have got a liability of 100 on the other side and your shareholders equity is unlevered.”

Other interviewees were supportive of the concept of liquidity requirements (still relating to the aforementioned conditions) but not in the same shape and form as the bank regulatory liquidity requirements. The two deductive codes that best captured this sentiment were “P2P should bear different liq req” and “P2P Cat I should bear different liq req”, which occurred in four and five interviews respectively. The responses to these codes (linked to others) prompted some discussion on whether P2P should fit into other existing regulatory regimes or whether it required an entirely new regulatory regime of its own. The thinking on different liquidity regulations for P2P lenders was captured by the following quotes:

P 6: Global Chief Digital Officer_Financial Group “…the first category is far too different to a bank I think it should be regulated and there should be some kind of structure to help manage it but not as close to the bank regulation.”

P 1: Product Developer_Bank “For liquidity requirements, but not to the extent of the similar liquidity requirements of the banking sector.”

Harking back to the earlier concept that P2P lending could be akin to a fund, one interviewee suggested that existing fund management regulation (in South Africa namely the Collective Investment Schemes Act) may have applicability to P2P lending:

P 2: Head Credit Investments_Bank “I think you should regulate the [P2P] market as an asset manager. In other words: is there due process followed, is there due diligence made, [are] there updates to investors etc.”

Some interviewees linked the need for some regulation of P2P lenders (different to those of banks) in order to ensure that the industry was acceptably governed, making it safer for consumers (both borrowers and lenders) and laying the foundations for the longevity of the business model. Insightful quotes included:

P 3: Dr_Head Insurance_Funds_Credit_Bank “So, I think that should be capital and liquidity tools in place irrelevant to what the legal structure is.”

Table 16: Codes relating to P2P lending platforms and liquidity requirements

Code Code family Total # interviews code in which code usage occurred *If B/S complexity, should bear Liquidity requirements 5 5 liq req *If leverage on B/S, should bear Liquidity requirements 3 3 liq req *If promise liq then bear liq req Liquidity requirements 3 2 *Investors should bear cap / liq Capital requirements & 3 3 req Liquidity requirements *Liq transformation needs liq req Liquidity requirements 5 4 Guarantees / promises Capital requirements & 26 7 Liquidity requirements If B/S involved, should bear liq Liquidity requirements 9 5 req P2P Cat I should bear different Liquidity requirements 7 5 liq req P2P Cat I should bear liq req Liquidity requirements 1 1 P2P Cat I should not bear liq req Liquidity requirements 15 10 P2P should bear different liq req Liquidity requirements 5 4 P2P should bear liq req Liquidity requirements 3 2 P2P should not bear liq req Liquidity requirements 7 3 Pooling should bear liq req Liquidity requirements 3 3

Some Cats should bear liq req Liquidity requirements 1 1

5.3.3.3 Interview question 22

“Question 22: Do you think that online P2P lending platforms should bear similar regulation to banks with respect to capital requirements? [category question: yes or no] Does the operating structure of the P2P platform (consider the three broad categories) affect this? [category question: yes or no] Please elaborate. [open question]”

Many of the key inductive concepts that arose in response to question 21 carried over into question 22. The code family “Capital requirements” applied largely in question 22. The structure of the findings was similar to question 21, where few interviewees outright confirmed or denied that P2P lenders should bear capital requirements (zero and five respectively for the broad deductive codes “P2P should bear cap req” and “P2P should not bear cap req”). However, rich conversation emerged around the contingent situations (based on operating structure) in which P2P lenders should bear capital requirements:

- Two interviewees remained vague, stating that some P2P lenders should bear capital requirements depending on the operating structure. As one interviewee put it:

P11: Global Head Digital Operations_Financial Group

“P2P lending platforms actually should be regulated based on their operating

structure and based on how their model actually works. Different P2P lenders have certain nuances in the way that they position it to lenders and borrowers…”

- Eight interviewees were of the view that if the balance sheet of the P2P lender is involved in the transaction (as per the category two and three operating structures) then the P2P lender should be subject to capital requirements. This was largely supported by the FinTech sample subgroup, 63% of whom were in agreement on the matter. “If B/S involved, should bear cap reg” cooccurred with “B/S involvement” thrice. A notable quote was:

P17: Dr_CEO_Financial Services Group “That then needs to be a bank. That needs to, same like a bank.”

- There were three interviewees that felt that leverage on the balance sheet of the P2P (where the balance sheet was involved in the transaction) was deserving of capital requirements.

P 5: Global Head FinTech Innovation_Financial Group “…even in the very limited example you would be creating note structure. Unless you are leveraging stuff, you aren’t actually creating true balance sheet risk.” - Three interviewees confirmed that balance sheet complexity of any sort (as in the category three operating structure) implied that the P2P lender should bear capital requirements.

P10: Dr_p.Head Investment Bank “…if these P2P lending platforms become more like banks, and particularly in your category three, certainly the same would apply with banks and not just as far as liquidity is required but also capital requirement.”

- Four interviewees confirmed that P2P lenders that pool risk should bear capital requirements. The academics were behind this notion, with 40% of the sample subgroup agreeing.

P 1: Product Developer_Bank “To the extent that there is on balance sheet risk, the issuing of a note in the shape or form, the investment goes into a pool, they don’t really have line of sight of where that money is going, and how that money is being transformed from the liquidity perspective. Are they giving up, are they putting [it] into long term structures? Are they putting [it] into risky investors? What exactly are they being invested in? To that extent I think the capital environments should be a lot stricter.”

P 8: Founder_FinTech Consultancy “…if the money is on balance sheet and you are taking the risk with the platform itself then it should be [subject to capital requirements], especially [as] the platform aggregating those loans and facilitating the lending of them.”

Similar to question 21, the case for category one (operating structure) P2P lenders was clear: 11 interviewees stated that they should not be subject to capital requirements whilst only one interviewee was of the view that they should be subject to capital requirements. The sample subgroup most in support of category one P2P lenders not being subject to capital requirements was the lending subgroup (78% of the subgroup agreed on this) followed by the regulation subgroup at 75%. Notable quotes included:

P 1: Product Developer_Bank “To the extent that it is completely off-balance sheet and the individual borrower and lender have line of sight to and what they are investing in, I think the capital requirements will be less.”

Similar to question 21, interviewees thought that P2P lenders should be subject to different capital requirements: four interviewees felt that P2P lenders should bear different capital regulations (all four were in the banking sample subgroup, resulting in 31% of that subgroup supporting this notion) whilst five interviewees felt that specifically category one operating structure P2P lenders should bear different capital requirements.

P 8: Founder_FinTech Consultancy “…you are taking on balance sheet so yes, they should be regulated but not on the current framework.”

P17: Dr_CEO_Financial Services Group “Its own framework, so that is for the matched category where you are going from, you can see visibly what you are going into.”

Table 17: Codes relating to P2P lending platforms and capital requirements

Code Code family Total # interviews code in which usage code

occurred *If B/S complexity, should bear Capital requirements 3 3 cap req *If leverage on B/S, should bear Capital requirements 3 3 cap req *Investors should bear cap / liq Capital requirements & 3 3 req Liquidity requirements B/S involvement P2P behaviour 29 12 Guarantees / promises Capital requirements & 26 7 Liquidity requirements If B/S involved, should bear cap Capital requirements 18 8 req P2P Cat I should bear cap req Capital requirements 1 1 P2P Cat I should bear different Capital requirements 5 5 cap req P2P Cat I should not bear cap req Capital requirements 17 11 P2P should bear different cap req Capital requirements 5 4 P2P should not bear cap req Capital requirements 9 5 Pooling should bear cap req Capital requirements 4 4 Some P2P Cat's should bear cap Capital requirements 2 2 req

5.4 Other findings

5.4.1 Different regulation

A clear view that emerged from 12 interviewees was that P2P lending platforms require some form of regulation to be considered safe in the context of the financial system which affects borrowers, lenders and other connected parties. The context of the conversations indicated that these regulations needn’t be liquidity or capital specific but should encourage forms of good governance in the industry. This connected with the notion of sophisticated investors as presented in section 5.3.3.1. The inductive code “*P2P requires regulation to be safe” cooccurred with “P2P should bear different regulation” five times. Notably, the co-founders of a South African P2P lender agreed, saying that:

P 9: Co-founders CEO COO_P2P Lender “…you’ve got to have some regulation but it needs to be new, it needs to be its own.”

Another said that:

P 3: Dr_Head Insurance_Funds_Credit_Bank “I think that capital and liquidity requirements are critical. I just don’t think regulators are the only tool. We need investor protections. So, this is the same

as, do they need regulations? They need regulations in the context that the fund

management industry has regulations. But they don’t necessarily, the answer is not necessarily a regulator in the context of a bank regulator.”

Advancing the notion presented in section 5.3.3.2, two interviewees associated the issue of regulating P2P lenders with existing regulation that governs funds.

P 3: Dr_Head Insurance_Funds_Credit_Bank “Could it be a regulator “light”? Sort of similar to what you get in the funds business versus a bank regulator which is a lot more onerous.”

Interviewee 18, working in regulation at the time of the research, commented that market conduct (relating to good governance) was important:

P18: Financial Stability Analyst_Regulator “I think that’s appropriate given that, I mean even like finance companies currently in South Africa [are] regulated from a conduct perspective at least. Even if we start there it’s a good start. I wouldn’t be against regulating P2P platforms altogether.”

5.4.2 Sustainability of the business model

Beyond safety for consumers, interviewees spoke about how some form of regulation was required to ensure the good governance and longevity of the industry. This was partly captured by the inductive code “*Unsustainable business models”. It arose in eight interviews, predominantly supported by the academic sample group (80% concurred) and then the lending sample group (67% concurred). It cooccurred with “*P2P requires regulation to be safe” twice, producing the following noteworthy quote from the CEO of a large financial services group:

P17: Dr_CEO_Financial Services Group “If I was even in this [P2P] industry I would make sure that I create some form of regulation as leader in an industry, to make sure that we could protect the industry

from unscrupulous behaviour.”

The inductive code "*Regulation can be stifling" arose in the context of these conversations, indicating a “Goldilocks” issue with the amount of regulation: too much can be stifling for business and innovation whilst too little opens the door for abuse by unscrupulous parties. "*Regulation can be stifling" occurred in 14 interviews, claiming significant support from all the sample groups: 100% of the academic sample subgroup agreed, 88% of the FinTech sample subgroup agreed and 75% to 85% of the other four subgroups agreed too. "*Regulation can be stifling” cooccurred with "*P2P should bear diff regulation" three times, soliciting the following comment from the founder of a South African P2P lender:

P12: Founder MD_P2P Lender “…it shouldn’t be restrictive and basically, how can I say, turn these P2P lending platforms into banks. Or put them into the same pigeon hole that you would with banks…”

A FinTech lawyer commented that regulating P2P lenders similarly to banks with respect to liquidity and capital was contradictory with the foundational rationale for P2P lending:

P15: Prof_Founder Director Portfolio Manager_Investment Firm “To me, P2P mitigates the need for that, that is exactly what P2P shouldn’t be.”

"*Regulation can be stifling” cooccurred with “*Unsustainable business models” once and provided the below quote, which suggested that should P2P lenders be forced to hold capital and liquidity requirements similar to banks, it may compromise the existing business model:

P10: Dr_p.Head Investment Bank “Does it destroy the business model? Would people have to pay higher interest rates to be able to cover these costs? Would these institutions have to charge less in their fees, which would affect the business model?”

Although P2P lenders are not governed by the Banks Act in South Africa and as such do not fall privy to liquidity and capital requirements, P2P lenders are governed by the National Credit Regulator (“NCR”) which ultimately aims to protect consumers. However, three interviewees confirmed that the National Credit Act (“NCA”), as dictated by the NCR, is presently stifling the P2P lending platform business model in South Africa. The situation is summarised by the following quote:

P 5: Global Head FinTech Innovation_Financial Group “…in SOUTH AFRICA I think the growth of the industry is severely hampered by the view of the National Credit Regulator. But if you are going to be providing funds through the platform you need to be registered as a credit provider, and that basically kills any sort of retail investor potentially going onto the platform.”

Whilst the NCR’s treatment of P2P lending in South Africa may not have been well received by the market, it echoes with the notion that lenders are not able to accurately gauge credit risks (the risk associated with the counterparty to a loan) and therefore require protective regulation of sorts, akin to the existing consumer protection. This is captured in the code “Lenders inability to measure risks” which featured in nine interviews. The lenders inability to accurately measure the risks in a transaction is related to the concept of asymmetric information, where lenders and borrowers have imperfect information on one another. "*Information asymmetry" and "Lenders' inability to measure risk" cooccurred to produce the following quote, where the founder of a South African

P2P lender recognised his/her responsibility to reduce information asymmetry:

P12: Founder MD_P2P Lender “…our responsibility [is] just to make sure that you vet those ideas correctly in order to make sure that we take care of the lending parties investment, and giving them enough information in order to make their decision on the lending…”

Four interviewees voluntarily discussed the viability of the P2P lending platform business model in South Africa; some had their doubts. This was captured by the code “*P2P may not work in SA”. Worth noting was that it was the lending (where 33% were in agreement) and the FinTech (where 25% were in agreement) sample subgroups that supported this notion the most. Other than the issues around the NCA, the concerns about the future success of the P2P lending business model in South Africa included (a) the issue of an

insufficiently sized lending (investing) pool relative to the borrower pool (societal structure); (b) the access to the technology required for P2P lending transactions; and (c) that generic interest rates associated with low risk investments in South Africa are high enough so as not to encourage investors to seek P2P lending type investment to bolster their returns. Quotes indicating (a) and (c) include:

P14: Founder Director_Alternative Lending “I maintain that it may never work or [that] it would take a long time for a real P2P platform to get going because we don’t have the lending pool.”

P 7: CEO Life Insurance_Financial Group “I don’t see the returns and the propositions [as] so attractive that people are going to spend a massive amount of well-earned cash to get to a point when it becomes bubble like. The big thing is that as a lender you can most probably lend at least say a mid-teen interest rate. We would have to ask [whether] most investors would be satisfied for a mid-teen [rate] on something that is significantly more risky.”

Seven interviewees claimed that P2P lending is not a novel concept, that it has existed in various other forms in years prior albeit not in online digital form. This was a view largely put forward by the FinTech sample group where 63% of them supported the notion. The co-founders of a South African P2P lending platform commented that:

P 9: Co-founders CEO COO_P2P Lender “…you always experienced the bank to provide those services but historically a bank did not. So, you are just going back pre [a] time when the bank took on that credit role.”

5.4.3 Insight into the risky nature of online P2P lending platforms

Relating to the risks specific to P2P lending platforms: although the author only created one deductive code (“Lenders inability to measure risks), interviewees volunteered a wealth of data on the elements that they considered risky (not necessarily translating into systemic risk) with respect to the online P2P lending proposition. The code family “P2P risks” captures the essence thereof, summarised in Table 18 below. The lion share of the codes therein were inductive in nature. A few of the relevant codes have been discussed earlier in Chapter 5. Table 18 summarises the outstanding inductive issues that arose in this regard.

Six interviewees raised the concern that P2P lending platforms have or develop high risk loan books primarily due to the fact that the types of loans that are facilitated (or issued) by P2P lending platforms are inherently high risk in nature, being loans to borrowers that may not be able to access credit through traditional banks. The concept of a high-risk loan book links with “*High risk underlying” and “*Binary outcome” (as discussed in section 5.3.2.5), which occurred in four and two interviews out of 18 respectively. These two codes cooccurred to produce the following quote:

P 7: CEO Life Insurance_Financial Group “The loss default on those loans are staggeringly high because there not necessarily assets in the background to protects them, it’s not like you are going to get cash back when they do default. That’s why I am saying that it is a very 0/1. On the upside, you might get fifteen or twenty percent and on the downside, you might lose everything.”

Relating specifically to operating structure categories two and three, three interviewees made reference to “*Double risk / CLN”, where CLN refers to a type of credit derivatives in the financial markets called a credit-linked note. This code speaks to a lender into a note issued by a P2P platform may be taking on credit risk to both the underlying borrower and the issuing entity being the P2P platform.

In favour of P2P lending platforms was the inductive code “*Data makes better credit decisions”, which proposes that a data driven credit decision is more effective than traditional human judgement.

Table 18: Codes relating to P2P lending risks

Code Code Total # interviews family code in which usage code occurred *Binary outcome P2P risks 6 2 *Bad quality / high risk loan books P2P risks 16 6 *Data makes better credit decisions P2P risks 2 2 *Double risk / CLN P2P risks 5 3 *Good quality loan books P2P risks 1 1 *High risk underlying P2P risks 8 4 *Information asymmetry P2P risks 5 4

5.5 Summary of results

Table 19 summarises the key data results in tabular format.

Table 19: Summary of key data results

Research question one

It depends on the operating structure, which also affects risk posed by P2P lenders compared to banks. If the balance sheet of the P2P lender is involved and/or pooling is performed, the P2P is

behaving like a bank.

Financial intermediation theory applies to P2P Are online P2P lending lenders whether or not they are behaving like banks platforms behaving like (theory applies to non-banks). banks? Banks play an important socio-economic role: transactional enablement and store of value. Category one operating structure not behaving like a bank.

Research question two

P2P platforms do not pose systemic risk presently as the industry is still too small. However, they could pose systemic risk in the future if the industry grows (linked to institutional involvement), the balance

sheets of P2P platforms are involved, the P2P loans are high risk, leverage is present or if pooling occurs. Notable components of systemic risk include: size of industry, interconnectedness (which leads to Do online P2P lending contagion) and leverage. platforms pose systemic Category one operating structure deemed less risky. risk to the South African GFC had less impact on South Africa and it is financial system, debatable whether this was due to exchange control specifically in the absence as South Africa already had sound regulatory of liquidity and capital protection in place. Exchange control can amplify regulation? domestic risks. Debate on whether P2P lending is restricting or creating liquidity. Maturity transformation is related to restricting liquidity. Banking is built on confidence: confidence and liquidity are married and if the marriage is compromised it can take down a bank.

Research problem

Generally, regulation of P2P lending is required to keep it safe, protect consumers and ensure a sustainable industry. However, too much regulation may stifle the industry, like the application of NCA to P2P lending. The role of the bank regulator includes depositor protection (linked to a moral hazard debate), systemic risk containment and ensuring the construction of quality balance sheets (good assets and capital adequacy). Investor protection is not the role of the bank regulator; should be covered elsewhere in the regulatory mix. Does the lender intend to deposit or invest funds? This indicates whether the funds are savings or risk capital. The former requires depositor protection Should online P2P lending (bank regulator oversight) whilst the latter involves platforms be regulated like investor protection (requires market conduct banks in South Africa, with oversight). Investors are deemed sophisticated and specific respect to liquidity make own risk decisions. Unclear whether P2P and capital requirements? lenders are able to do so. Liquidity and capital requirements do mitigate systemic risk and act as confidence tools. Whether they should apply to P2P depends on the operating structure. If the P2P platform's balance

sheet is involved, it makes promises, it performs maturity transformation, it performs pooling or leverage then liquidity and capital regulations should apply. Category one should not bear liquidity and capital regulations. Where applied to P2P lenders, it's debatable whether liquidity and capital requirements should mirror bank regulation as this may sterilise the business rationale.

6. CHAPTER 6: DISCUSSION OF RESULTS (Appendix 3 may refer)

Chapter 6 allowed the opportunity to melt together the theoretical literature, the P2P lending industry metrics and the data results in order to form and corroborate findings. In search of whether or not P2P lending platforms should be regulated similarly to banks, qualitative exploratory research was undertaken the results of which are presented in Chapter 5. Here following these are considered together with the literature in the context of the research problem. Key insights (summarised in section 7.1) included that financial intermediation theory does apply, it was debatable whether P2P platforms are behaving like banks, P2P lending may prove systemic in South African in the future and – where certain elements are present in the operating structure – liquidity and capital regulations should be applied to P2P lending platforms.

For the discussion in Chapter 6, a reminder of the P2P platform operating structure categories is useful. With reference to section 2.4.2, the following is a brief summary thereof:

- Category one: the P2P lender acts as an introductory agent. It does not create obligations (liabilities) or assets to clients on its own balance sheet. - Category two: the P2P lender involves its own balance sheet in the transactional

equation insofar that it accepts client money onto its balance sheet (attached to

a future – albeit contingent – obligation to repay it) and then on-lends the money to clients (an asset on its balance sheet). However, the nature of the balance sheet remains uncluttered with limited (if any) leverage or structuring. Also, the money from a specific lender is directly connected with the on-lent money to a specific borrower through the wording of the legal contracts. - Category three: the P2P lender pools the money from lenders (obligations) and from the pooled source lends money to borrowers. Specific lenders and borrowers are no longer connected by the wording of the legal contracts. The pooling may occur either on the balance sheet of the P2P lender or off the balance sheet of the P2P lender in an investment vehicle. Further, the P2P lender may apply leverage and/or structuring elements thereto.

6.1 Sample concerns

Threats to the credibility (akin to validity) and dependability (akin to reliability) of the data were addressed were largely addressed by the author by employing methods recommended by qualitative research literature (detailed in section 4.3). Regards the

basis of evidence: quotes from interviewees were not taken at face value but rather considered in the context of the sentence and corroborated with input from other interviewees from different trades. For example, findings were cross checked between the banking and regulation sample subgroups. In Chapter 6 findings were further corroborated with literature and P2P lending industry metrics.

As discussed in section 5.1, two interviewees were included in the sample who had less than ten years’ relevant industry experience. However, as both had valuable experience in the arenas of FinTech and P2P lending which is rare in South Africa, the author included them in the sample. The overall sample size was healthy at 18 interviews, reinforcing that these two interviewees were included for the value that they added not to meet quota requirements.

6.2 Research question one: Are online P2P lending platforms behaving like banks?

6.2.1 Financial intermediation theory

A cornerstone that supported much of the structure of the research is that of banking theory, specifically financial intermediation theory. It was recently analysed by Werner in his 2016 work. Werner (2016) advised that financial intermediation theory may apply to non-bank entities as well, where their money-in-money-out activity may be akin to that of a bank, although a bank would be deposit taking and on-lending. These terms and the legal implications related thereto may not necessarily apply to the financial intermediary, although the economic effect is similar.

The data agreed with this point, as indicated by the code “*Applies to non-banks” which occurred in 10 out of 18 interviews (refer to section 5.3.1.2). Certain interviewees associated this notion with that of disruption. Although not a critical connecting component with the intersecting spheres of banking theory, banking regulation and systemic risk, it may be of interest to other researchers.

A key differentiating factor for Werner (2016) is that banks show the money-in leg (for banks this is deposits) on the balance sheet as senior ranking obligations. This element of the transactional equation certainly arose in the data, specifically through two codes: “Guarantees / promises” and “B/S Involvement”, which together speak to the act of a financial intermediary accepting funds onto its balance sheet with a promise attached thereto that they shall be repaid in line with certain terms. This is a critical step: the act of accepting obligations onto the balance sheet shifts the entity from being unlike a bank toward being akin to a bank through the eyes of Werner (2016).

The evidence from the data in section 5.3.1.1 was mixed as to whether P2P lenders are behaving like banks. The meaningful finding is that interviewees associated the P2P lending behaviour with that of a bank in certain situations, meaning that some operating structure categories are akin to a bank whilst others are not.

The data related the notion of whether or not a P2P lender is behaving like a bank with whether or not its balance sheet is involved. This is clear in section 5.3.1.1 where the code “B/S Involvement” cooccurs with all the deductive codes that confirmed whether or not a P2P lender is indeed behaving like a bank. This evidenced the notion that the balance sheet involvement of the online P2P lender in the transaction between lender and borrower (whether this be in the form of a deposit or otherwise) is a determining factor as to whether or not that P2P lender is deemed to be behaving like a bank. A quote that captured this eloquently was:

P13: Prof_Director FinTech Regs_Law Firm “The moment you take deposits and promise to repay some or other part of the money you receive, that is the business of the bank.”

The concept of on balance sheet pooling (where specific borrowers are not associated with specific lenders resulting in the pooling of obligations (liabilities)) was also found to be similar to banking activity. This is akin to a category three operating structure and connected with the work of Diamond and Rajan (2001) who noted that it has long been the business of a bank to accept and aggregate liabilities (including deposits and other forms of funding).

This led to the discussion on category one operating structure P2P lenders. Werner (2016) commented that stockbrokers are financial intermediaries whose balance sheets are not embedded in the nature of their work: they do not commit to obligations to clients. Through the lens of theory, these types of entities are not akin to banks but do fall under the ambit of financial intermediation theory. The data echoed with this, where four interviewees agreed that category one P2P lenders are unlike banks; none of the interviewees proposed the opposite to be true.

6.2.2 Other banking theories

Philips (1920) and Werner (2016) spoke about the application of fractional reserve theory in the context of the banking system only, with reference to the money multiplier effect. The data agreed that fractional reserve theory has little application to P2P lending platforms as they do not deposit a portion of their assets with the central bank. Section 5.3.1.2 presents data indicative of this. As such, the author concluded that fractional

reserve theory is not relevant to P2P lending platforms in the current environment in South Africa.

The essence of credit creation theory is the leverage that it proliferates in the system (Werner, 2016). The association of leverage with credit creation theory in the data (as laid out in section 5.3.1.2) indicated that should category two and/or three operating structures occur, then credit creation theory may have application to P2P lending platforms.

6.2.3 Comparing the roles of banks and online P2P lending platforms

In relation to whether or not P2P platforms are behaving like banks, the conversations with interviewees inductively led to the topic of the role that banks’ play in society. The data in section 5.3.1.2 emphasised the socio-economic role of banks with respect to three elements: transactional enablement, a store of value (which relates to the theme of depositors) and the medium via which monetary policy is transmitted. Although not a new realm in academic literature in of itself, the role of banks was inductive insofar that it connected with the debate on whether or not P2P lending platforms are behaving like banks.

This connected further with a bigger theme: the intention of lenders in a P2P transaction. Does the lender via a P2P platform intend to store value or earn a superior return for the risk he/she knowingly takes on? To the extent that lenders seek a store of value when they transact with P2P platforms, it appears then that lenders seek that which a bank has traditionally provided them with. It featured strongly in the data, the results of which are presented in sections 5.3.2.6 and 5.3.3.1. In this light, the intention of the lenders is a central contributory factor toward assessing whether or not a P2P platform is behaving like a bank. The intention of lenders via P2P platforms is considered an emergent theme as an inductive insight and one deserving of future exploration.

The activities of banks extend beyond lending. Feedback from interviewees on whether P2P lending platforms were more or less risky than banks was mixed, as presented in section 5.3.1.3. The interviewees thinking supporting their views was that P2P lending platforms are riskier than banks simply because banks are highly regulated entities. This concurred with Moshirian (2011) who commented that it is the lack of effective regulation that allows room for financial risk to develop. Wang, Shen and Huang (2016) and Wei (2015) all confirmed that regulated entities offer safer investment realms.

This connected with an inductive point raised during the coding process: that some P2P lending platform were founded and are run by individuals with aggressive risk-taking

mentalities. This connected with work by Douglas (2016) who commented that the people driving FinTech start-ups are risk taking in nature and may disregard regulation, which tied up strongly with the sentiments expressed by interviewees in section 5.3.1.3. The results indicated interviewees' concerns about the founders of certain P2P platforms in various jurisdictions where their attitudes and actions display a concerning disregard for the regulations designed to safeguard the financial system. This connected further with the notion raised by interviewees that the industry requires regulation to ensure the safety of consumers and the financial system. The concerns raised by interviewees were that the absence of regulation allows room for unscrupulous behaviour from industry participants. These sentiments are presented by the data in 5.4.2.

Interviewees continued that P2P lending platforms pose more risk as one progresses from a category one operating structure to a category two or three operating structure. This linked with the literature which advised that the P2P lending platform operating structures are not standardised across geographies (Financial Times, 2014; Grant Thornton, 2015): the amount of risk that consumers absorb and the degree to which P2P platforms can be considered similar to banks depends on the operating structure of the P2P platform. Regulated financial entities were deemed safer by both the literature and the data.

In conclusion to research question 1, both the literature and the data confirmed that it is the nature of the operating structure and legal ramifications therefrom for a consumer that drives whether a P2P platform is behaving like a bank. The presence of the balance sheet of the P2P lender in the transactional equation leads one toward the camp that P2P lenders are behaving like banks. Both data and literature further indicated that the activity of on balance sheet pooling of liabilities and assets is akin to a bank (Diamond & Rajan, 2001). In this light, it appeared that a P2P lender with a category one operating structure (purely playing a facilitation role) is not behaving like a bank whilst the involvement of balance sheet and the act of pooling (akin to operating structures two and three) suggest that those P2P platforms are behaving like banks. At this point, evidence that lenders have depositor type intentions would conclude whether P2P platforms are indeed behaving like banks. This is precisely where and why further research is required on the specific matter of the lenders’ intentions who transact through P2P platforms.

6.3 Research question two: Do online P2P lending platforms pose systemic risk to the South African financial system, specifically in the absence of liquidity and capital regulation?

6.3.1 Components of systemic risk in South Africa

Moshirian (2012) spoke extensively about the interconnectedness between players in a financial system that gives risk to the contagion of financial distress, ultimately risking a large portion (if not the entire) system. The data presented in section 5.3.2.1 agreed strongly with this: the risks of being interconnected and the effects of contagion were recurrent codes throughout the interviews. A notion that arose alongside these was the size of the industry both in relative form (relative to the total lending industry) and absolute form (implying the number of people that might be affected). The literature emphasised the size of individual players within a financial system (Moshirian, 2012; Roulet & Blundell-Wignall, 2013) as opposed to the size of the industry. The extent to which the data related the size of the industry with (a) the presence of systemic risk (discussed in section 6.2.3.1) and (b) P2P lending platforms’ effect on the general liquidity of a market (discussed in section 6.2.3.3) reinforced that the size of the industry is a prominent factor in the systemic risk equation.

The data were mixed with respect to whether or not only large concentrated players pose systemic risk. Section 5.3.2.1 indicated how there were interviewees in both camps: the size of the individual financial market participants determines whether systemic risk is created versus the school of thought that small interconnected financial market participants also create systemic risk. Whilst Moshirian (2012), Roulet and Blundell- Wignall (2013) and Werner (2016) agreed that the size of individual players influences the systemic risk present, the data indicated that systemic risk could be present whether or not the players in a financial system were of significant size. This differentiation highlighted the data’s preference for interconnectedness as the key systemic risk ingredient.

Interviewees raised the point that systemic risk is non-diversifiable. This opposed the view by Wei (2015) that diversification could reduce the build-up of systemic risk.

Roulet and Blundell-Wignall (2013) proposed that the root causes of systemic risk are maturity transformation, leverage and credit intermediation. It was the first two elements that arose in the data as prominent features in interviewees’ dialogue on systemic risk. The presence of leverage was strongly associated with systemic risk as laid on in 5.3.2.1 with some interviewees stressing the point that leverage amplifies the effects of (as opposed to just causes) systemic risk.

Maturity transformation arose as a concept not in the abstract discussions on defining systemic risk but rather in the specific discussions on whether or not P2P platforms are restricting liquidity in the market and whether or not they should bear liquidity requirements. These results are presented in sections 5.3.2.7 and 5.3.3.2 and discussed in section 6.2.3.3. In essence, managing maturity transformation has long been the business of banks (Diamond & Rajan, 2001). Maturity transformation offers the opportunity for enhanced returns (as banks borrow short dated money to invest in long dated assets) (Werner, 2016) but brings with it the risks associated with run on the bank and the bank being underfunded in the short term to make good on those obligations. This lays the foundation for why supportive regulatory regimes exist for banks (Bank for International Settlements, n.d.). The data results indicated that (a) P2P lenders may restrict liquidity in the market if they are performing maturity transformation and (b) P2P lenders should bear liquidity requirements if they are performing maturity transformation. Both the concepts of restriction of liquidity (Foster, 1986; Fernando & Herring, 2002) and maturity transformation (Roulet & Blundell-Wignall, 2013) were strongly associated with systemic risk in the literature and the data and, further, were interrelated in the data. As such, these two elements are related components of systemic risk.

An interesting connection was made between the literature and the data regards the accurate pricing of risk. Wang, Shen and Huang (2016) commented that this is a critical function performed by financial intermediaries. It was Fernando and Herring (2002) that specifically linked this with the generation of systemic risk when they spoke about the formation of asset bubbles and the presence of information asymmetry. These thoughts are consistent with the findings in section 5.3.2.1 and 5.4.2, where interviewees spoke of the likelihood of either (or both) attribute(s) being present in market distress scenarios. Data in section 5.3.2.1 spoke of the mispricing of risk, specifically the times when the gap between the price of good quality risk versus bad quality risk narrows. This is associated with “bubbles” in financial markets, which typically refers to overinflated asset prices (Fernando & Herring, 2002). Interviewees indicated that these are ingredients involved in the development of systemic risk. The author thus proposed that if the mispricing of risk is related to the generation of systemic risk and the lenders into P2P lending platform loans are not always able to accurately measure risk, then the risk pricing function should sit with the financial intermediaries. This implies that a category three operating structure for P2P lenders is desirable, where the risk selection decision is removed from lenders.

On the issue of exchange control in South Africa, the data were mixed as presented in section 5.3.2.2. Interviewees largely supported the notion that South Africa survived the

Great Financial Crisis (GFC) better than other markets, both developed and emerging. As to why, interviewees were split across three camps: exchange control does mitigate systemic risk in South Africa, it makes no difference and, lastly, it plays a role but it is not the primary factor. The last subset gave credit to South Africa’s existing regulatory framework at the time of the GFC for protecting the financial system from systemically transmitted risks. Although this outcome was deemed positive by interviewees, it also confirmed that South Africa is a highly regulated jurisdiction. Interviewees also voiced that regulation can be stifling (section 5.4.2) which connected with the existing regulatory treatment of P2P lending in South Africa, where the NCA is relatively restrictive for the industry. As such the author concluded that South Africa does indeed have a vigilant effective regulatory regime. However, this research aimed to interrogate a specific regulatory element, being whether liquidity and capital requirements should apply to P2P lending platforms.

6.3.2 Liquidity and capital requirements as tools to mitigate systemic risk

Roulet and Blundell-Wignall (2013) and Moshirian (2011) voiced their views that liquidity and capital requirements are tools to counter systemic risk. Basel regulations have been adopted by a number of jurisdictions around the globe in support of the drive toward safer financial markets with a handle on systemic risk (Bank for International Settlements, n.d.). Per the data in sections 5.3.2.3 and 5.3.2.4, interviewees largely

supported the notions that both liquidity and capital requirements do indeed mitigate systemic risk. The interviewees not in favour thereof voiced their concerns around the intention of the regulations not being achieved due to a lag effect between passing new regulations and market evolution.

Connecting with the robust theme that confidence keeps the banking system afloat, interviewees proposed that it is liquidity that ultimately leads to bank failures (data in section 5.3.2.3). This data confirmed Foster’s (1986) view that bankruptcy arises due to unresolvable liquidity issues and echoed strongly with Fernando and Herring’s (2002) thinking, who voiced that liquidity and confidence both enhance and threaten one another. This was a strong theme throughout the results illustrated in Chapter 5. In their view, it is the mismatch of expectations of liquidity versus the nonrealisation thereof that threatens confidence and in turn liquidity. This is certainly indicative, then, of the logic chain that liquidity requirements reduce the risk of a run on the bank which could spread due to contagion, hence liquidity requirements mitigate systemic risk. This was further reinforced when Wei (2015) confirmed that a significant portion of the unregulated

Chinese P2P loans were troubled between 2011 and 2014 (43.5% of the Chinese P2P platforms) due to a cash shortage.

Section 2.4 spoke to Werner’s (2016) views that systemic risk is better contained when the structure of the financial system is one made up of many small players as opposed to few concentrated ones. Werner (2016) suggested that this would be more effective than liquidity and capital requirements. On this specific point the data found otherwise: section 5.3.2.1 presented data indicating that even small players in a financial system can create and transmit systemic risk to the degree that they are interconnected.

The author concluded that whilst not perfect, both literature and data confirm that liquidity and capital requirements are indeed tools that do mitigate (not eliminate) systemic risk in financial systems.

6.3.3 Do online P2P lending platforms pose systemic risk?

With reference to the Chinese market, Wei (2015) confirmed that P2P lending is a high- risk game. Wei (2015) linked the concepts of P2P lending, systemic risk and shadow banking. Addressing the issue of whether P2P platforms pose systemic risk highlighted three central concepts.

6.3.3.1 The size of the industry

Per the data in sections 5.3.2.5, it was with conviction that interviewees stated that P2P lending platforms do not presently pose systemic risk in South Africa. However, the data indicated that P2P lending could pose systemic risk in the future. Both these findings were strongly associated with the size of the P2P lending industry, interviewees deemed it too small at present to pose systemic risk but should it grow (alongside other factors) then P2P lending platforms could pose systemic risk. To some extent the literature provided support for this, where Wei (2015) commented that P2P lending in China does contribute to systemic risk and the P2P lending industry in China is significant in size (Morgan Stanley Research, 2015; Transparency Market Research, 2016). However, the literature prioritised the size of individual players in the financial system and their interconnectedness with one another as key contributors to systemic risk whereas the data prioritised the size of the industry as a key contributor.

The other factors that interviewees cited that contribute to the generation of systemic risk by P2P lenders included the balance sheet involvement of the P2P lender, the pooling of liabilities, the presence of leverage on the P2P balance sheet and that the underlying loans (assets) that P2P lending platforms create are in themselves risky by nature. Recall that Wei (2015) spoke of the dynamic in the Chinese P2P lending market: when bad

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debts accumulated and financial distress spread through the Chinese market in circa 2014 and 2015, the lenders looked to the P2P platforms to make good on the loans. This linked the concepts of systemic risk and the obligation (associated with balance sheet liability) of P2P platforms to their lenders. Further, Roulet and Blundell-Wignall (2013) highlighted three causes of systemic risk, being maturity transformation, leverage and credit intermediation. These activities are facilitated on the balance sheet of an entity, be it a bank or a special purpose vehicle in a securitised structure. As such, that the presence of a balance sheet in between the borrower and lender and the subsequent enactment of these activities causes systemic risk.

Diamond and Rajan (2001) commented that if the unfulfilled obligations of a failing intermediary are absorbed by a separate intermediary then there is no harm done by the failing intermediary. This relates to the notion of state intervention in a financial distress scenario. However, the findings in section 5.3.2.5 indicated that P2P platforms are largely not considered systemic at present which casts doubt on whether or not the state would support them (South African Reserve Bank, n.d.-c).

Per section 5.3.2.5, the data indicated that the growth rate of the industry was connected with the presence of institutional investors into the assets offered by P2P lending platforms. The data confirmed that institutional investors are involved on both sides of the lending equation in South Africa (section 5.3.2.6). As such, there is a connection between P2P lenders posing systemic risk in the future and the presence of institutional investors, who may accelerate the growth of the industry.

6.3.3.2 Are lenders depositors or investors?

As discussed in section 6.2.3, it was through the interview process and across a variety of conversations that a critical point arose: are the lenders into P2P platforms depositors or investors? Interviewees differentiated between (a) those seeking a safekeeping mechanism for their money, a “*Store of value” and (b) those making informed risk- reward decisions in their pursuit of enhanced returns. Emekter, Tu, Jirasakuldech and Lu (2015) and Wang, Shen and Huang (2016) confirmed that investment in loans through an online P2P lending platform is indeed a riskier form of investment. Through the lens of the data, in (a) the intention of the lender is associated with that of a depositor whilst in (b) the intention of the lender is associated with that of an investor. To the extent that lenders via P2P platforms view the loans as a deposit substitute (consider the data in section 5.3.2.5), the data indicated that this strengthens the argument for P2P platforms posing systemic risk. However, it is not necessarily conditional. The notion presented by the data that the P2P lending industry has grown on the back lenders seeking superior

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yields echoes with Chaffee and Rapp (2012) and may imply that lenders are acting as investors. However, the data did not confirm what the intentions of lenders via P2P platforms are, but rather highlighted it as a key deciding factor on whether or not P2P platforms are behaving like banks, which relates to the presence systemic risk. The author recognised this as an emergent theme; a key inductive insight.

Deposits with banks have a different risk profile compared with investments that seek superior returns. The central banks in certain jurisdictions (for example the United Kingdom (FSCS, n.d.) explicitly guarantee bank deposits up to a certain level. In South Africa, the central bank does not explicitly commit to guaranteeing deposits but does commit to protecting depositors, which could imply a variety of actions (South African Reserve Bank, n.d.-c).

6.3.3.3 Restricting liquidity

Armed with the knowledge that unresolvable liquidity issues are a key cause of financial distress (ultimately bankruptcy) (Foster, 1986) which can spread in financial systems where participants are interconnected, the restriction of liquidity is a determining factor as to whether or not P2P lending platforms post systemic risk. The data supported the notion that liquidity is pivotal, evident from the discussions on how liquidity can take down banks (section 5.3.2.7). This was further reinforced when Wei (2015) confirmed that a significant portion of the unregulated Chinese P2P loans were troubled between 2011 and 2014 (43.5% of the Chinese P2P platforms) due to a cash shortage.

The data in section 5.3.2.7 were mixed: there was support for the camp that P2P lenders are restricting liquidity whilst support also existed for the opposite, that they are not restricting liquidity and in fact might be creating it. The latter was connected with the size of the industry, presently considered too small to affect market liquidity. Both Chaffee and Rapp (2012) and Chuang, Mo, Chen and Ye (2016) spoke of the positive effects of secondary markets in enhancing liquidity. This was certainly supported by the data as presented in section 5.3.2.7.

The concept of maturity transformation arose with respect to liquidity restriction, where the data suggested that the act of maturity transformation would increase the likelihood of liquidity restriction. Per the above train of thought, this would in turn aid the creation of systemic risk. This tied neatly with the thinking from Roulet and Blundell-Wignall (2013), who cited maturity transformation as one of the underpinning causes of systemic risk.

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In summary with respect to research question two, it appeared that P2P lenders do not presently pose systemic risk in South Africa but that they could do so in the future. The future state of such systemic risk is dependent on several factors: the size of the P2P lending industry (which in turn influences the restriction of liquidity); the involvement of the P2P platforms’ balance sheets; the pooling of liabilities; interconnectedness with the financial system; maturity transformation (associated with restriction of liquidity); the use of leverage and/or the mispricing of risk which leads to high-risk loan books. These elements need not occur concurrently; data and literature supported concepts independently. Whether lenders via P2P platforms are behaving as depositors or investors is a notable factor, although it did not preclude literature and data confirming that other elements may confirm the presence of systemic risk.

This threat of systemic risk was reinforced by the occurrence of consumer losses in the industry where a P2P platforms has either involved its balance sheet in the transactional equation or made direct commitments to lenders (Financial Times, 2015; Wei, 2015).

6.4 Research problem: should online P2P lending platforms be regulated like banks in South Africa, with specific respect to liquidity and capital?

Wei (2015) commented that remaining unregulated is dangerous. Chaffee and Rapp (2012) commented that because the various regulatory regimes differ across jurisdictions, regulators have found it difficult to implement a standardised or even coherent regulatory framework for P2P lenders. The data in section 5.3.2.2 indicated that current regulatory coverage of P2P lenders in South Africa is unique, where the NCA acts as a protective measure against risks similar to those in China.

The data echoed with the literature (Moshirian, 2011; Wei, 2015) when it associated the activities of P2P lenders with shadow banking (sections 5.3.1.2 and 5.3.2.5), raising the concern that economically similar transactions that occur within the regulated space are occurring outside of the regulated space. Although the author did not specifically seek to associate P2P lending with shadow banking, the concept arose inductively in the coding process and connected with select pieces of literature.

The data in section 5.3.2.5 raised the concern that the present day online P2P lending platforms have not as yet been tested in a financial crisis. Certain data penetrated the matter further, voicing the concern that in the absence of capital requirements, P2P lenders don’t stand to lose much in a financial crisis other than their reputations. This partly echoed with the principles espoused by Stiglitz and Weiss (1981) on moral hazard. However, the notion that P2P lending has not been tested in a time of financial distress

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seemed odd considering that P2P lending is not a recent concept, variations of P2P lending have existed for generations (Chaffee & Rapp, 2012; Chuang et al., 2016; Namvar, 2013).

6.4.1 The banks regulator’s role

Of primary significance is the view from interviewees that online P2P lending platforms require a form of regulation to be safe, implying that the status quo is insufficient. This is clear from data in section 5.4.1. Interviewees spoke about the notion of safety in a broader context, from the point of view of systemic risk as well as from a market conduct point of view. A quote from a significant member of the financial services community captured this:

P17: Dr_CEO_Financial Services Group “If I was even in this industry I would make sure that I create some form of regulation as leader in an industry, to make sure that we could protect the industry from unscrupulous behaviour.”

This connected somewhat with existing literature but not perfectly. Wang, Shen and Huang (2016) put forward their view that the China Banking Regulatory Commission should craft a regulatory framework for P2P lending in China which should include that P2P platforms hold capital.

Chaffee and Rapp (2012) spoke about the need for both borrower and lender protection, where borrowers’ levels of indebtedness should be contained within safety limits whilst lenders should enjoy a secure well governed environment. Section 5.3.3.1 of the findings addressed this issue squarely. The findings indicated that depositor protection is a vital role for the bank regulator to ensure. This issue reconnects with the theme of whether lenders into P2P loans are depositors or investors (connected with section 6.2.3.2 which addressed whether P2P lenders pose systemic risk in South Africa). This differentiation drove whether interviewees were sympathetic to the notion of regulatory support or not. To the extent that lenders are acting as depositors, the data agreed with the theory: the bank regulator should prioritise their protection. This aligns with both the view of the South African Reserve Bank (n.d.-c) and the stance taken by UK authorities, where the FSCS (2016) protects any lenders who have incurred losses through P2P lending due to unsuitable advice.

However, to the extent that lenders are acting as investors, the data was at odds with the literature. The data spoke about how investors who make informed risk decisions in search of higher returns are not the responsibility of the bank regulator. “*Investors at

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risk for own calls” as an inductive code was strongly evident thereof. This aligns with the stance taken by the US regulatory authorities who placed the P2P lending industry under the supervision of the SEC, which governs listed investable securities. The realm of the SEC specifically excludes lenders from any depositor protection type framework (Chuang et al., 2016). This theme in the data extended to include the notion that to the extent that lenders into P2P platforms are investors responsible for their own calls, the market should then self-regulate as investors will make appropriate investment decisions based on the risk-reward relationship. Data in section 5.3.3.1 supported this indicating that the market must discipline investors.

However, that is not to say that investors should not have any regulatory support at all. A view arose from interviewees that there should exist a different regulatory framework for investors, along the lines of market conduct and good governance. This fitted precisely with the thinking from Roulet and Blundell-Wignall (2013) where they advised that the regulatory burden should be spread across an array of regulatory authorities with different functions. The fit extended to Chaffee and Rapp (2012) who commented that P2P lending specifically should receive oversight from a variety of regulatory bodies given the multiple touchpoints that it creates (for example, consumer protectionism, the banking system and market conduct). Lastly, it was reinforced by Douglas (2016) who commented that consumer protection is prioritised ahead of innovation in the US regulator’s mind.

Emekter, Tu, Jirasakuldechc and Lu (2015) and Dapp (2014) presented marginally opposing views. The first said that P2P lending platfroms offer superior returns. The latter advised that it may be dautning for lenders to self assess credit for the first time, a funciton traditinally perfromed by experts in financial institutions (primarily banks). The data analysis yieled data that supported both views: seciton 5.4.3 indicated that the use of data (as opposed to intuition or human analysis) leads to superior credit decisions (consistent with Chuen and Teo’s (2015) view) whilst data in section 5.4.2 indicated that the lenders inability to measure risk is a concern for the business model. The latter ties in with the notion that investors require a different form of protective regulation should they wish to operate as investors but may not always be fully equipped with the required knowledge and skills. In South Africa, this role is fulfilled by the National Credit Regulator. However, its application has resulted in the avoidance (not governance) of P2P lending between individuals (Zhang et al., 2017).

Interviewees did not indicate what they believed the primary intention of lenders into P2P platforms in South Africa is, being either deposit or investment seeking. This may be due

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to the lack of evidence, as P2P lenders in South Africa remain relatively small with few retail investors due to the present restrictions of the NCA on P2P lending (Dewar & Shilongo, 2017). As such, it is difficult to conclude whether or not it is the South African bank regulator’s role to protect lenders in P2P transactions as the issue of lenders’ intentions remains unanswered, with different outcomes for each option (being bank regulatory oversight for depositors versus market conduct governance for investors).

With relation to the bank regulator’s role, Moshirian (2011) presented two concepts that were addressed by the data. First, Moshirian (2011) commented that financial stability (and consequently systemic risk containment) are the responsibility of the bank regulator. This was strongly supported by the data presented in section 5.3.3.1 where interviewees spoke about systemic risk containment as a primary function of the central bank. Secondly, Moshirian (2011) spoke about the tendency of regulations to lag the market. This too was supported by the data (section 5.3.2.3), where “*Regulation lags” featured insofar that interviewees felt that the market usually was and would likely remain a step ahead of regulatory development. As such, it is difficult to hold a regulator responsible for containing systemic risk when regulation itself is a slow-moving response pursuing nimbly evolving issues.

In the context of the bank regulator’s role, interviewees connected two key concepts with systemic risk. First, several interviewees that advocated depositor protection did so on

the rationale that it is a key element that enables systemic risk containment. For elaboration thereon, consider the results laid out in section 5.3.3.1 where certain interviewees clearly associated the notion of depositor protection with that of inspiring confidence amongst depositors and investors in the financial institutions that they select. This in turn mitigates the risk of a “run on the bank”, which is the consequence of a loss of confidence by depositors and investors in a financial institution. It is this severe drainage of short term liquidity out of a financial institution that can ultimately sink it (Foster, 1986), which may then have knock on effects to other institutions in the financial system as a result of their interconnectedness. As such, depositor protection from the regulator (be it implicit or explicit) boosts confidence and lessens the probability of the hostile effects of systemic risk playing out in a crisis scenario. This aligns directly with the work by Fernando and Herring (2002) who spoke to the crucial relationship between liquidity and confidence. This was further supported by Diamond and Rajan (2001).

The second concept that interviewees associated with systemic risk containment was the concept of high quality well capitalised banks’ balance sheets as per the data laid out in section 5.3.3.1. This concept is directly tied with the discussion in the literature on

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capital requirements in bank regulation (section 2.3.1), which leads to capital adequacy as a tool for mitigating systemic risk (Bank for International Settlements, n.d.; Moshirian, 2011). However, certain interviewees highlighted that the role of the bank regulator is ensuring the construction of high-quality balance sheets containing good assets in the first place and that this mitigates systemic risk containment. This partly connected with Werner’s (2016) view that the bank regulator should guide credit extension.

Consequently, as supported by the literature (above), it was clear from the data that several functions that are associated with the bank regulator are ultimately in pursuit of systemic risk containment.

6.4.2 Stifling versus enabling regulation

Chaffee and Rapp (2012) and Moshirian (2011) presented contradictory views, where the former commented that stifling regulations led to the birth of P2P lending in the first place whilst Moshirian commented that ineffective controls allow risk to breed. Wei (2015) supported the latter view.

Section 5.4.2 presented data that spoke exactly to this tug of war: interviewees advocated that regulation is required to ensure both the safety and the longevity of the P2P lending industry whilst a chunk of interviewees advocated that overregulation is problematic as it either stifles the development of industries or incentivises existing players to take risks that they otherwise wouldn’t have. The data in this research and insight from Zhang et al. (2017) agree that industry participants are apprehensive that an appropriate regulatory regime is required in South Africa to protect the financial system against the systemic risks that P2P lending platforms could pose if the industry grows. However, a balance should be sought to ensure that the P2P lending business model is not entirely defeated.

6.4.3 The present regulatory framework for P2P lending

Wang, Shen and Huang (2016) explored whether online P2P lending platforms are essentially performing the function of information or credit intermediaries in China. They found that P2P lending platforms are more akin to credit intermediaries as they do not provide sufficient information for lenders to make their own fully informed decisions. This contradicted the view of the Chinese regulator, who declared the opposite. In light of Wang, Shen and Huang’s (2016) view of P2P platforms as credit intermediaries, the lenders into the platforms may tend to rely (albeit indirectly) on the platform to select the credits. This insight may have application in South Africa where the data in this research (laid out in section 5.4.2) found that the lenders’ inability to accurately grade credit risks

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is a concern. This was further related with the notion of information asymmetry, which is exactly the issue that Wang, Shen and Huang (2016) spoke to. The notion of information asymmetry stems from work of Akerlof (1970) and relates to moral hazard (Stiglitz and Weiss, 1981). Fernando and Herring (2002) echoed similarly: that information asymmetry could lead to the mispricing of risk which in turn could translate into asset bubbles. Fernando and Herring (2002) associated information asymmetry and asset bubbles with market distress scenarios. In this light, the present application of the NCA protects the P2P lending industry from these risks as it restricts the lending between individuals (retail consumers), allowing lending between sophisticated entities only. However, Dewar and Shilongo (2017) highlighted the stifling effects of the NCA on the P2P lending business model in South Africa. This was confirmed by the data as presented in section 5.4.2 in which the interviewees’ view that the NCA acts as a prohibitive factor for P2P lending in South Africa was clear. However, the notion that regulations are restrictive did not preclude interviewees from purporting a strong view that online P2P lenders require regulation to be safe as laid out in section 5.4.1.

6.4.4 Whether online P2P lending platforms should bear liquidity and capital requirements

Both the literature and the data spoke about conditional circumstances in which liquidity and/or capital requirements are sensible for combatting systemic risk. There is limited

literature investigating the application of liquidity or capital controls to P2P lending in South Africa.

6.4.4.1 Obligations on the online P2P lending platform

Wang, Shen and Huang (2016) commented that lenders should be wary of platforms that make promises about returns and liquidity availability. As both the literature (Werner, 2016) and data indicated, promises are obligations on the balance sheet of the P2P lender. Should a P2P lender not have sufficient liquidity and capital requirements in place (driven by regulations) then a lender should be wary about the feasibility of the P2P lender making good on its obligations (Bank for International Settlements, n.d.; Roulet & Blundell-Wignall, 2013). Should a P2P lender not make good on its obligations and it is connected with the financial system, its default on obligations may then affect other players in the same system (Moshirian, 2012; Staum, 2012). This connected with the theme on whether or not P2P lenders are acting as depositors or investors, where the former does not have the risk appetite to incur such losses whilst an investor may have analysed the situation, noticed the lack of controls and chosen to invest nonetheless, in which case he is at risk for his / her own calls.

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Sections 5.3.3.2 and 5.3.3.3 presented results that clearly indicated the interviewees connection of liquidity and capital controls with the obligations (created via promises or guarantees) of the P2P lending platform. The data in section 5.3.3.2 confirmed that the presence of the P2P lender’s balance sheet in the transaction (which connects with the theme of promises) should subject the P2P lender to liquidity requirements. The data in section 5.3.3.3 confirmed similarly with respect to capital requirements: that the involvement of the P2P lender’s balance sheet in the transaction should require the P2P lender to meet capital regulations. This connected with Wang, Shen, Huang’s (2016) sentiment that P2P platforms are credit intermediaries and should hold capital. The balance sheet involvement is connected to the theme of promises or guarantees, which create obligations on the P2P lender’s balance sheet.

Considering the practical implications of this finding: recall that category one operating structure P2P lenders act purely as facilitation agents, making no guarantees about returns (Dewar & Shilongo, 2017; RainFin, 2017). The data in sections 5.3.3.2 and 5.3.3.3 agreed with this notion, finding that P2P lenders acting purely as facilitation agents should not be made to hold liquidity or capital requirements. In this light, P2P lenders of this nature (category one operating structures) are akin to brokers, a sentiment echoed by Werner (2016) when he spoke about financial intermediaries that do not create balance sheet commitments of their own.

It appears that the category one operating structure is the only P2P lending model that presently operates in South Africa (Dewar & Shilongo, 2017). As such, the finding that P2P lenders should bear capital and liquidity requirements to the extent that they create balance sheet obligations of their own could remain a theoretical concept in South Africa for the time being. However, the evolution of online P2P lenders in other geographies (Chaffee & Rapp, 2012; RateSetter, 2017; Wei, 2015) suggests that should the P2P lending industry grow and develop in South Africa, category two and three operating structures may occur. Morgan Stanley Research (2015) and Transparency Market Research (2016) indicated positive growth trends for the African P2P lending markets whilst certain data (laid out in section 5.4.2) indicated that this is unlikely in South Africa specifically, doubting the value proposition of P2P lending in the South African context.

6.4.4.2 The presence of systemic risk elements

The data in in section 5.3.3.2 indicated that should maturity transformation be present at the level of the P2P lender, the P2P lender should be subject to liquidity requirements. The data in section 5.3.3.3 indicated that should leverage be present, the P2P lender should be obligated to meet capital requirements as well as liquidity requirements. Roulet

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and Blundell-Wignall (2013) confirmed that both leverage and maturity transformation are generators of systemic risk. Diamond and Rajan (2001) confirmed the same for the business of maturity transformation. Further, the data in sections 5.3.3.2 and 5.3.3.3 continued that the pooling of liabilities on balance sheet should result in the P2P lender being subject to liquidity and capital requirements. Diamond and Rajan (2001) contested that pooling has long been the business of banks. Pooling of liabilities creates room for maturity transformation to occur (per section 6.3.3.1) which is related to the restriction of liquidity (per section 6.3.1). Hence the data and the literature together led to the conclusion that the presence of these elements relating to systemic risk (which spreads through interconnected parties per section 5.3.2.1) at the level of the P2P lender prescribes that the P2P lender should bear liquidity and capital requirements akin to those of a bank.

Regards the discussion in section 6.4.1 on the role of the bank regulator. To the degree that lenders via P2P platforms have depositor type intentions, the literature and data deem that they should fall within the ambit of the bank regulator. This because it is a primary function of the bank regulator to protect depositors. Consequently, P2P lenders should bear liquidity and capital requirements. However, this argument does not disrupt the logic presented above, being that the presence of systemic risk components in the P2P lending industry should result in P2P platforms being subject to liquidity and capital requirements. The containment of systemic risk also falls within the ambit of the bank regulator. As concluded in section 6.4.1, some argue that depositor protection is ultimately in pursuit of systemic risk containment. As such, the lenders through P2P platforms behaving as depositors strengthens but does not dictate the stance that P2P lending platforms should bear liquidity and capital requirements where systemic risk components are present and P2P platforms are interconnected with the financial system.

6.4.4.3 Not banking requirements

An inductive finding in the data in section 5.3.2.6 was that investors should bear the liquidity and capital requirements themselves directly. This insight was in the context of a category one operating structure. As such, the data was supportive of liquidity and capital requirements in principle in the transactional equation but where the P2P lender is acting purely as a facilitator, the requirements should then rest on the lender. This implies that the lender in this instance would be behaving as an investor (not a depositor).

Lastly, a theme that arose through a combination of codes (sections 5.3.3.2 and 5.3.3.3) was that in the instances where P2P platforms should bear liquidity and/or capital requirements (conditional on the presence of certain elements), the requirements should

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not be identical to those that banks bear. P2P lenders should be governed by liquidity requirements of a different sort, designed to meet the types of risks that they pose. This concept connects with the general finding that P2P lenders should bear their own regulatory framework altogether. This emergent theme was (and remains) inductive in nature.

The data in section 5.4.2 related the concepts of P2P lending requiring regulatory oversight (including liquidity and capital oversight) with P2P lending requiring its own regulatory framework which onward connected with the notion that regulation can be stifling. Chaffee and Rapp’s (2012) view linked in here: stifling regulations led to the birth of P2P lending in the first place. This echoed with the data in section 5.4.2 which proposed that the application of banking regulations, specifically liquidity and capital requirements, will place severe strain on the business model of an online P2P lending platform. To the extent that P2P lending platforms in other jurisdictions were born outside of the bank regulated space because the regulations were overly stifling, moving P2P lenders back into that space may conclusively compromise the value proposition of P2P lending.

Banking regulations aside, the data sections 5.4.1 and 5.4.2 indicated that the issues of market conduct, the health and the longevity of P2P lending as an industry call for regulatory oversight. This is reinforced by Wei’s (2015) description of the civil protests in

China about the lack of appropriate regulatory oversight of an increasingly significant segment of the lending industry.

In closing to Chapter 6, there was considerable agreement between the data and the literature on key elements, many of which acted as building blocks for inductive concepts and emergent themes. It is these particularly that have furthered the body of knowledge on P2P lending: financial intermediation theory applies to P2P platform, the elements that contribute to P2P lending posing systemic risk in South Africa and that liquidity and capital controls have contingent application to P2P lending platforms in South Africa. Lastly, that it is the view of experts that P2P lending regulation should not necessialry mirror banking regulation.

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7. CHAPTER 7: CONCLUSION

Recall from Chapter 1 that it is the variation in regulation design for P2P platforms across financial markets (Chaffee & Rapp, 2012; Financial Times, 2014); the academic debate on regulation of P2P lending; the potential systemic risks posed by online P2P lending (Moshirian, 2011; Wei, 2015); and the growth of online P2P lending (Grant Thornton, 2015; Transparency Market Research, 2016) that together formulated the overarching rationale for the research. At the time of the research, there was limited literature on (a) whether or not liquidity and capital requirements (banking regulation) have application to P2P platforms and (b) online P2P lending in South Africa (refer to section 1.3). Qualitative exploratory research was undertaken to investigate the research problem: whether or not online P2P lending platforms should be regulated similarly to banks in South Africa with respect to liquidity and capital requirements. Here following, the principal findings are summarised which lead into implications for management, recommendations for future research and the limitations of the research.

7.1 Principal findings

In relation to the overarching research problem, two research questions were investigated. Their results of are addressed here first as they lead into the research problem.

7.1.1 Research question one: Are online P2P lending platforms behaving like banks?

The data and the literature agreed that financial intermediation theory can be applied to non-bank entities (Werner, 2016). The data found that financial intermediation theory applies specifically to P2P lending platforms due to the facilitation role that they play between borrowers and lenders. This has not been explicitly confirmed in P2P lending literature to date.

The data and literature agreed on a handful of determining factors that influence the debate on whether or not a P2P lender is behaving like a bank, being the involvement of the P2P balance sheet in the transactional equation (Roulet & Blundell-Wignall, 2013; Werner, 2016) and the pooling (aggregating) of assets and liabilities on balance sheet which in turn creates opportunity for maturity transformation (Diamond & Rajan, 2001).

Building on these determining factors, the data found that where a P2P lender involves its balance sheet or pools assets and liabilities (akin to operating structure categories two and three) then that P2P lender is more likely behaving like a bank. Where P2P

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lending platforms purely play an introductory facilitation role (akin to a category one operating structure), they are not behaving like banks.

An emergent theme that arose in the data (premised on theoretical elements in the literature) was the question of whether or not lenders transact through P2P platforms with intentions akin to a depositor or an investor. If the lender is acting as a depositor, it strengthens the argument that P2P platforms are behaving like banks, that systemic risk is present and that liquidity and capital requirements should be levied on the P2P platform. This issue appeared across multiple discussions on the research questions and the research problem, evidencing its place in the logic arguments relating to bank behaviour and the role of the bank regulator. The author views this as a key area for future research: ascertaining whether lenders having depositor or investor type intentions when transacting through P2P platforms.

7.1.2 Research question two: Do online P2P lending platforms pose systemic risk to the South African financial system, specifically in the absence of liquidity and capital regulation?

The data and literature concurred on certain generic components that contribute to systemic risk in a financial system, namely interconnectedness between the participants in a financial system (Moshirian, 2012; Staum, 2012); maturity transformation (Diamond & Rajan, 2001; Roulet & Blundell-Wignall, 2013); the restriction of liquidity (which relates to maturity transformation) (Diamond & Rajan, 2001; Fernando & Herring, 2002); the presence of leverage (Roulet & Blundell-Wignall, 2013) and the mispricing of risk (Fernando & Herring, 2002).

The data and literature both confirmed that liquidity and capital requirements are effective tools to mitigate systemic risk (Bank for International Settlements, n.d.; Moshirian, 2011; Roulet & Blundell-Wignall, 2013), albeit imperfect ones.

Ultimately the data proposed that P2P lending does not presently pose systemic risk in South Africa but it could do so if the industry grows, P2P platforms are interconnected with the financial system and the systemic risk components (as above) are evident in the operating structures of the P2P platforms. These components include the involvement of the balance sheet in the transactional equation, the presence of pooling (related to maturity transformation) (Diamond & Rajan, 2001; Roulet & Blundell-Wignall, 2013), the restriction of liquidity (which in itself is a function of the size of the industry) (Diamond & Rajan, 2001; Fernando & Herring, 2002), the presence of leverage (Roulet & Blundell- Wignall, 2013) or the mispricing of risk (Fernando & Herring, 2002). The systemic risk components need not occur concurrently.

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Per section 6.4.4.2, the debate on whether or not lenders via P2P platforms act with depositor or investor type intentions does not detract from the finding that P2P lending platforms pose systemic risk when the abovementioned systemic risk components are present. As such, research question two was conclusively addressed.

The size of the industry of P2P lending in South Africa arose as a prominent factor influencing the debates on whether or not P2P platforms pose systemic risk and a sub debate thereof being whether or not P2P platforms restrict liquidity. This was at odds with the literature which focussed on the size of individual financial market participants in a financial system as opposed to the industry as a whole (Moshirian, 2012; Roulet & Blundell-Wignall, 2013). The restriction of liquidity was reinforced as a key component of financial distress (Foster, 1986; Fernando & Herring, 2002) and was further related to systemic risk through contagion (Staum, 2012).

The marriage between confidence and liquidity arose prominently in both the literature (Fernando & Herring, 2002) and the data, where they both support and threaten one another in financial distress scenarios. The latter can lead to a run on the bank.

The data argued equally for and against the effectiveness of exchange control as a reducer of systemic risk in South Africa. The literature commented on the justification for its implementation (Moshirian, 2011; Roulet & Blundell-Wignall, 2013) but did not confirm its effectiveness in South Africa.

7.1.3 Research problem: Should online P2P lending platforms be regulated like banks in South Africa, with specific respect to liquidity and capital requirements?

With the context of the above in mind (7.1.1 and 7.1.2), the research problem itself can be directly addressed.

The literature and data were broadly similar in confirming that P2P lending certainly requires some form of regulation to ensure its safety for consumers and the longevity of the industry (Chaffee & Rapp, 2012; Wang et al., 2016; Wei, 2015). However, a “Goldilocks” debate emerged from the data as to the right balance of regulation required: too little and systemic risk may breed (Moshirian, 2011) whilst too much may severely compromise the P2P lending business model.

Regards the responsibilities of the bank regulator, the literature and data together confirmed that depositor protection and systemic financial risk containment fall within its ambit. This again related to the question on whether or not lenders in P2P lending act as depositors or investors. If lenders act as depositors, P2P lending platforms fall directly

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within the ambit of banking regulation (Republic of South Africa, 2015). If lenders act as investors, the bank regulator’s involvement is a question of whether or not systemic risk exists. Per the second research question, this research clarified when P2P lending poses systemic risk. Nonetheless, literature supported the notion of some protective regulation for investors (Chaffee & Rapp, 2012) and data suggested that investors require a separate framework to ensure good market conduct, which is connected with the longevity of the industry. Lastly, the data suggested that it is also the responsibility of the bank regulator to guide the credit extension in the industry such that high-quality balance sheets are constructed. This had equivocal connection with Werner’s (2016) work.

Ultimately, in direct response to the research problem, the data proposed that the application of liquidity and capital requirements to online P2P lending platforms in South Africa is contingent on the involvement of the P2P platform’s balance sheet in the transactional equation (Werner, 2016), the presence of systemic risk components (driven by the operating structure) and growth in the P2P lending industry. The applicable systemic risk components include: the interconnectedness of the P2P lenders with the financial system (Moshirian, 2012; Staum, 2012); pooling of liabilities (Diamond & Rajan, 2001) (which creates room for maturity transformation); maturity transformation (Diamond & Rajan, 2001; Roulet & Blundell-Wignall, 2013) (which is related to restriction of liquidity); liquidity restriction (Fernando & Herring, 2002; Foseter, 1986) or the use of leverage (Roulet & Blundell-Wignall, 2013). The systemic risk components need not occur concurrently.

As such, a P2P lending platform playing only an introductory role (category one operating structure) should not be subject to any liquidity or capital requirements.

In line with the “Golidlocks” situation discussed above, the data suggested that although liquidity and capital requirements should have contingent application, they should not be identical to those dictated by banking regulation. This connected with the debate about a hybrid or unique regulatory framework for P2P lenders, which was considered by Chaffee and Rapp (2012) and Douglas (2016).

At the time of the research, the literature relating to both (a) the application of liquidity and capital controls to P2P platforms and (b) P2P lending in South Africa specifically was limited. As such, these findings contribute to the academic debate on regulating P2P lending platforms in both senses.

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7.1.4 Summary of principal findings

Table 20 summarises the key concepts that relate to the principal findings in turn relating to the research questions and research problem as presented in Chapter 7. Table 20 does not confirm the nature of the relationships between the concepts and the research questions but rather serves as a quick reference guide. The concepts listed on the right- hand side of Table 20 need not all apply to the respective research question simultaneously. Please refer to Chapters 6 and 7 for in-depth insight on each concept.

Table 20: Summary of concepts that relate to principal findings

Research question Related concepts drawn from Chapters 6 and 7 one and two (Please read in conjunction with Chapters 6 and 7 for depth) Research problem

Research question Financial intermediation theory one: Involvement of P2P platform balance sheet in transaction Are online P2P Pooling lending platforms Does lender via P2P platform have depositor or investor behaving like banks? intentions?

Research question Not now but could if industry grows, P2P platform balance two: sheet involved and systemic risk components are present: Do online P2P lending Interconnected platforms pose Pooling, maturity transformation, restriction of liquidity

systemic risk to the Leverage South African financial Mispricing of risk system, specifically in the absence of Category one operating structure does not pose systemic liquidity and capital risk regulation? Liquidity and capital requirements are effective

P2P lending industry requires regulation Bank regulator role includes systemic risk containment

Research problem: Apply liquidity and capital requirements if industry grows, Should online P2P P2P balance sheet involved and systemic risk components lending platforms be are present: regulated like banks in Interconnected South Africa, with Pooling, maturity transformation, restriction of liquidity specific respect to Leverage liquidity and capital requirements? Should be different to liquidity and capital controls in banking regulation Category one operating structure does not require liquidity and capital controls

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7.2 Implications for stakeholders

Both start-up and existing P2P lending businesses in South Africa may extract value from the findings when considering how best to structure their operations in the context of the regulatory environment. Should they remain primarily category one type operating structures, the risk that they run of encountering liquidity and capital requirements is deemed low. Further, the insight on how P2P lending platforms have evolved in various jurisdictions may provide P2P platform management teams with context on the development of the global industry and the various shapes into which P2P lending could morph in South Africa given growth trends (Grant Thornton, 2015; Morgan Stanley, 2015; Transparency Market Research, 2016). Lastly, P2P platform business management may draw insights regards the risks that P2P platforms pose both in the systemic sense and also with specific regard to the quality of the loan books that they construct. This knowledge may feed into loan origination and/or risk management frameworks for the business. This is relevant in the context of losses that have been suffered by both consumers of P2P lending and the P2P platforms themselves in various jurisdictions (Financial Times, 2015; Wei, 2015).

This research offers consumers (both borrowers and lenders) that transact through P2P platforms (both existing and future potential) insight into the various risks posed which may not necessarily be transparent at the outset of the transaction (Chaffee & Rapp,

2012; Chuang et al., 2016; Emekter et al., 2015; Wang et al., 2016; Wei, 2015). The balance sheet involvement and balance sheet activity of P2P lenders requires consideration. The research may prompt lenders to question their own transaction intention (deposit substitute seeker or risk-taking investor) and to thoroughly analyse the risk-reward formula presented by the transaction.

7.3 Limitations of the research

Because P2P lending platforms are relatively new in South Africa (RainFin, 2017) and occasions of financial distress are relatively infrequent, the author’s ability to consider the relationship between regulation, systemic risk and P2P lending in times of financial distress was limited to financial distress data relating to jurisdictions and theoretical principles. Should a period of financial distress relating to P2P lending platforms occur in South Africa in the future, data arising therefrom can be corroborated with this research.

The sample was restricted to South African skilled professionals in line with the restriction of the research scope to the South African financial market. The reasoning behind this was twofold: the unique regulatory mix prevalent to each jurisdiction (Roulet & Blundell-

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Wignall, 2013) and the potential effects of exchange control on systemic risk in South Africa (Republic of South Africa, 2016). However, the literature and data yielded relatively broad insights that the author considered relevant to other market contexts.

The author did not have access to certain data of privately owned P2P lending platform businesses across jurisdictions, including financial statements and data on the P2P loan books. Such data would have allowed for accurate in-depth comparison of the accounting treatment of P2P loans and related obligations on the balance sheets of P2P platforms across jurisdictions as governed by various regulatory schemes.

The ability to source suitable skilled professionals for the sample was largely reliant on publicly available data and the author’s own extended professional network in Johannesburg. As discussed in Chapter 4, the sampling method was not random.

7.4 Suggestions for future research

Emergent themes arose from the research as derived through a dual deductive-inductive process. These emergent themes open the door for further debate. Primarily, the issue of the intention of lenders transacting via P2P platforms: do they seek a deposit substitute or an investment (sections 6.1.3 and 6.4.4.2)? This question will allow for the complete addressment of the first research question on whether or not P2P lending platforms are behaving like banks. Although the research yielded insight relating thereto, the evidence was not conclusive. This also feeds into the debate on the bank regulator’s role and whether or not it should administer P2P platforms (section 6.4.1).

Room exists for a quantitative analysis comparing the systemic risks posed by P2P platforms that do and do not adhere to liquidity and capital requirements. Although this may be premature at present, the application of banking regulation to P2P lenders in certain European countries (Germany, France and Italy (Grant Thornton, 2015)) and the recent applications for banking licenses by a handful of significant P2P lenders (Hosking, 2017) infer that such a comparison could be feasible in the near future.

Considering the main findings to the research problem, an emergent theme was that P2P regulation should not mimic banking regulation (section 6.4.4.3). The data suggested that although liquidity and capital requirements could have application to P2P lenders, such application should be different to that dictated by banking regulation. The author proposes that future research in this regard will continue the academic debate as to the optimal regulatory scheme for P2P lenders, including a form of liquidity and capital adequacy.

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Lastly, indistinct inductive insight arose suggesting that P2P lending bears similarity with funds: legal vehicles established with the specific intention of pooling and investing investors’ money. The data in sections 5.3.1.1 and 5.3.3.2 relates hereto. This presents a different angle from which to consider the design of a regulatory framework for P2P lending. This relates to the debate mentioned above regards lenders’ intentions, where in this scenario the lenders’ intentions would undoubtedly be to invest.

7.5 Closing

In closing, the research found that it is unclear whether online P2P lending platforms consistently behave like banks but financial intermediation theory has application nonetheless. Online P2P lending platforms in South Africa do not presently pose systemic risk but they may do so in future should the industry grow and should certain systemic risk components be present. Liquidity and capital principles should be incorporated into the regulatory scheme for P2P lending platforms where the balance sheet of the P2P lending platform is involved and the presence of certain systemic risk components exists. These are emergent themes that were discovered through a deductive-inductive process premised on theoretical elements.

Online P2P lending is growing (Grant Thornton, 2015; Morgan Stanley, 2015; Transparency Market Research, 2016) and evolving (Chaffee & Rapp, 2012). The academic debate on precisely how to regulate these entities continues. This research addressed the specific application of liquidity and capital requirements to online P2P platforms in South Africa and in so doing contributed to the body of knowledge on regulating P2P lenders that will hopefully guide both academia and the industry as the issue progresses.

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9. APPENDICES

9.1 Appendix 1: Consistency matrix

Consistency Matrix

RESEARCH TESTABLE LITERATURE REVIEW LITERATURE DATA ANALYSIS QUESTION PROPOSITION (excluding commercial source often relating REVIEW COLLECTION to industry data and metrics) TOOL Dependent variable Independent Peer-to-peer Banking and Risk Qualitative Interview guide Qualitative variables lending regulation research and audio exploratory methodology recorder research design Should online P2P RQ 1: Are online Chaffee & Baltensperger Akerlof Creswell Interview guide Qualitative lending platforms P2P lending Rapp (2012) (1980) (1970) (2013) for in-depth exploratory be regulated like platforms behaving Chuang, Mo, Bernanke & Beaver Guest, Bunce semi-structured research. banks in South like banks? Chen & Ye Blinder (1988) (1966) & Johnson interviews. Thematic and

Africa, with (2016) Casu, Fernando (2006) Accompanied by summative specific respect to RQ 2: Do online Chuen & Teo Girardone & & Herring Mack, a cover letter content liquidity and P2P lending (2015) Molyneux (2002) Woodsong, and appendix to analysis of capital platforms pose Dapp (2014) (2006) Foster MacQueen, familiarise transcripts requirements? systemic risk to the Emekter,Tu, Diamond & (1986) Gust & interviewees through South African Jirasakuldech Rajan (2000, Moshirian Namey (2011) with the coding financial system, & Lu (2015) 2001) (2011, Miles, & research ahead process. specifically in the Iyer, Khwaja, Douglas 2012) Huberman of time. Utilised absence of liquidity Luttmer and (2016) Roulet & (1994) Interviews were ATLAS.ti and capital Shue (2009) Kashyap, Blundell- Morse (2000) audio recorded software. regulation? Namvar Rajan, Stein Wignall Saldana and transcribed (2013) (2002) (2013) (2015) into typed Wang, Shen & Moshirian Staum Saunders & transcripts. Huang (2016) (2011, 2012) (2012) Lewis (2012) Wei (2015) Phillips (1920) Stiglitz & Shannon Riordan Weiss (2005) (1993) (1981) Shenton

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Roulet & (2004) Blundell- Strauss & Wignall (2013) Corbin (1990) Sealey & Whitaker Lindley (1997) (2016) Tobin (1963) von Mises (1912) Werner (2016)

9.2 Appendix 2: Ratings for the referenced journals per the ABS Journal Guide 2015

Journal name Ratings (As listed under Referernces) AJG 2015 ABS 2010 ABS 2009 ABS-RI 2016

Quarterly Journal of Economics 4* 4 4 n/a American Economic Review 4* 4 4 n/a Journal of Accounting Research 4* 4 4 A* Journal of Finance 4* 4 4 A* Journal of Monetary Economics 4 4 4 n/a International Review of Financial Analysis 3 3 3 n/a Journal of Banking and Finance 3 3 3 A Quantitative Finance 3 2 2 B Applied Economics 2 2 2 n/a

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9.3 Appendix 3: Existing online P2P platform metrics

Metrics for selected online P2P lending platforms across jurisdictions (publically available data as at 2017 unless otherwise stated) US UK Europe Asia South Africa Prosper: Zopa: Bondora: PaipaiDai: RainFin: First P2P lender Founded in Estonia. China. Founded in Founded in US. USD 10 2005. Now 200 Founded in 2007. IPO in US in 2012. billion employees. 2008. for USD 200 million Originating cumulative Cumulative Cumulative in 2017 (Ren, R1 million loans to date lend total GBP loans to date 2017). in loans (Prosper, n.d.). 2.64 billion. 60 EUR 102 per day by 000 investors, million. end 2016 277 000 28,850 invest (Ziady, borrowers ors (Bondora, 2016). (Zopa, 2017). n.d.). Lending Club: Assetz Lendico: Renrendai: FlintFin: Founded in Capital: Austria, China. Founded in Establishe 2006. Now Founded in Netherlands, 2010. USD 2.4 d in 2016. employees 1000 2003. Switzerland, billion by end 2015 Commerci people. USD Cumulative Germany, (Alois, 2015). alised in 28.8 billion lend GBP 300 Brazil, South August cumulative million (Assetz Africa. 2017. In loans to date Capital, 2017). Founded in capital (Lending Club, 2013. 330 raising 2017). 000 phase (G. customers. Leeuw, EUR 100 personal million communic

cumulative ation, July loans to date. 2017). Bought by Arrowgrass British hedge fund, lending stalled (Lendico, 2017). SoFi: Funding Auxmoney: Ezubao: Founded in Circle: Founded in China. Defrauded 2011. USD 20 Founded in 2007. Now 1 million investors. billion 2010. Now has 120 Yuan 100 billion cumulative GBP 250 employees. (Ren, 2017). laons to date. million in 50 000 350 000 capital. investors, 82 registered Cumulative 000 members (SoFi, lend total GBP borrowers. 2017). 3 billion. 32 Cumulative 000 small lend to date businesses EUR 300 have million borrowed. 69 (Auxmoney, 000 investors 2017).

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(Funding Circle, n.d.).

Upstart: RateSetter: Funding Societies: USD 1 billion Founded in Indonesia. Raised cumulative lend 2009. GBP 2.1 USD 1.5 million in since 2014 billion funding by 2016 launch. Artificial cumulative (FinTech News, intelligence lend to date. 2016).. value Has a proposition Provision Fund (Upstart, n.d.). to cover unexpected losses (RateSetter, 2017). Peerform: ThinCats: WeLab Holdings: Founded in Founded in China / Hong 2010. Made 2011. GBP Kong. Founded in 4000 loans 248 million 2013. Raised USD since 2014. cumulative 160 million in (Peerform, lend to date. capital in 2016. 2017) (ThinCats, 2017) Pave: LendInvest: CreditEase / Founded in Founded in Yirendai: 2012. USD 22.3 2013. Provides China. Founded in million of lLoans financing for 2006. Covers 232 and 1,665 properties. Chinese cities and borrowers to Cumulative 96 rural areas.

date (Pave, lend to date Owns Yirendai: n.d.) GPB 1 billion IPO in US for USD for 2700 75 million in 2015 properties (Ren, 2017). Plans (buy, build or to buy USD 50 renovate) to million of loans the value of from Prosper and GBP 1.4 billion Avant (FinTech in 120 UK News, 2016). towns (LendInvest, n.d.). Avant: Crowdcredit: Founded in Japan. Reach 2012. USD 4 extends to Peru, billion issued in Cameroon, loans Estonia, Finland, cumulatively. Spain and Italy. 600 000 Founded in 2014. registered Cumulative loans customers to 2016 YEN 848 (Avant, 2017). million. Has USD 2.76 million in funding.

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Maneo: Japan. Founded 2007. Cumulative loans to date YEN 48 billion. 31 000 investors (FinTech News, 2016). 9.4 Appendix 4: Ethical clearance approval

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9.5 Appendix 5: Summary of sample containing interviewees’ metrics

# Position AT Transcript years Institution at Interv LA Specialist document Title Trade trade type (current institution Education Nature of P2P exposure iew S.ti skills name experi & previous) (current & date # ence previous)

Product development pricing, BsC Health Sciences, Product Strategy & Member of divisional 20- Bank strategy Bcom Honours Finance 1 Developer Mrs Banking 11 Product FinTech investigative Jun- (Treasury) execution, & Business _Bank developer business unit. 17 funding/liabilit Management y/liquidity management.

Credit Business Science, analysis, Actuarial Science market Head Head Banking, risk depth/awaren 23- Credit Bank Credit User of divisional FinTech 2 Mr management, 12 ess, balance Jun- Investment (Treasury) Investment investigative business unit. regulation sheet 17 s_Bank Portfolio Honours Degree structuring, capital efficiency.

Head Dr_Head Banking, Regulations, Investec PHD Maths, Masters Analysed from VC / PE 28- Insurance_ lending, risk Bank credit, 3 Dr 12 Life, ISI, Financial Economics point of view as a business Jun- Funds_Cre management, (Treasury) lending, Credit (cum laude) case. 17 dit_Bank regulation markets. Book

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Manco member

Head Liquidity, 30- Central Banking, risk Bank Central MBA, CFA, BsC Health Considered as investment 4 Mr 25 interest rate Jun- Treasury_ management (Treasury) Treasurer Sciences / Anaesthetist opportunity management. 17 Bank

Global Head: Digital 2017- Global FinTech & innovation, Business Science in IT Head strategy, 07-04 Banking, Financial Innovation Job mandate includes FinTech technology, 5 Mr lending, risk 16 Services s scouting for & analysis of Innovation product management group Previous: investment opportunities. _Financial management & Provincial Group / design / Honours degree 2017- COO for operations. 07-07 retail bank

Global Global

Chief Banking, Head: Strategy Financial Personal investment. Digital lending, risk Digital formulation BsC Computer Science, 05- 6 Mr 16 Services Scouting for business Officer_Fin management, (Chief and BTech IT, MBA Jul-17 group opportunities. ancial regulation Digital execution. Group Officer)

Insurance / Banking, CEO Life financial lending, Insurance_ Banking, services CEO Life credit, Analysed business case for 13- 7 Mr 14 Actuary, FIA, FASSA Financial lending group Insurance insurance, his firm. Jul-17 Group Previous: portfolio Bank management.

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Asset Equity capital manager Product markets, Business Science Founder_F (financial manager FinTech, Banking, risk Finance Honours, MBA inTech intermediary) digital, Consultant to institutional 17- 8 Mr management, 8 cum laude, Kellogg Consultanc investment equity investor in P2P. Jul-17 regulation Previous: School Management y products, FinTech Founder / Innovation consultancy; CEO advisory, bank innovation.

Strategy, WITS Business School business Banking, Co-founder PDM, Bphys Ed, Founded & runs a P2P 21- Mr 10 P2P lender development, lending & CEO Business Economics, firm. Jul-17 disruptive Co- Psychology founders technology. 9 CEO Technology COO_P2P development, Lender Co-founder operational UJ BSC Maths & Founded & runs a P2P 21- Mr Lending 20 P2P lender & COO management, Physics firm. Jul-17 business building.

Chief Investment Investment Finance, trust corporate Officer PHD Finance, BCom Dr_p.Head Banking, governance, LLB, Higher Diploma Business investment into 25- 10 Investment Dr lending, risk 25 Previous: risk Head Company Law, Masters P2P platforms. Jul-17 Bank management Previous: management, Corporate International Tax Bank investment Institutional management. Banking

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Global Global Head 2017- Head Digital Banking, 07-27 Financial WITS Business School Digital Banking, risk Operations lending, Exposed to business cases 11 Mrs 15 Services MBA, Executive course Operations management Previous: technology, for investment. group Singularity University & _Financial Head operations. 2017- Group Lending 08-01 team

Strategy, WITS Business School business Founder Masters in Management Lending, risk Founder & development, Founded & runs a P2P 28- 12 MD_P2P Mr 6 P2P lender Entrepreneurship, PDM, management MD sales, firm. Jul-17 Lender BCom Economics (PHD communicatio WIP) n.

Bank & University of London: financial Advised on the preeminent Prof_Direct Legal Aspects of Banking, market regulatory structure of 02- or FinTech Law firm, Director, International Finance, 13 Prof lending, 17 / 30 regulations, primary South African P2P Aug- Regs_Law academic Professor Harvard: Program of regulation product lender as well as other 17 Firm Instruction for Lawyers, development, alternative lenders. Stellenbosch: BA LLB1 FinTech.

Strategy, Founder Analysis of business funding, risk, 03- Director_Al Lending, risk Founder & model. Professional 14 Mr 10 Lender business Honours Finance Aug- ternative management director engagement with lending opportunity 17 Lending business networks. identification.

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Prof_Foun Founder & Strategy, der Chief portfolio Director Risk Asset Executive PHD Economics, Professional engagement 04- management, 15 Portfolio Prof management, 25 manager, Masters Commerce, BA with people working on Aug- investment Manager_I regulation academic Honours Economics P2P platforms. 17 Professor / opportunity nvestment lecturer scouting. Firm

MBA, Honours Business Senior Risk Senior IT Bank Informatics, MA Regulatory analysis & 07- Risk 16 Mr management, 12 Regulator Risk regulation, Strategic Foresight, IT oversight of global & local Aug- Analyst_R regulation Analyst FinTech. management, Financial P2P businesses & risks. 17 egulator Management

Established business CA(SA), HDip BDP Dr_CEO_F Banking, division to actively seek & Financial CEO & Banking, (Business Data 14- inancial lending, risk investigate FinTech 17 Dr 40+ Services Executive regulations, Processing), Aug- Services management, 2 2. opportunities for group Director investments MBA, WITS Honorary 17 Group regulation2 informational and potential Doctor of Commerce2 investment purposes.

Financial Financial Non-bank 14- Stability Stability financial 18 Ms Regulation 7 Regulator Masters Economics Regulatory oversight. Aug- Analyst_R Departmen intermediation 17 egulator t Analyst .

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9.6 Appendix 6: Cover letter template

Tamarin Floyd

[email protected] Phone: +27 (0)60 529 7025

 [Interviewee name] [Interviewee email address]

Good day [interviewee name], Hoping that this letter finds you well. I am conducting research in the field of Finance specifically on peer-to-peer online lending platforms. The research seeks to address whether peer-to-peer online lending platforms should be regulated like banks (with respect to liquidity and capital) in South Africa. This research will form the Research Project element of the MBA Programme I am presently completing at Gordon Institute of Business Science (GIBS), University of Pretoria. I work full time at Investec Bank Limited and have seven going on eight years of experience in the financial markets. My interest in peer-to-peer lending has been stimulated by the trends visible worldwide around FinTech and alternative lending. I would be most grateful if I could interview you. The interview will be semi-structured in nature guided by the questions in the attached interview guide. The data gathered in the interview will be analysed alongside data from other interviews to draw insights and conclusions on the research questions. The overarching research problem and key questions are summarized as:

• Research problem: Should online P2P lending platforms be regulated like banks in South Africa, with specific respect to liquidity and capital? • Research question 1: Are online P2P lending platforms behaving like banks? • Research question 2: Do online P2P lending platforms pose systemic risk to the South African financial system, specifically in the absence of liquidity and capital regulation?

Please find attached the interview guide, consent form (addresses confidentiality) and theory excerpts for your perusal prior to the interview. I expect that the interview will last an hour. Hoping that you are comfortable and available to partake. Please let me know two alternative dates and times that suit you, preferably within the next month. Thank you in advance for your participation and contribution to the body of research in the field of Finance. Tamarin Floyd Final year student, MBA Programme [Type the sender company name] [Date]

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9.7 Appendix 7: Consent form template

Interview Consent Form

Should online peer-to-peer lending platforms be regulated like banks in South Africa, with specific respect to capital and liquidity?

As pertaining to research by Tamarin Floyd, final year student 2017 at Gordon Institute of Business Science, University of Pretoria, contactable at [email protected] Supervised by Matthew Birtch contactable at [email protected]

Research overview I am conducting this research to investigate whether online peer-to-peer lending platforms are behaving like banks, whether they pose systemic risk and whether they should be regulated like banks with respect to liquidity and capital. This research is specific to South Africa given its unique mix of legislation and regulatory bodies. This research may add value as the industry is new and largely unknown. The peer-to-peer lending industry in South Africa grows may grow as its peers have done globally.

The questions we intend to address in the interview will be as per the interview guide provided. However, the questions are largely open ended and intended as discussion stimulants, not strict discussion tramlines. Please feel free to elaborate and digress. I anticipate that the interview will last an hour.

When reporting the data in the final research project, I commit to preserving the interviewees’ confidentiality as data will be stored and reported without identifiers.

Please contact myself or my supervisor regards any concerns or questions you may have.

Points of consent 1. I confirm that I understand what the research is about and have had the opportunity to ask questions. [initial] 2. I understand that my participation is voluntary and that I can withdraw at any time without giving a reason and without penalty. [initial] 3. I agree to take part in the research. [initial] 4. I agree to my interview being audio recorded. [yes or no, initial] 5. I agree to the use of a professional transcriber as selected and contracted by the author of the research for the sole purpose of transcribing (converting) the recorded interview audio into a typed script. [yes or no, initial] 6. I agree to the use of quotations without identifiers in publications. [yes or no, initial]

Name of participant: ……………………………. Signature: …………………………….

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Name of interviewer: ……………………………. Signature: …………………………….

Date: …………………………….

9.8 Appendix 8: Interview Guide

Interview Guide

Should online peer-to-peer lending platforms be regulated like banks in South Africa, with specific respect to capital and liquidity?

As pertaining to research by Tamarin Floyd, final year student MBA 2017 at Gordon Institute of Business Science, University of Pretoria, contactable at [email protected] Supervised by Matthew Birtch contactable at [email protected]

Please note that questions are specific to South Africa and its financial market / system. However, examples from and principles in other geographies / markets can be considered for analysis. Please make reference to the “Appendix to Interview Guide: Theory Excerpts” as required.

Population criteria

1. Are you in the trade of banking, lending, risk management or regulation? [list question] 2. How many years of experience do you have in your trade? [quantity question] 3. What are your qualifications? [open question]

4. Which firm do you work at? [open question]

5. What is your position at the firm? [open question] 6. What is your role at the firm? [open question] Please describe your job. [open question] 7. What are your specific specialist skills? [open question] 8. Have you had exposure to online peer-to-peer P2P lending platforms? [category question: yes or no] If so, please elaborate. [open question]

Data collection questions (Brief discussion to confirm the meanings of concepts referred to in questions below)

9. How do you define systemic risk in a financial system? [open question] What indicators exist that alert you to its presence? [open question] 10. In your view, are the systemic financial risks in South Africa largely contained within its own financial system given the exchange control regulation? [category question: yes or no] Please elaborate. [open question] 11. In your view, which functions should the bank regulator ensure? [category question: depositor protection, investor protection, systemic financial risk containment, none of the above, other] Please elaborate. [open question]

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12. In your view, does banking regulation on liquidity management mitigate systemic financial risk? [category question: yes or no] Please elaborate. [open question] 13. In your view, does banking regulation on capital adequacy requirements mitigate systemic financial risk? [category question: yes or no] Please elaborate. [open question] 14. In your view, are online P2P lending platforms behaving like banks? [category question: yes or no] Please elaborate. [open question] 15. Which of the following banking theories, if any, can be applied to online P2P platforms’ behaviour? [category question: financial intermediation theory, fractional reserve theory, credit creation theory, none of the above] Please elaborate. [open question] 16. In your view, do P2P lending platforms presently pose systemic financial risk in the financial system? [category question: yes or no] Does the operating structure of the P2P platform (consider the three broad categories) affect this? [category question: yes or no] Please elaborate. [open question] 17. In your view, do P2P lending platforms create systemic financial risk in the financial system such that they could they pose systemic financial risk in the future? [category question: yes or no] Does the operating structure of the P2P platform (consider the three broad categories) affect this? [category question: yes or no] Please elaborate. [open question]

18. Do you think that the systemic risk exists as a result of P2P lending activity but not at

the level of the online P2P lender? [category question: yes or no] Please elaborate. [open question] Might that imply that another party in the investment equation should be subject to liquidity and capital requirements? [open question] 19. Do you think that there is a fundamental difference between the risks posed to the financial system created by (a) banks (who guarantee depositors’ funds) versus (b) online P2P lending platforms (who facilitate the meeting of lenders and borrowers), considering each of the three broad categories for the P2P operating structure? [category question: yes or no] Please elaborate. [open question] 20. Do you think that online P2P lending platforms are restricting liquidity in the financial system? [category question: yes or no] Does the operating structure of the P2P platform (consider the three broad categories) affect this? [category question: yes or no] Please elaborate. [open question] 21. Do you think that online P2P lending platforms should bear similar regulation to banks with respect to liquidity requirements? [category question: yes or no] Does the operating structure of the P2P platform (consider the three broad categories) affect this? [category question: yes or no] Please elaborate. [open question]

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22. Do you think that online P2P lending platforms should bear similar regulation to banks with respect to capital requirements? [category question: yes or no] Does the operating structure of the P2P platform (consider the three broad categories) affect this? [category question: yes or no] Please elaborate. [open question]

9.9 Appendix 9: Appendix to Interview Guide

Appendix to Interview Guide: Theory Excerpts

Defining peer-to-peer lending

The term “peer-to-peer” shall be referred to as P2P throughout this paper. Where the author refers to P2P, she means in the context of an online lending marketplace. Reference to platforms shall mean any firm that offers P2P lending services primarily via an online mechanism.

A form of FinTech, Online P2P lending describes the online marketplace where lenders can transact directly with borrowers without prior relationships and without acting via an intermediary channel, which would ordinarily be a bank. It is a new way of connecting demand and supply for funds (Chuang et al., 2016). Traditional lending is defined as transactions where the lender is institutional. Critically, P2P lending excludes the institutional player (Chaffee &

Rapp, 2012).

Online P2P lending platform operating structures: three broad categories

P2P lending platforms across geographies have structured their operations in various ways. The author has categorised these broadly as follows:

1. Clients monies are ring-fenced (for example, RainFin in South Africa) The loan relationship exists between the lender and the borrower with the P2P platform effectively acting as a facilitation agent. For the interim stage during which the money leaves the lender but before it arrives at the borrower, the P2P lender arranges that monies from lenders are ring-fenced in off balance sheet trust accounts with a separate entity, ordinarily a bank (RainFin, 2017). The P2P platform may have a transactional account in its own name into and out of which monies are transferred to execute the lend or receive monies from clients. For the short period of time that lenders’ money passes through the P2P platform’s transactional account, the lender may be exposed to the credit risk of the P2P platform (in other words, if the P2P platform were to go into liquidation at that point, the lenders’ money would be part and parcel of the liquidation

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process). As such, the loan relationship exists between the lender and the borrower with the P2P platform effectively acting as a facilitation agent. OR 2. Securities issuance (for example, Prosper Marketplace in the US) Lenders invest in notes (regulated as tradeable securities) issued by the P2P platform, the repayment terms of which are contingent on the performance of selected borrower loans the P2P platform makes on the other side of its balance sheet. As such, the lender and the borrower do not share a direct legal relationship. The lender is exposed to the P2P platform’s credit risk as it is the note issuer (Prosper Marketplace, 2017). As such, the lender may find that he/she is exposed to both the ultimate borrower and the online P2P lending platform for the same piece of money. In this way, the balance sheet of the P2P lending platform is involved in the transaction between the borrower and the lender. However, to the extent that assets and labilities are matched on the P2P lender’s balance sheet, there is minimal maturity transformation and minimal leverage on the balance sheet of the P2P lender. OR 3. Investing in a portfolio of assets (for example, RateSetter in the UK) In this instance, lenders lend into a pool of loans selected and constructed by the P2P platform. The lenders have not self-selected the beneficiaries of their loans (RateSetter, 2017). The pool may exist on the balance sheet of the P2P lending

platform or in an off balance sheet vehicle. The elements of maturity transformation

(short term liquidity availability despite the longer dated maturity of the underlying loans), leverage or other forms of balance sheet complexity may exist.

Theories of banking

Financial intermediation theory proposes that banks and non-bank financial intermediaries do not act dissimilarly, collecting and lending out funds (Werner, 2016). Critically, financial intermediation theory likens all institutions that effect deposit taking and on-lending behaviour, be they banks or otherwise (Werner, 2016). This builds on early work by von Mises’ in 1912 in which he commented that those enacting the lending of money are bankers whilst those whose money is ultimately being lent (depositors) are merely capitalists (Werner, 2016). The theory was furthered over time by Sealey and Lindley (1977); Baltensperger (1980); Riordan (1993); Kashyap, Rajan and Stein (2002); Bernanke and Blinder (1988) and, more recently, Casu, Girardone and Molyneux (2006). This theory is presently fairly popular (Werner, 2016) and certainly provokes thought around the similarities between banks and P2P platforms.

Tobin (1963) commented specifically that banks differ from other financial intermediaries (which in the modern-day context may include P2P platforms) only due to the reserve

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requirements that they hold, the capital requirements that they need to meet and the interest rate ceilings which cap the rates chargeable on loans. Any financial intermediary adhering to similar regulations would behave in much the same way that banks do (Tobin, 1963). However, Werner (2016) continues that banks own the deposits they gain from clients and show them on the balance sheet as senior ranking liabilities whereas non-bank financial intermediaries (for example, stockbrokers) do not show their clients’ investments on their own balance sheets. This begs the question whether P2P lenders create liabilities on their own balance sheets when accepting funds from lenders.

Financial intermediation theory is countered by the fractional reserve theory which proports that beyond the financial intermediary role that banks play, the banking system as an aggregate creates money through multiple deposit expansion (Werner, 2016). Fractional reserve theory rests on the money multiplier effect: because each bank is required to place only a percentage of its total deposits with its central bank and can lend out the rest, if each bank does that one after the other acting on the same initial deposit, money is in fact created. However, this effect is reliant on banks acting collectively in the financial system (Werner, 2016). Per Phillips (1920), what is true for the banking system as a whole is not necessarily true for an individual bank. A prerequisite for the loans a bank makes are the deposits it gains (Werner, 2016).

By contrast, the credit creation banking theory proports that each individual bank can create

money simply through the process of lending. This theory is over a century old but has lost popularity amongst academics since the 1930s. The credit creation theory bears little similarity to either the financial intermediary or fractional reserve theories. It differs in that banks do not first need to gather deposits in order to lend; are not required to hold reserves; and that an increase in one bank’s assets does not imply an equal decrease elsewhere in the financial system. Instead, credit creation theory proports that banks create money out of nothing via credit extension due to their ability to extend more credit than deposits received (Werner, 2016).

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9.10 Appendix 10: Complete list of code super families, code families and codes

Super code family Code family (themes) (categories) Banking *Banks’ role Banking theory P2P Behaviour P2P Business *P2P outlook P2P risks Regulations *Reg views Bank regulator role Capital requirements Liquidity requirements Systemic risk *Systemic risk other Exchange Control Interconnectedness Leverage Liquidity P2P systemic Size

Families: List of Code Families and their Members Code Family Codes Code description / rationale

(where required) *Banks' role *Agency role Refers to the bank acting for its depositors when it selects investments. In P2P lending, the lender self selects investments. *Confidence Relates to the discussion on confidence underpinning the banking system. *Monetary policy enablement *Socio-economic role *Store of value *Transactional enablement *P2P outlook *NCA restricting P2P National Credit Act defines individuals as in SA credit providers, limiting the scope P2P lending to retail individuals. *P2P may not work in SA *P2P should bear diff regulation *Unsustainable business models *Reg views *Different reg framework for investors

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*Market self The risk and reward benefits shall discipline regulation investors, not regulators. *Moral hazard Having "skin in the game" leads to better risk decisions. *Regs for distinct Differentiate regulatory treatment for retail investor types individuals, institutions, etc. *Regulation can be stifling *Regulation lags The market plays out before regulation can be formed and implemented. *Sound system Regulaotry governance of the financial protection in SA system is strong in South Affrica. *Stifling regulation so Where regulation restricts a business banks take new risks avenue, banks pursue riskier avenues to continue earning high returns. *Systemic risk *Bubble in mkt The prices of assets in a certain market are other buoyed; fundamentally too high. *Mispricing of risk The differential in pricing between low and high risk investments narrows due to demand. Bank regulator role *Capital adequacy / The bank regulator should ensure sufficient quality B/S amounts of capital on banks' balance sheets and good quality, well managed investments. *Investors at risk for It is not the bank regulator's role to protect own calls investors; they make informed risk/reward decisions. *P2P requires The P2P lending industry requires

regulatio n to be safe regulation as a financial entity to ensure it does not damage the financial system or consumers. Depositor protection Per the literature. Investor protection Per the literature. Systemic risk Per the literature. containment Banking theory *Applies to non- An academic banking theory may apply to a banks non-bank entity. Credit creation theory Per the literature. Financial Per the literature. intermediation theory Fractional reserve Per the literature. theory Capital *Cap req are The presence of capital requirements on requirements confidence tool financial entities inspires confidence amongst depositors and investors. *If B/S complexity, If the P2P lender's balance sheet is should bear cap req involved in the transaction and it's complex, the P2P lender should bear capital requirements. *If leverage on B/S, If the P2P lender's balance sheet is should bear cap req involved in the transaction and it's leveraged the P2P lender should bear capital requirements.

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*Intention but not The intention of liquidity and capital reality liq / cap regs regulations was to mitigate systemic risk mitigate systemic risk but this has not played out in reality. *Investors should The lenders (not the P2P platform) should bear cap / liq req bear capital and/or liquidity requirements relating to the investment. Cap req don't mitigate systemic risk Cap req mitigate systemic risk Default risk Guarantees / In the context of the obligations of an entity. promises If x has a commitment to repay y, y is exposed to x's balance sheet. If B/S involved, If the balance sheet of the P2P lender is should bear cap req involved in the transaction, the P2P lender should bear capital requirements. Loss buffer Capital requirements act as a loss buffer for financial entities, such that their obligations to depositors and senior ranking investors are unaffected. P2P Cat I should A category one operating structure P2P bear cap req lender should bear capital requirements similar to banks. P2P Cat I should A category one operating structure P2P bear different cap req lender should bear different capital requirements to banks. P2P Cat I should not A category one operating structure P2P bear cap req lender should not bear capital requirements similar to banks.

P2P should bear P2P lending platforms should bear capital different cap req requirements of sorts but not similar to banks. P2P should not bear P2P lending platforms should not bear any cap req capital requirements. Pooling should bear If the P2P lender is pooling risks (either on cap req balance sheet or off), there should be capital requirements. Some P2P Cat's Some (not all) operating structure should bear cap req categories of P2P lenders should bear capital requirements. Exchange Control *Excon amplifies The presence of exchange control amplifies domestic risks the domestic build up / effects of systemic risk. *Export risk freely Exchange control doesn't limit how much foreigners can buy of South African investments, therefore South Africa exports risk wihtout restriction. *GFC had less The Great Financial Crisis of 2008 affected impact on SA South Africa relatively less than other nations. *Restrict risk import Exchange control limits how much South Africans can buy of foreign investments,

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therefore there are restrictions on inward risk. Makes no difference Exchange control does not restrict the build up / severity of systemic risk in South Africa. Mitigate systemic risk Exchange control does restrict the build up / in SA severity of systemic risk in South Africa. Plays a role, not only Exchange control partially restricts the build / primary up / severity of systemic risk in South Africa but other factors play a greater role. Interconnectedness *Loss through no Systemic risk may result in losses that arise action of own from being connected to the system, not from one's own risk decisions *Non-diversifiable The risks arising from systemic risk and being connected to the system cannot be reduced through portfolio diversification. Banking system Contagion / domino Systemic risk spreads to connected parties. effect Interconnected Leverage *Leverage amplifies The presence of leverage at an entity level risk or collectively in the financial system amplifies the effect of systemic risk. Leverage B/S The presence of leverage (gearing) on a balance sheet. Liquidity *Create liquidity P2P lending platforms create liquidity in the market. *Create liquidity for P2P lending platforms create liquidity borrowers specifically for borrowers in the market. *Funds flow through The funds associated with P2P lending flow banking system through the banking system anyway to effect P2P transactions. *Liquidity takes down The outright lack or lack of access to banks liquidity in times of financial distress is what ultimately causes banks to fail. *Listed notes offer A listed note which is a security offers more more liquidity liquidity than a bilaterally contracted loan. *Loss of confidence / When depositors and investors lose panic / run on the confidence in the banking system, they bank panic and all demand their funds at the same time. This is a run on the bank and may lead to a liquidity shortage at the bank. *Pool offers more When assets (and risks) are pooled liquidity together, it offers better liquidity due to the mix of underlying maturity dates and access options. *Restrict liquidity for P2P lending platforms restrict liquidity savers specifically for savers (lenders or investors). *Secondary mkt Secondary market trade of investments creates liq creates more liquidity in that market. Maturity Per the literature. Occurs when assets and transformation liabilities do not have matched maturity dates.

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Not restricting Online P2P lending platforms are not liquidity restricting liquidity in the market. Restrict liquidity Online P2P lending platforms are restricting liquidity in the market. Liquidity *If B/S complexity, If the P2P lender's balance sheet is requirements should bear liq req involved in the transaction and it's complex, the P2P lender should bear liquidity requirements. *If leverage on B/S, If the P2P lender's balance sheet is should bear liq req involved in the transaction and it's leveraged the P2P lender should bear liquidity requirements. *If promise liq then If a P2P lender promises to deliver on bear liq req certain liquidity terms, then it should bear liquidity requirements to ensure that it can deliver on those promises. *Intention but not The intention of liquidity and capital reality liq / cap regs regulations was to mitigate systemic risk mitigate systemic risk but this has not played out in reality. *Investors should The lenders (not the P2P platform) should bear cap / liq req bear capital and/or liquidity requirements relating to the investment. *Liq regs early The reporting ratios' associated with warning liquidity requirements serve as an early warning system if a bank is struggling with liquidity management; indicative of financial distress. *Liq req are a The presence of liquidity requirements on

confidence tool financial entities inspires confidence amongst depositors and investors. *Liq transformation If a P2P lender constructs maturity needs liq req (liquidity) transformation, it should bear liquidity requirements. Guarantees / In the context of the obligations of an entity. promises If x has a commitment to repay y, y is exposed to x's balance sheet. If B/S involved, If the balance sheet of the P2P lender is should bear liq req involved in the transaction, the P2P lender should bear liquidity requirements. Liq req don't mitigate systemic risk Liq req mitigate systemic risk P2P Cat I should A category one operating structure P2P bear different liq req lender should bear different liquidity requirements to banks. P2P Cat I should A category one operating structure P2P bear liq req lender should bear liquidity requirements similar to banks. P2P Cat I should not A category one operating structure P2P bear liq req lender should not bear liquidity requirements similar to banks.

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P2P should bear P2P lending platforms should bear liquidity different liq req requirements of sorts but not similar to banks. P2P should bear liq Online P2P lending platforms should bear req liquidity requirements similar to banks. P2P should not bear P2P lending platforms should not bear any liq req liquidity requirements. Pooling should bear If the P2P lender is pooling risks (either on liq req balance sheet or off), there should be liquidity requirements. Some Cats should Some (not all) operating structure bear liq req categories of P2P lenders should bear liquidity requirements. P2P behaviour *Deposit substitute The issue of whether investors see P2P lending as an alternative to deposits at banks; whether or not they are fully appreciative of the risk / reward differentials. *Disintermediation The notion that P2P lenders are disintermediating banks. *Disruption The notion that P2P lenders are disrupting the banking and / or lending, industry. *P2P is like If P2P lenders pool risks in off balance securitisation sheet vehicles, this is akin to a securitisation structure. *P2P like a fund If P2P lenders pool risks in off balance sheet vehicles, this is akin to a fund (unit trust).

*P2P not new, P2P lending is not a new concept. Similar existed in other forms business models have existed over time, for example stokvels and building societies. *Pooling & P2P loan If P2P lenders pool risks on balance sheet selection is like bank and select the investments on behalf of investors, this is similar to what banks do. *Shadow banking P2P lenders are associated with the concept of shadow banking: financial entities performing the business of banks but not regulated like banks. B/S involvement The balance sheet of an entity is involved in a financial transaction. Connect supply & demand for funds Intermediary P2P Cat I is not like a A category one operating structure P2P bank lender is not similar to / behaving like a bank. P2P like a bank Online P2P lending platforms are is similar to / behaving like banks. P2P not like a bank Online P2P lending platforms are not is similar to / behaving like banks. Some P2P Cat's are Some (not all) operating structure like a bank categories of P2P lenders are similar to / behaving like banks.

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P2P risks *Bad quality / high P2P lenders are building low quality loan risk loan books books that contain high amounts of risk *Binary outcome An investment in a P2P loan poses a binary outcome for the investor: the borrower will either pay the lender back or not. There are only two possible outcomes. *Data makes better Data driven credit selection tools credit decisions (algorithms) make better credit decisions than humans. *Diffs distribution P2P lending platforms offer an alternative channel for insto's method for institutions that are originating excessive amounts of risk to distribute that risk to other institutions, who are the key investors in the assets offered by the P2P platform. As such, P2P is not individuals lending to one another. *Diversification A portfolio of assets is less risky for an reduces risk investor due to the mix of risks involved. This reduces the binary outcome. *Double risk / CLN A category two operating structure P2P lender poses double the risk to the lender: the lender loses his/her money if the P2P platforms goes bankrupt or if the underlying borrower defaults. This concept is akin to a credit derivative called a Credit Linked Note, where through an investor is exposed to the credit risks of two entities. *Good quality loan P2P lenders are building good quality loan books books.

*Grow faster with P2P lending platforms will grow faster if insto's institutions invest in the assets offered as they have larger amounts of funds to spend. *High growth rate P2P lending platforms have displayed high growth rates globally *High risk underlying The nature of the underlying investments faciliated by P2P (largely being unsecured personal loans) is of itself a high risk investment. *Information Borrowers and lenders have imperfect or asymmetry incomplete information about one another leading to situations where people make ill informed investment decisions. *No state support Online P2P lending platforms do not have explicit or implicit support from the central bank in times of financial distress. *P2P growing on The business proposition for P2P platforms yield hunt has grown overseas as a function of the low interest rate environment hence investors seek new ways to earn higher returns. *P2P only lose In times of financial distress or default, the reputation in crisis P2P lender does not lose its own capital, only its reputation. It does not have "skin in the game".

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*Taking risk not Either through the operating structure of the aware of P2P lender or due to information asymmetry, lenders / investors are taking on risks that they were not aware of when they made the investment decision *Test in stress event The online P2P lending business model has not been tested in a time of financial distress. Lenders' inability to measure risk P2P systemic *If B/S involved then If the balance sheet of the P2P lender is systemic risk involved in the transaction, then the P2P lender poses systemic risk *Pooling creates The pooling of investments (either on or off more risk balance sheet) creates more systemic risk. Cat I is lower risk A category one operating structure P2P lender poses less risk (systemic and otherwise) than the other categories. No systemic risk from Online P2P lending platforms will not pose P2P in future systemic risk in the future. No systemic risk from Online P2P lending platforms do not P2P now presently pose systemic risk. P2P could pose Online P2P lending platforms could pose systemic risk in future systemic risk in the future. P2P less risky than Online P2P lending platforms are less risky bank to the financial system than banks. P2P poses systemic Online P2P lending platforms presently risk now pose systemic risk.

P2P riskier than bank Online P2P lending platforms are riskier to the financial system than banks. Size *Size of industry The absolute and relative size of the P2P lending industry / market. Even small players Relatively smaller financial entities in the financial system can still pose systemic risk. Size of player matters The relative size of financial entities in the financial system affects the amount of systemic risk that it poses.

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9.11 Appendix 11: Complete code list and frequency

Code Code family Total # interviews code in which usage code occurred *Agency role *Banks' role 2 1 *Applies to non-banks Banking theory 12 10 *Bad quality / high risk loan books P2P risks 16 6 *Binary outcome P2P risks 6 2 *Bubble in mkt *Systemic risk other 8 5 *Cap req are confidence tool Capital requirements 6 3 *Capital adequacy / quality B/S Bank regulator role 10 5 *Confidence *Banks' role 17 8 *Create liquidity Liquidity 12 9 *Create liquidity for borrowers Liquidity 14 9 *Data makes better credit decisions P2P risks 2 2 *Deposit substitute P2P behaviour 26 9 *Different reg framework for *Reg views 12 7 investors *Diffs distribution channel for insto's P2P risks 14 6 *Disintermediation P2P behaviour 9 7 *Disruption P2P behaviour 9 5 *Diversification reduces risk P2P risks 15 8 *Double risk / CLN P2P risks 5 3 *Excon amplifies domestic risks Exchange Control 7 4

*Export risk freely Exchange Control 1 1 *Funds flow through banking system Liquidity 1 1 *GFC had less impact on SA Exchange Control 12 11 *Good quality loan books P2P risks 1 1 *Grow faster with insto's P2P risks 2 2 *High growth rate P2P risks 7 1 *High risk underlying P2P risks 8 4 *If B/S complexity, should bear cap Capital requirements 3 3 req *If B/S complexity, should bear liq Liquidity 5 5 req requirements *If B/S involved then systemic risk P2P systemic 3 1 *If leverage on B/S, should bear cap Capital requirements 3 3 req *If leverage on B/S, should bear liq Liquidity 3 3 req requirements *If promise liq then bear liq req Liquidity 3 2 requirements *Information asymmetry P2P risks 5 4 *Intention but not reality liq / cap Capital requirements 6 4 regs mitigate systemic risk & Liquidity requirements *Investors at risk for own calls Bank regulator role 23 11

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*Investors should bear cap / liq req Capital requirements 3 3 & Liquidity requirements *Leverage amplifies risk Leverage 5 2 *Liq regs early warning Liquidity 1 1 requirements *Liq req are a confidence tool Liquidity 8 4 requirements *Liq transformation needs liq req Liquidity 5 4 requirements *Liquidity takes down banks Liquidity 8 4 *Listed notes offer more liquidity Liquidity 3 1 *Loss of confidence / panic / run on Liquidity 23 9 the bank *Loss through no action of own Interconnectedness 7 4 *Market self regulation *Reg views 14 3 *Mispricing of risk *Systemic risk other 4 1 *Monetary policy enablement *Banks' role 4 3 *Moral hazard *Reg views 10 5 *NCA restricting P2P in SA *P2P outlook 4 3 *No state support P2P risks 2 2 *Non-diversifiable Interconnectedness 4 4 *P2P growing on yield hunt P2P risks 6 5 *P2P is like securitisation P2P behaviour 11 6 *P2P like a fund P2P behaviour 8 6 *P2P may not work in SA *P2P outlook 11 4 *P2P not new, existed in other forms P2P behaviour 14 7

*P2P only lose reputation in crisis P2P risks 5 4 *P2P requires regulation to be safe Bank regulator role 44 12 *P2P should bear diff regulation *P2P outlook 29 13 *Pool offers more liquidity Liquidity 3 1 *Pooling & P2P loan selection is like P2P behaviour 5 4 bank *Pooling creates more risk P2P systemic 6 5 *Regs for distinct investor types *Reg views 3 2 *Regulation can be stifling *Reg views 23 14 *Regulation lags *Reg views 6 5 *Restrict liquidity for savers Liquidity 1 1 *Restrict risk import Exchange Control 6 5 *Secondary mkt creates liq Liquidity 4 3 *Shadow banking P2P behaviour 12 7 *Size of industry Size 42 14 *Socio-economic role *Banks' role 16 8 *Sound system protection in SA *Reg views 16 6 *Stifling regulation so banks take *Reg views 3 3 new risks *Store of value *Banks' role 14 9 *Taking risk not aware of P2P risks 5 2 *Test in stress event P2P risks 8 5

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*Transactional enablement *Banks' role 7 3 *Unsustainable business models *P2P outlook 19 8 B/S involvement P2P behaviour 29 12 Banking system Interconnectedness 14 8 Cap req don't mitigate systemic risk Capital requirements 3 3 Cap req mitigate systemic risk Capital requirements 21 17 Cat I is lower risk P2P systemic 11 8 Connect supply & demand for funds P2P behaviour 23 11 Contagion / domino effect Interconnectedness 18 11 Credit creation theory Banking theory 9 7 Default risk Capital requirements 10 7 Depositor protection Bank regulator role 37 15 Even small players Size 11 7 Financial intermediation theory Banking theory 22 16 Fractional reserve theory Banking theory 1 1 Guarantees / promises Capital requirements 26 7 & Liquidity requirements If B/S involved, should bear cap req Capital requirements 18 8 If B/S involved, should bear liq req Liquidity 9 5 requirements Interconnected Interconnectedness 44 14 Intermediary P2P behaviour 19 12 Investor protection Bank regulator role 3 3 Lenders' inability to measure risk P2P risks 20 9

Leverage B/S Leverage 25 10 Liq req don't mitigate systemic risk Liquidity 7 3

requirements Liq req mitigate systemic risk Liquidity 23 14 requirements Loss buffer Capital requirements 14 8 Makes no difference Exchange Control 11 5 Maturity transformation Liquidity 18 8 Mitigate systemic risk in SA Exchange Control 13 8 No systemic risk from P2P in future P2P systemic 10 4 No systemic risk from P2P now P2P systemic 49 17 Not restricting liquidity Liquidity 3 2 P2P Cat I is not like a bank P2P behaviour 7 4 P2P Cat I should bear cap req Capital requirements 1 1 P2P Cat I should bear different cap Capital requirements 5 5 req P2P Cat I should bear different liq Liquidity 7 5 req requirements P2P Cat I should bear liq req Liquidity 1 1 requirements P2P Cat I should not bear cap req Capital requirements 17 11 P2P Cat I should not bear liq req Liquidity 15 10 requirements

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P2P could pose systemic risk in P2P systemic 39 11 future P2P less risky than bank P2P systemic 8 7 P2P like a bank P2P behaviour 26 9 P2P not like a bank P2P behaviour 26 13 P2P poses systemic risk now P2P systemic 1 1 P2P riskier than bank P2P systemic 11 8 P2P should bear different cap req Capital requirements 5 4 P2P should bear different liq req Liquidity 5 4 requirements P2P should bear liq req Liquidity 3 2 requirements P2P should not bear cap req Capital requirements 9 5 P2P should not bear liq req Liquidity 7 3 requirements Plays a role, not only / primary Exchange Control 9 6 Pooling should bear cap req Capital requirements 4 4 Pooling should bear liq req Liquidity 3 3 requirements Restrict liquidity Liquidity 18 9 Size of player matters Size 34 11 Some Cats should bear liq req Liquidity 1 1 requirements Some P2P Cat's are like a bank P2P behaviour 6 4 Some P2P Cat's should bear cap Capital requirements 2 2 req

Systemic risk containment Bank regulator role 25 12

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9.12 Appendix 12: Summary of code occurrence across the sample subgroups

Sample group Academic Banking FinTech Lending Regulation Risk management Metrics per sample group # # # # # # # # # # # # (in brackets: # interviews interv intervi interv interv intervi intervi interv intervi interv interv intervi intervie in sample group) iews ews as iews iews ews in ews as iews ews as iews iews ews in ws as in % of in as % which % of in % of in as % which % of which group which of code group which group which of code group code code group occurr code code group occur occur occur ed (8) occur occur red red red red red (13) (5) (13) (9) (8)

*Agency role 1 20% - 0% - 0% - 0% 1 13% 1 8%

*Applies to non-banks 3 60% 7 54% 6 75% 6 67% 4 50% 7 54% *Bad quality / high risk loan books 2 40% 4 31% 2 25% 4 44% 1 13% 4 31%

*Binary outcome 1 20% 2 15% - 0% 1 11% 1 13% 1 8%

*Bubble in mkt 1 20% 4 31% 3 38% 3 33% 2 25% 3 23% *Cap req are confidence tool 1 20% 2 15% 2 25% 2 22% 1 13% 3 23% *Capital adequacy / quality B/S 2 40% 4 31% 3 38% 4 44% 3 38% 2 15%

*Confidence 2 40% 8 62% 3 38% 4 44% 3 38% 7 54%

*Create liquidity 2 40% 7 54% 6 75% 4 44% 4 50% 5 38% *Create liquidity for borrowers 3 60% 7 54% 7 88% 7 78% 2 25% 8 62%

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*Data makes better credit decisions - 0% 1 8% 2 25% 2 22% - 0% 2 15%

*Deposit substitute 2 40% 7 54% 5 63% 6 67% 4 50% 6 46% *Different reg framework for investors 2 40% 6 46% 3 38% 4 44% 2 25% 4 31% *Diffs distribution channel for insto's 1 20% 4 31% 4 50% 5 56% 2 25% 4 31%

*Disintermediation 3 60% 6 46% 2 25% 4 44% 4 50% 5 38%

*Disruption 2 40% 4 31% 4 50% 4 44% 2 25% 4 31%

*Diversification reduces risk 2 40% 6 46% 4 50% 5 56% 3 38% 6 46%

*Double risk / CLN 2 40% 3 23% 1 13% 3 33% 1 13% 1 8% *Excon amplifies domestic risks 1 20% 3 23% 2 25% 1 11% 3 38% 3 23%

*Export risk freely 1 20% 1 8% 1 13% 1 11% 1 13% - 0% *Funds flow through banking system 1 20% 1 8% - 0% 1 11% - 0% 1 8% *GFC had less impact on SA 4 80% 8 62% 5 63% 7 78% 5 63% 7 54%

*Good quality loan books 1 20% 1 8% - 0% 1 11% - 0% 1 8%

*Grow faster with insto's - 0% 1 8% 1 13% 1 11% - 0% 2 15%

*High growth rate - 0% - 0% 1 13% 1 11% - 0% 1 8%

*High risk underlying 1 20% 2 15% 1 13% 2 22% 2 25% 2 15%

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*If B/S complexity, should bear cap req 2 40% 2 15% 1 13% 2 22% 1 13% 3 23% *If B/S complexity, should bear liq req 2 40% 3 23% 1 13% 2 22% 2 25% 3 23% *If B/S involved then systemic risk - 0% 1 8% 1 13% 1 11% 1 13% - 0% *If leverage on B/S, should bear cap req 2 40% 2 15% 1 13% 2 22% 1 13% 3 23% *If leverage on B/S, should bear liq req 2 40% 2 15% - 0% 1 11% 1 13% 2 15% *If promise liq then bear liq req - 0% 2 15% 2 25% 1 11% 1 13% 1 8%

*Information assymetry 1 20% 3 23% 2 25% 3 33% - 0% 3 23% *Intention but not reality liq / cap regs mitigate systemic risk 1 20% 3 23% 2 25% 1 11% 3 38% 3 23%

*Investors at risk for own calls 4 80% 7 54% 5 63% 7 78% 5 63% 8 62% *Investors should bear cap / liq req 1 20% 3 23% 1 13% 3 33% 2 25% 1 8%

*Leverage amplifies risk 1 20% 1 8% - 0% 1 11% 1 13% 2 15%

*Liq regs early warning - 0% 1 8% 1 13% 1 11% - 0% 1 8% *Liq req are a confidence tool - 0% 3 23% 3 38% 4 44% 1 13% 2 15% *Liq transformation needs liq req 1 20% 3 23% - 0% - 0% 2 25% 2 15%

*Liquidity takes down banks 3 60% 4 31% - 0% 2 22% 2 25% 4 31% *Listed notes offer more liquidity - 0% 1 8% - 0% - 0% 1 13% 1 8%

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*Loss of confidence / panic / run on the bank 4 80% 9 69% 4 50% 6 67% 4 50% 6 46% *Loss through no action of own 2 40% 4 31% 3 38% 3 33% 2 25% 2 15%

*Market self regulation 2 40% 3 23% - 0% 1 11% 2 25% 3 23%

*Mispricing of risk 1 20% 1 8% - 0% - 0% 1 13% 1 8% *Monetary policy enablement 2 40% 2 15% - 0% 1 11% 3 38% 3 23%

*Moral hazard 2 40% 3 23% 2 25% 3 33% 2 25% 3 23%

*NCA restricting P2P in SA 1 20% 3 23% 3 38% 2 22% 1 13% 2 15%

*No state support - 0% 2 15% 1 13% - 0% - 0% 1 8%

*Non-diversifiable 1 20% 4 31% 2 25% 1 11% 1 13% 3 23%

*P2P growing on yield hunt 1 20% 3 23% 4 50% 5 56% - 0% 5 38%

*P2P is like securitisation 4 80% 5 38% 2 25% 4 44% 5 63% 3 23%

*P2P like a fund 2 40% 5 38% 2 25% 3 33% 4 50% 5 38%

*P2P may not work in SA - 0% 3 23% 2 25% 3 33% - 0% 2 15% *P2P not new, existed in other forms 2 40% 7 54% 5 63% 4 44% 3 38% 4 31% *P2P only lose reputation in crisis 1 20% 3 23% 2 25% 4 44% 1 13% 3 23% *P2P requires regulation to be safe 2 40% 10 77% 6 75% 7 78% 4 50% 9 69% *P2P should bear diff regulation 3 60% 9 69% 8 100% 8 89% 6 75% 9 69%

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*Pool offers more liquidity - 0% 1 8% - 0% - 0% 1 13% 1 8% *Pooling & P2P loan selection is like bank 1 20% 4 31% 1 13% 3 33% - 0% 2 15%

*Pooling creates more risk 2 40% 3 23% 2 25% 2 22% 3 38% 2 15% *Regs for distinct investor types 1 20% 1 8% 1 13% 1 11% 2 25% 1 8%

*Regulation can be stifling 5 100% 11 85% 7 88% 7 78% 6 75% 11 85%

*Regulation lags 2 40% 3 23% 2 25% 2 22% 3 38% 5 38%

*Restrict liquidity for savers - 0% 1 8% - 0% - 0% - 0% 1 8%

*Restrict risk import 3 60% 5 38% 1 13% 4 44% 3 38% 3 23%

*Secondary mkt creates liq - 0% 2 15% 1 13% 1 11% 2 25% 2 15%

*Shadow banking 2 40% 6 46% 3 38% 3 33% 3 38% 6 46%

*Size of industry 3 60% 10 77% 5 63% 6 67% 6 75% 10 77%

*Socio-economic role 3 60% 5 38% 3 38% 5 56% 5 63% 6 46% *Sound system protection in SA 3 60% 2 15% 3 38% 3 33% 4 50% 5 38% *Stifling regulation so banks take new risks - 0% 2 15% - 0% - 0% 2 25% 2 15%

*Store of value 3 60% 8 62% 5 63% 6 67% 5 63% 6 46%

*Taking risk not aware of - 0% 1 8% - 0% - 0% 1 13% - 0%

*Test in stress event 2 40% 4 31% 2 25% 5 56% 1 13% 4 31%

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*Transactional enablement 1 20% 2 15% 1 13% 2 22% 3 38% 2 15% *Unsustainable business models 4 80% 6 46% 3 38% 6 67% 5 63% 4 31%

B/S involvement 4 80% 7 54% 6 75% 7 78% 6 75% 8 62%

Banking system 4 80% 5 38% 3 38% 4 44% 5 63% 6 46% Cap req don't mitigate systemic risk - 0% 3 23% 1 13% - 0% 1 13% 2 15% Cap req mitigate systemic risk 5 100% 12 92% 7 88% 8 89% 8 100% 12 92%

Cat I is lower risk 2 40% 5 38% 4 50% 4 44% 3 38% 6 46% Connect supply & demand for funds 2 40% 9 69% 8 100% 7 78% 2 25% 8 62%

Contagion / domino effect 3 60% 9 69% 4 50% 4 44% 6 75% 6 46%

Credit creation theory 2 40% 6 46% 4 50% 2 22% 4 50% 5 38%

Default risk 2 40% 4 31% 3 38% 6 67% 3 38% 4 31%

Depositor protection 5 100% 11 85% 7 88% 8 89% 7 88% 10 77%

Even small players 4 80% 4 31% 1 13% 3 33% 5 63% 6 46% Financial intermediation theory 5 100% 11 85% 7 88% 9 100% 7 88% 11 85%

Fractional reserve theory - 0% - 0% 1 13% 1 11% - 0% 1 8%

Guarantees / promises 1 20% 6 46% 5 63% 4 44% 3 38% 5 38% If B/S involved, should bear cap req 1 20% 7 54% 5 63% 4 44% 2 25% 6 46%

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If B/S involved, should bear liq req 1 20% 4 31% 3 38% 4 44% 2 25% 3 23%

Interconnected 3 60% 10 77% 6 75% 7 78% 6 75% 11 85%

Intermediary 4 80% 10 77% 6 75% 7 78% 4 50% 8 62%

Investor protection - 0% 2 15% 1 13% 1 11% 1 13% 2 15% Lenders' inability to measure risk 2 40% 6 46% 5 63% 6 67% 4 50% 6 46%

Leverage B/S 3 60% 8 62% 3 38% 4 44% 4 50% 7 54% Liq req don't mitigate systemic risk - 0% 3 23% 2 25% 1 11% 2 25% 2 15% Liq req mitigate systemic risk 4 80% 10 77% 5 63% 7 78% 6 75% 10 77%

Loss buffer 2 40% 6 46% 3 38% 5 56% 3 38% 5 38%

Makes no difference - 0% 3 23% 3 38% 1 11% 2 25% 4 31%

Maturity transformation 3 60% 5 38% 3 38% 4 44% 4 50% 5 38%

Mitigate systemic risk in SA 3 60% 6 46% 2 25% 5 56% 3 38% 5 38% No systemic risk from P2P in future 1 20% 4 31% 3 38% 3 33% 2 25% 1 8% No systemic risk from P2P now 5 100% 13 100% 7 88% 8 89% 8 100% 12 92%

Not restricting liquidity 1 20% 1 8% 1 13% - 0% 1 13% 2 15%

P2P Cat I is not like a bank - 0% 2 15% 2 25% 1 11% 3 38% 2 15% P2P Cat I should bear cap req 1 20% 1 8% - 0% 1 11% 1 13% 1 8%

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P2P Cat I should bear different cap req 2 40% 4 31% 2 25% 3 33% 2 25% 4 31% P2P Cat I should bear different liq req 2 40% 4 31% 2 25% 3 33% 2 25% 4 31% P2P Cat I should bear liq req 1 20% 1 8% - 0% 1 11% 1 13% 1 8% P2P Cat I should not bear cap req 3 60% 7 54% 4 50% 7 78% 6 75% 8 62% P2P Cat I should not bear liq req 2 40% 6 46% 4 50% 5 56% 5 63% 8 62% P2P could pose systemic risk in future 3 60% 7 54% 3 38% 4 44% 5 63% 9 69%

P2P less risky than bank 3 60% 6 46% 1 13% 4 44% 3 38% 5 38%

P2P like a bank 4 80% 7 54% 3 38% 2 22% 4 50% 7 54%

P2P not like a bank 3 60% 8 62% 6 75% 8 89% 7 88% 8 62%

P2P poses systemic risk now - 0% - 0% 1 13% 1 11% - 0% 1 8%

P2P riskier than bank 2 40% 5 38% 4 50% 4 44% 2 25% 6 46% P2P should bear different cap req - 0% 4 31% 1 13% 1 11% 1 13% 2 15% P2P should bear different liq req - 0% 4 31% 2 25% 1 11% 1 13% 3 23%

P2P should bear liq req - 0% 2 15% - 0% - 0% 1 13% 1 8% P2P should not bear cap req 1 20% 4 31% 1 13% 2 22% 3 38% 3 23%

P2P should not bear liq req 1 20% 2 15% 2 25% 2 22% 3 38% 1 8% Plays a role, not only / primary 3 60% 5 38% 3 38% 4 44% 3 38% 4 31%

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Pooling should bear cap req 2 40% 4 31% 1 13% 1 11% 1 13% 3 23%

Pooling should bear liq req 2 40% 3 23% 1 13% 2 22% 1 13% 3 23%

Restrict liquidity 3 60% 6 46% 3 38% 5 56% 5 63% 6 46%

Size of player matters 2 40% 8 62% 7 88% 7 78% 4 50% 9 69% Some Cats should bear liq req - 0% 1 8% 1 13% - 0% - 0% 1 8% Some P2P Cat's are like a bank - 0% 4 31% 3 38% 2 22% - 0% 3 23% Some P2P Cat's should bear cap req - 0% 2 15% 1 13% - 0% - 0% 1 8%

Systemic risk containment 4 80% 8 62% 2 25% 5 56% 6 75% 9 69%

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