SECTOR REPORT

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- 42022631 bally, business models that have access to customers (BigTechs) (BigTechs) to customers access have that models business bally, 22- Finnovation - FinTech perspective 1) Payments, 2) Financing, Financing, 2) Payments, 1) perspective FinTech an immediate is space this within While Payments Others. 4) and a key emerge should in India (Paytm is which hotly contested opportunity, multiple see could Financing attractive. most the looks Financing leader), i succeeding players an SMB is space, initiate We team. management strong model and business attractive c to Access Key risks: stock. the on an Outperformer with coverage shifts. technology and competition (JanDhan, Aadhar and Mobile) should intensify the growth. India has has India growth. the intensify should Mobile) and Aadhar (JanDhan, in the adoption seen already 2023E. by 600m to expands base user internet as accelerate, will believe services financial India’s b dominated currently is which services, in financial space white Financing opportunity. a Rs20trn is alone SMB financing instance, For next over space FinTech in India’s opportunity a US$1trn be should alone in at US$500bn, another estimated in payments prospects with years, 5 our The view. e US$22bn to US$120bn over next 5 years. Niyogin a from segments broad sub 4 into it subdivided have and opportunity is a large addressable market that has attracted investments by venture capital (VC) funds both globally and India (total ~US$28bn in 2017). In been have space services financial in China’s BigTech’s and etc) Kabbage, currently. 69% touching payments for levels penetration with scaling, Glo been have (Square) advantage channel unique build to able are and/or - white of emergence the also see We thanothers. successful more that a Finvest) Bank, Apollo (Solaris lenders tech a service. as credit offer to companies driving FinTechData India’s shift by 63% to double (to penetration smartphone by led in FinTech, growth supported 2022E), affordable internet.by Moreover, Tax Service Network Goods and as such government the by initiatives J and platform) software unified a (creating IndiaStack (GSTN), technology of cost lower by complemented market, addressable services financial indiv on data delivery digital added and ourview, mustlook investors at business models have that the edge,distribution engagement. India’s FinTech industry being nascent, most players are unlisted. However, we like SMB Niyogin’s - model in this space and initiate coverage on the stock with an Outperform globally are scaling FinTechs India’s India’s to shift digitalthe economy has setin motion emergence the of ofnewtechnology drivers Key in set companies FinTech the space. digitalenabling ecosystem Doubling the are 1) of smartphone penetration (63%) expandingand 4G network, Infrastruc2) for digital delivery, and 3) adoption of e of 3) adoption and delivery, fordigital India Fin Aniket Pande [email protected] 91

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yr high/low (Rs) high/low yr - - 600 - - 1,200 1,800 6 FY19 Change in TP (%) TP in Change (%) CMP from Potential (%) change Earnings Target Price BSE SensexBSE Free float (%)

NIYOGIN IN IN NIYOGIN (%) Promoter holding (%) holding Promoter Price performance performance Price

1 6 Bloomberg code Bloomberg FY20 (Rsm Mkt (Rs Cap Shares CMP (Rs)

Stock data

Sector: Sector: BSE Sensex: 38243 Sensex: BSE 7 September 2018

2,400

[email protected] 91 Rumit Dugar For Private Circulation only. Circulation For Private India FinTech

4 | IDFC SECURITIES 7 September 2018

India FinTech

Financial Services - Ripe for disruption

• Direct Bank transfer system • Online savings platform • Mobile payments • Online asset management • Payment service provider / • Online only Bank Gateways • Investment services • Remittances • Market places Payments Savings/Investment

• Personal lending • Regtech • SME lending • Insurtech • Crowd funding (P2P) • Personal credit scoring • Transactional (white label) • Technology – Blockchain, banks Robotics Process Financing • Payday Loan Others Automation

FinTech attracting VC capital Subsegments seeing funding activity

Deal Value (US$ m - LHS) Deal Volume (RHS) 1 Insurtech 30,000 27,445 3,000 h 23,255 2 Lending 21,170 22,500 2,250 3 Payments

15,000 13,337 1,500 Area 4 Investment platforms

7,500 750 4,819 5 B2B FinTech 3,231 2,548 1,889 Technology Centric (AI + ML 0 0 6 2010 2011 2012 2013 2014 2015 2016 2017 + NLP + Blockchain)

China has scaled well Regulations evolving

Application % of internet users using the app Regulatory Sandbox Instant Messaging 93.0%

Search 82.8% Key Payments 68.8% Payments PSD2Europe Areas Online Banking 51.7%

Internet Financing 16.7% P2P lending Savings/Investment 8.7%

India to see strong smartphone growth India internet penetration

India Smartphone penetration Wireless Internet Subs (m) 29% 425 370 21% 312 17% 249

11%

5% 1% 2%

2011 2012 2013 2014 2015 2016 2017 2014 2015 2016 2017

5 | IDFC SECURITIES 7 September 2018

India FinTech

India dominated by Banks, but technology infrastructure offers opportunity

India’s digital lending opportunity IndiaStack Consent Layer 400 (US$ m) 350 Open Cashless Layer personal Data Source 300 270 IMPS, AEPS, Paperless Layer APB, and UPI 200 Presence-less Aadhaar e-KYC, 200 Layer e-sign, Digital 150 Locker 110 Aadhaar 100 75 Authentication 58 46 23 33 Supported by major reforms and policy interventions 9 14 0 Pradhan Aadhaar Goods and Unified Bharat Bill Mantri Jan eKYC Services Payments Payment Dhan Tax Interface System 2017 2012 2015 2013 2018 2016 2014 2021E

2019E Yojana Network 2022E 2023E 2020E

Reducing cost of delivery

Small ticket loans/MFI Savings account Wealth management

Loan Customer Break Customer Break even Addressable disbursement acquisition even acquisition investment market cost (Rs) cost (Rs pa) MAB (Rs) cost (Rs) portfolio (Rs)

20 1,800 60K 1,500 200K 3M

Physical Physical Physical

1/4th 1/6th 1/10th

Aadha Digital ar (Fintech) APBS 5 Based 300 10K 150 20K 30M

Consumer debt to GDP India MSME- Large underpenetrated market

(m) No of MSME in India 51.1 48.8 46.8 Total number 100% 42.9 44.8 of MSME 87% (51m) 79% No of >90% 57% current Penetration account 48% gap (40m)

25% 16% 11% No of MSME borrowers (4.5m) FY11 FY12 FY13 FY14 FY15 UK Total employees USA India Brazil China

Japan 96 101 106 112 117 (in m) Russia

Canada

6 | IDFC SECURITIES 7 September 2018

India FinTech

Niyogin Fintech: SMB-focused FinTech play

Large supply gap MSME growth

No. of MSMEs (m) 68.0 63.4

Potential addressable credit gap: Rs20.46trn 51.0

36.2 33.2 34.0 2.8 0.7

12.7 17.0 9.2

SCBs NBFCs Other Total Formal Total 0.0 Banks/Govt Supply Addressable Fourth All India Census NSS 73rd Round 2015-16 Institutes Demand of MSMEs, 2006-07

Business Model - Platformisation Opens room for collaboration

Ability to attract partners Banks

Hyperlocalise products

Niyogin FinTech Niyogin Service Platform Platform innovators Cross sell other financial products

Unsecured credit is the Product entry product innovators

Creates relatively asset-light model Room to scale

Equity Customers 1000+ 50,000 Goals Potentially assets light structure Partners FY19E 500+ 5000+ Disbursals • Securitisation US$25m+ US$500m+ Partnerships • Co-lending by Indian banks 2+ Beyond FY2021 50+ Solutions beyond credit 1 5+ • Alternate Funds

• Rising leverage - Debt

INITIATE COVERAGE WITH AN OUTPERFORMER RATING

7 | IDFC SECURITIES 7 September 2018

India FinTech

Contents

Investment Summary ...... 9 The Landscape ...... 10 Digital Economy and Implications ...... 14 Data – The new oil!...... 21 Rising role of BigTechs! ...... 24 Global financial services ripe for disruption ...... 27 Segments of FinTech ...... 30 VC capital investment in FinTechs ...... 39 FinTech progress in China ...... 44 An evolving regulatory framework ...... 51 Financing – A Case study ...... 56 Financing – A Case study ...... 56 Personal lending – A case study ...... 57 Savings/Investment – A Case study...... 57 Others – Regtech: Smartkarma – A Case study ...... 58 Others – Insurtech: Lemonade – A Case study ...... 58 India - Market structure ...... 59 India FinTech – A US$1trn opportunity ...... 84 Annexure ...... 92 Glossary ...... 106 Company...... 107 Niyogin Fintech ...... 108

8 | IDFC SECURITIES 7 September 2018

India FinTech

INVESTMENT SUMMARY

 The shift towards digital ecosystem is driving data advantage to internet-centric business models. We could see disruption to traditional models as customer engagement shifts to digital, with the emergence of business models.

 Entry of players in the US (such as Square, Kabbage etc in the USA) and Chinese BigTechs in financial services is an example of technology companies pushing customer engagement into new verticals. We also see the emergence of new models such as white- labeled tech lenders (Solaris Bank, Apollo Finvest) that allow all internet companies to offer credit as a service.

 Global investments by venture capital (VC) funds in FinTechs grew to ~US$28bn in 2017, spurred by high deal value in the US, UK and India. Digital payments and lending services attracted the most investment capital.

 Additionally, there is regulatory recognition for FinTech players across the world (even in India) with regulations such as PSD2 in Europe, sandboxes across markets and clarity around P2P lending in most markets.

 We think India is at the cusp of hyper growth in FinTech, led by smartphone penetration, which is expected to double to 63%.

 India’s data price affordability at 1.3% (ARPU/GDP per capita) is at similar levels to that of China from where the 4G LTE penetration took off. This, along with digital infrastructure initiatives by the government should drive market expansion.

 We see Financing alone within India’s FinTech space as a US$1trn opportunity over next 5 years, with prospects in payments estimated to be another US$500bn. The e-wallet transaction market is expected to grow from US$22bn currently to US$120bn in next 5 years.

 We have segregated financial services into 4 broad sub segments from an India FinTech perspective 1) Payments, 2) Financing, 3) savings/investments and 4) Others.

 Payments is an immediate opportunity in India with Paytm expected to emerge as a key leader in the category. Players such as Paytm could diversify and use their customer advantage beyond payments into other services such as savings/investments, e-commerce etc.

 Savings/Investment will have overlaps with payments players but there is room for specialized players such as Zerodha (discount broker) and marketplaces (PolicyBazaar) to create niche positioning in the space. Insurtech and Regtech are other two interesting sub verticals.

 However, Financing looks the most attractive, given the possibility of multiple players succeeding in this large addressable market.

 We initiate coverage on Niyogin, within the listed FinTech space, with an Outperformer rating and a target price of Rs250. Niyogin is an SMB-focused financial services platform player with an attractive business model and a strong management team.

9 | IDFC SECURITIES 7 September 2018

India FinTech

THE LANDSCAPE

Emergence of digital ecosystem has been the key driver for internet economy and new technology-centric business models. Technology- centric business models have been enabled by rising compute capacity, reduced prices of handheld devices, which is bringing greater number of people into the connected world. These factors coupled with Potentiality of Internet of Things (IoT) will enable connectivity of several more devices over the next 5 years, which will drive proliferation of business models, in our view.

 Smartphone and network technology evolution Apart from China, India The role of smartphone as a driver for internet uptake in markets has been remains the biggest and one of the key digital stories of the decade so far. Growth opportunities among the fastest have shifted, with home-grown mobile brands in the east having muscled growing smartphone their way alongside Apple and Samsung, resulting in the proliferation of markets globally available handsets, which led to the downward pressure on price. Apart from China, India remains the biggest and among the fastest growing smartphone markets globally. Mature European and North American markets have stagnated or contracted as a share of year-on-year global mobile purchases. There is a good reason for this – mobile adoption in these regions have reached a saturation point, given upwards of 90% internet penetration rates there and high smartphone ownership figures among these internet users.

Exhibit 1: Global mobile phone purchasers Exhibit 2: Percentage share of global purchasers % of internet users who purchased India North America Europe smartphones in past 6 months 45% 20% 40% 17% 38% 38% 15% 40% 16% 14% 14% 14% 13% 12% 35% 32% 10% 30% 30% 12% 10% 10% 10% 9% 13% 30% 11% 8% 10% 9% 25% 8% 8% 20% 4% 2012 2013 2014 2015 2016 2017 2012 2013 2014 2015 2016 2017

Source: Globalwebindex, Company Source: Globalwebindex, Company

We gather value that can be delivered on the wireless networks has been consistently rising with the advent of network technology and an improving device ecosystem. From a pure wireless voice capability, we have seen networks evolve to carry wireless data at near fixed broadband speeds. More importantly, we have already seen mainstreaming of these high-speed technologies such as LTE, with large markets like China and now India rapidly adopting these technologies. However, network capabilities continued to improve with the potential capability of IoT to connect not only humans, but even low power devices. This creates opportunities for new business models and growth opportunities for technology-centric companies.

10 | IDFC SECURITIES 7 September 2018

India FinTech

Exhibit 3: Value delivered on the telecom network has been rising with time

• High Speed • Video-On- • Video-On- Demand Demand • Video • Video Conference Conference • Streaming • Streaming • Streaming • Push-to-talk Music Music Music (PTT) • 3D Gaming • 3D Gaming • 3D Gaming • Customised • Faster Web • Faster Web • Faster Web Infotainment Browsing Browsing Browsing • SMS • Multimedia • Full motion • Full motion • Full motion • Voice mail Messaging Video Video Video • Caller ID • Web • Speech, • Speech, • Speech, • Conference Browsing Voice mail, Voice mail, Voice mail, Calling • Speech, SMS, Web SMS, Web SMS, Web • Speech Voice mail, Browsing, Browsing, Browsing, • Speech only (digital) SMS MMS, PTT MMS, PTT MMS, PTT

Late 1970s – 80s 1990s 1990s 2000s

1G 2G 2.5G 3G 3.5G 4G Analog network GSM GPRS, EDGE UMTS, WCDMA, EVDO Rev B, Wmax, LTE CDMA 2000 HSDPA, DVBDAB

Source: RIL, IDFC Securities Research

Exhibit 4: Global snapshot Internet Users: % of Devices and Connections Average Speeds Average Traffic per Population per Capita Capita per month

27.5 53.0 44% 58% 2.3 3.5 Mbps Mbps 12.9GB 35.5GB

2016 2021 2016 2021 2016 2021 2016 2021

Source: CISCO Visual Networking Index, IDFC Securities Research

 Rising population of Mobile-Only users All sorts of interesting new audiences have emerged as a result of emerging technologies/handsets. There are Mobile-First consumers, who see their handsets as their most important access point; then there are Mobile-Heavy consumers, who are reported to be spending four hours or more per day on their phones; and then there are Mobile-Only consumers, people solely dependent on mobiles as a gateway to get online. While Mobile-First users have alternate devices, interestingly, the Mobile-Only users present immense opportunities.

Exhibit 5: Percentage of Mobile-Only users between the ages 16 and 24 Country % of users Indonesia 60% Philippines 59% India 53% Mexico 51% Vietnam 46%

Source: global webindex, IDFC Securities Research

 Users moving towards advanced networks Ericsson forecasts 8.9bn We believe users continue to shift towards more advanced and capable mobile subscriptions by networks, as is visible from the large shift in mobile subscriptions from 3G the end of 2023E to 4G at the global level. Enhanced network coupled with improving handsets with bigger screens are rapidly creating a digital ecosystem for consumption of goods and services through the digital channel. Ericsson

11 | IDFC SECURITIES 7 September 2018

India FinTech

forecasts 8.9bn mobile subscriptions by the end of 2023E, of which, mobile broadband subscriptions is expected to touch 8.3bn during the period, accounting for close to 95% of all mobile subscriptions. The number of unique mobile subscribers is estimated at 6.1bn by the end of the forecast period.

Exhibit 6: Mobile subscriptions by technology (billion)

Source: CISCO Visual Networking Index, IDFC Securities Research

Number of smartphone Smartphone penetration continues to rise, driven by the increasing subscriptions is forecast at affordability of devices. At the end of 2017, there were 4.3bn smartphone 7.2bn by 2023E, with subscriptions, 95% of which were for 3G and 4G. The number of almost all for mobile smartphone subscriptions is forecast at 7.2bn by 2023E, with almost all for broadband mobile broadband.

Voice over Long Term Evolution (VoLTE) creates a foundation for interoperable consumer and enterprise communication services on different devices across LTE, Wi-Fi and 5G. As per Ericsson, several operators have started deploying VoLTE over cloud-based core networks from a cost-efficiency perspective. Network evolution builds on Network Functions Virtualization (NFV) and helps deliver complex services. These include several devices and phones sharing same number and service use cases such as IoT, augmented reality (AR) and virtual reality (VR) in a 5G context. Currently, there are more than 1500 VoLTE-enabled device models. Asia Pacific (APAC), led by India is expected to have a large chunk of 4G-VoLTE ecosystem.

Exhibit 7: VoLTE subscriptions by region (billion)

Source: CISCO Visual Networking Index, IDFC Securities Research

The value delivered on networks has been growing with time and technology generation and we believe a shift from voice to high-speed data will enable emergence of multiple internet/digital business models.

12 | IDFC SECURITIES 7 September 2018

India FinTech

 Rising data penetration led by Asia Developed markets are well underway on the data cycle and despite good data penetration, consumption continues to grow. Unlike the voice era, where traffic had a ceiling based on the user’s ability to talk and spare time for voice calls, data consumption carries no such constraints. Most of the consumption is now led by developed markets, primarily driven by network rollout. We expect this growth to further shift to emerging markets, as prices of devices reduce, and the first access to internet for a large chunk of the populace happens through smartphones.

Exhibit 8: Internet users (million) (m) 772 800

600 462 400 312 149 143 200 119 110 98 85 80 0 USA India Brazil China Japan Russia Mexico Nigeria Indonesia

Bangladesh Source: internetworldstats, IDFC Securities Research

Exhibit 9: Internet penetration (%)

120% 96% 93% 90% 76% 71% 65% 55% 54% 60% 50% 48% 34% 30%

0% USA India Brazil China Japan Russia Mexico Nigeria Indonesia Bangladesh

Source: internetworldstats, IDFC Securities Research

Smartphones generate Mobile data traffic continues to expand globally across all regions. 85% of total data traffic Superior device capabilities, affordable data plans and increase in data intensive content have been driving strong data growth and penetration across markets. We think the economic impact could be more profound on emerging markets like India, where citizens’ first experience of internet will be on a mobile device. According to Ericsson’s mobility report, smartphones generate 85% of total traffic.

 IoT connections expected to reach 3.5bn IoT is already seeing deployments in markets like China, and with fabless chipset players working on innovative chipsets, the market for cellular IoT connections is expected to expand sharply. As per Ericsson, IoT connections should touch 3.5bn by 2023E (0.7bn currently) with North Asia accounting for 2.2bn connections.

New massive IoT technologies are evolving such as NarrowBand-Internet of Things (NB-IoT) and Category M1 (Cat-M1) are taking off. These technologies effectively support a low power wide area network (LPWAN), which use cases built on an underlying LTE network.

13 | IDFC SECURITIES 7 September 2018

India FinTech

DIGITAL ECONOMY AND IMPLICATIONS

Digitalization encompasses a wide range of new applications of information technology (IT) in business models and products that are transforming the economy and social interactions. The digital shift is driven by rising smartphone penetration, improved wireless networks, cheaper compute/storage supporting data explosion and rapid adoption of newer technologies.

Exhibit 10: Drivers for digital consumption in place Expanding digital Increasing infrastructure technology adoption

Growing digital Unprecedented consumption data explosion

Source: IBM, Kalaari Capital, IDFC Securities Research

As per IMF digital sector Criteria that define digital transactions include 1) how the transactions are constitutes less than 10% made (digitally ordered, enabled or delivered), 2) what is transacted of most economies if (goods, services or data), and 3) who are involved (consumer, business or measured by value added, government). The expert groups’ current working definition of digital income or employment transactions includes products that are digitally ordered, digitally delivered, or platform-enabled.

Exhibit 11: Three dimensions of digital transactions Nature Product Actors (‘how’) (‘what’) (‘who’)

Digitally Corporations ordered Goods and/or Households Platform Services enabled Government and/or Non-profit Digitally Information/ Institutions delivered data Serving Households

Source: Fortanier and Matei (2017), IMF, IDFC Securities Research

14 | IDFC SECURITIES 7 September 2018

India FinTech

However, according to World Bank, measuring the size of the digital economy is a challenge, given the lack of consistent definition, as the internet platform spans across industries. As per International Monetary Fund (IMF), the digital sector constitutes less than 10% of most economies if measured by value added, income or employment.

Exhibit 12: Estimated size of the digital sector in the United States (2015) Product group % of GDP ICT equipment, semiconductors and software 2.8 Telecommunication and Internet access services 3.3 Data processing, and other information services 0.7 Online platforms, including e-commerce platforms 1.3 Platform-enabled services, (e.g., the “sharing economy”) 0.2 Total (with incomplete adjustment for double counting of output) 8.3 Conceptually not included in GDP, or missed for procedural reasons: Wikipedia and open source software 0.2 Free media from online platforms funded by advertising 0.1 “Do-it-yourself” fixed capital formation of online platforms 0.3 Output of MNEs attributed to tax havens 0.4 Total (with incomplete adjustment for double counting of output) 1

Source: IMF Measuring Digital economy report

Continued pick up in the digital ecosystem has also led to the rise in sharing economy. As per CNNIC, China’s sharing economy, integrated with social resources to provide services for users, boomed in 2017. Specifically, online car-hailing and shared bike as typical representatives of the sharing economy have been favoured. A survey indicates 30.6% and 28.6% penetration in online car-hailing and shared bike, respectively; the penetration of shared power bank was 12.5%; shared bed and breakfast and shared car with a penetration of 2.8% and 2.2%, respectively, had a niche market.

Exhibit 13: China's sharing economy

Online Car Hailing 30.6%

Shared Bike 28.6%

Shared Power Bank 12.5%

Shared Homestay 2.8%

Shared Car 2.2%

0.0% 9.0% 18.0% 27.0% 36.0% Source: CNNIC, IDFC Securities Research

 Time spent on the internet Millennials spending 223 One of the major implications of the shift to digital economy is the minutes per day on the incremental mind and time share that the internet is taking of users. We internet, implying 16% note that as users spend more time in the internet ecosystem, it would be CAGR over last five years imperative for companies to build channels for their goods and services within this ecosystem. As per Statista, the global average time spent on internet per day by millennial users has more than doubled over last 5 years with millennials spending 223 mins per day on the internet, implying 16% CAGR over last five years.

15 | IDFC SECURITIES 7 September 2018

India FinTech

Exhibit 14: Time spent on the internet Daily time spent on mobile by Millennial internet users (mins) 240 223

181 188 180 163 133 120 107

60

0 2012 2013 2014 2015 2016 2017 Source: Statista, IDFC Securities Research

Indians spend 3.22 hours Interestingly, Asian countries lead the daily consumption stats as regards per day on internet on time spent on the internet, with the Malaysia/Philippines at the top of the their mobiles chart. Faster mobile internet access could be one of the reasons why Filipinos spend more time on the internet compared to those in any of other 29 countries. The data we have looked at pertains to only the time spent on mobile devices to access the internet. The table below shows that mobile is the primary access device for internet in Asia, while western markets have their usage split between desktops and mobile devices. We expect markets in Asia, particularly India, to turn Mobile-First with a large percentage of Mobile-Only internet users. Device affordability, improving 4G population network coverage and affordable data tariffs are factors that would drive the change, in our view.

Exhibit 15: Time spent on internet on mobile devices by country Hours on Internet on a mobile device per day 4.5 4.1 3.6 3.6 3.5 3.4 3.4 3.4 3.4 3.6 3.2 3.0 2.7 2.3 2.2 2.0 1.5 1.4 1.8 1.2 0.9 0.6

0 UK USA India Brazil China Japan Saudi Arabia Mexico Canada Malaysia Thailand Germany Indonesia Argentina Singapore HongKong Phillippines Source: World Bank, IDFC Securities Research

As more consumers come While we have seen continued rise in time spent on the internet, we take a online, the cost of delivery closer look at where the users are spending their time. As per Statista, on of services should fall an aggregate basis, the top 3 categories where users apparently are spending time are 1) Email, 2) Videos and 3) Social media. Interestingly, online banking is among the top-10 most popular internet activities among consumers. In our view, for most other activities to be monetized, there needs to be a smooth payments mechanism. Additionally, as users get more comfortable with security and spend time on the internet, activities such as online banking will continue to gain momentum. This could be immensely relevant in India’s markets, where cost of customer acquisition and importantly, cost of delivery of a service through traditional banking channels has been high. As more consumers come online, the cost of delivery of services should fall. Additionally, these customers create a trail of data and behavior that could be used for credit decision making.

16 | IDFC SECURITIES 7 September 2018

India FinTech

Exhibit 16: Most popular internet activities on smartphone in 2HCY17 Most popular Internet activities on smartphone 2HCY17 Online banking 36% Streaming music 38% Sharing content 39% Instant messaging 43% Online Shopping 43% News 48% Watching Videos 52% Social media 54% E-mail 59%

Source: Statista, IDFC Securities Research

 Customer shift from offline to online has profound implications This rapid development of The world today is connected and mobile. With everything around moving technology, mass increasingly to digital, consumers are quickly adopting technology and adoption and increased benefiting from quick and easy accessibility to the online world. In accessibility, has triggered addition, as the adoption rate of smartphone and mobile devices a global shift in consumer accelerates globally, people demand ‘anytime, anywhere’ connectivity. behavior. This rapid development of technology, mass adoption and increased accessibility, has triggered a global shift in consumer behaviour. A new generation of consumers has emerged that are sophisticated, hyper- informed, always-mobile-connected, and actively use online platforms such as social media. These consumers have become accustomed to the high level of interactivity and responsiveness, ease of use and seamless experience offered by online platforms that exist today. As a result, they demand a similar experience from their interactions with companies, across both online and offline channels.

Rising online presence has 3 major implications for traditional businesses • Creates perfect information - Full transparency leads to rational decision making/ product selection • If activity is online, so must be the customer acquisition • Shift creates something very valuable – Data! Data! Data!

 Creates perfect information - Full transparency leads to rational decision making/product selection We think the biggest impact on consumers and businesses of internet on the go is greater customer access to information. Earlier, businesses such as banking, used cars, etc, benefitted from information asymmetry and customers weren’t able to make fair decisions, given limited access to information. However, the scenario is different today, with customers having full transparency and complete information about product/service of each competitor. The change, in our view, is a big shift and has compressed margins for some traditional businesses (ex-car dealership in the US) that, to an extent, survived on information arbitrage. Lack of information arbitrage also potentially increases the risk of churn for existing customers. Additionally, digital delivery of products or services continues to break channel barriers and thus introduces cost efficient competition.

We think this has led to the emergence of an online-centric business model that allows companies to compare, remove information asymmetry and buy the best/product service. This is particularly visible in success of price comparison or marketplace platforms across industries – travel, credit cards, loans, insurance marketplace platforms.

17 | IDFC SECURITIES 7 September 2018

India FinTech

The digital age and rise of online shopping have driven an unprecedented business model shift for consumer product manufacturers and retailers. Many traditional consumer businesses and new start-ups alike are moving away from shop-centric or geographically-focused models to ones that are customer-centric and virtually borderless.

Price and product The ‘path to purchase’ is a traditional shopping concept that has evolved information are two main significantly over the past decade due to the internet, digital innovation reasons why consumers and the subsequent rise of online shopping. Although digital revolution opt for online research hasn’t altered consumer experience of awareness, consideration, conversion and evaluation, the journey itself has changed. The consideration’ phase, where the buyer conducts product and company research, has consistently moved online. KPMG’s global consumer survey conducted in 2017 highlights online as the key driver with 55% of consumers researching and looking for online product reviews and 47% visiting the company website.

As per KPMG survey, price and product information are two main reasons why consumers opt for online research. This, in our view, could be a game changer and disruptive for certain products and industries that have been generating ROEs by capitalising on limited customer information.

Exhibit 17: What are customers researching

65% 61% 49%

Price Comparison Product information/ Online reviews with other retailers specifications

35% 16%

Product options Store inventory/ (e.g. color, size, style, etc) availability

Source: KPMG – Global online consumer report

Exhibit 18: Where are customers researching

26% 23% 55% 47%

Online search for reviews and Visited the company Visited physical stores to Spoke with my friends or recommendations website see, try or fit the product family about it Source: KPMG, IDFC Securities Research

18 | IDFC SECURITIES 7 September 2018

India FinTech

As users search more, we think that increasingly, customers look to equip themselves with the perfect information. This brings us to the big question, if customers are rational decision makers and are equipped with the perfect information, would they choose the product? We believe every business will need to question itself, time and again, to protect against impending digital disruption.

Businesses will need to We think that businesses will need to offer best in class products at offer best in class superior value to their customers with multi service and delivery channels. products at superior value In our view, 2nd tier products might struggle, as customers’ switching costs to their customers with reduce, propensity to churn rises, with every business assuming that the multi service and delivery customer is always equipped with the perfect information. channels A large number of 2nd Tier products is a common problem among banks, who offer a high number of products. Most of the products offered by banks are commoditised with mixed service experiences. It is impossible to believe that all banks are adequately resourced to deliver a complete suite of best-in-class products at the best value.

 Customer acquisition critical but will keep getting expensive A few decades ago, banks or enterprises seeking to grow their customer base, had a few tried-and-true options. They could run a promotion and give away a gift, opt for a mail campaign, or air TV ads, for example. Customers were predictable and more importantly, easy to find. Customers were still walking into malls, retail stores and bank branches regularly – thus, the touch point existed. This made it easier for companies to cross-sell new products and services to these customers.

A shift towards digital and increasingly away from the brick-and-mortar model has two big implications for both, traditional as well as internet companies.

• Customer acquisition will keep getting difficult • Customer acquisition costs (CAC) will keep rising

Given today’s dispersed landscape, finding potential customers is a challenge. However, customer acquisition is changing and changing fast, as customers spend majority of their time in the digital world. Customers no longer walk into branches or retail stores at the frequency seen earlier. In fact, if a customer walks into a bank branch today, it is probably more to address a grievance and definitely not the best opportunity for a bank to try and sell a loan. The sheer number of channels and platforms available to marketers has grown considerably, and with users spreading their time on internet across various portals, it is increasingly challenging to grab their attention. Finally, all this comes at a cost.

 Customer acquisition costs CAC is a metric that has been popular, along with the emergence of Internet companies and web-based advertising campaigns that can be tracked. CAC is an extremely important metric for both the company as well as investors, especially in the start-up internet ecosystem. While CAC is an important metric on an absolute basis, investors should also look at customer lifetime value (CLV) which measures a company’s ability to retain the customer and ensure multiple purchases.

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 CLV should exceed CAC in a short time Payments have huge For a business model to be successful, CLV has to exceed CAC in a short implications on CLV, time frame. Payments is perceived to be one of the areas, where frequency which in turn can impact can push up the CLV>CAC at a rapid pace. However, purely building in a the economics of the long gestation, CLV delivery can be detrimental to a business model, and business model itself mean very high burn rates. This could lead to funding mismatches, as investors run out of patience to deploy in CAC in the hope of eventually achieving CLV. Heavy CLV companies forget that the life time value (LTV) model does not create sustainable competitive advantage. Organic users typically have a significantly higher NPV, a higher conversion rate, a lower churn, and are more satisfied than customers acquired through marketing spend.

Most studies cite payments as a key hindrance, especially in the e- commerce space, resulting in several transactions being left incomplete. We have seen this play out in the Indian e-commerce sector too, where a number of transactions exploded with the introduction of cash on delivery (COD). In the subscription model again, unintentional cancellation of subscription due to payment failure is a common problem. Thus, payments have huge implications on CLV, which in turn can impact the economics of the business model itself.

Customer proximity, engagement, technology and knowledge As discussed, generating rising CAC, will continue to push companies to figure out ways to improve customer engagement to make sure they have greater retention rates and thus the ability to deliver on CLV much quicker.

 Emerging online models to drive re-engagement There exist multiple engagement vectors that companies use, ranging from subscription, flash sales in retail-centric models to loyalty in both retail and enterprise models. We are not a fan of flash sales model. In our view, if a company is to use ’unmatched deals‘ as a vector to gauge growth/CAC, there has to be a compelling reason to believe that the company (as a start-up) will continue to have a structural pricing advantage that cannot be matched by other larger scale players. Otherwise, it is an unscalable model, in our view.

 Subscription model picking up in India as well Long popular in low-COGS business (media such as Netflix or Spotify, SaaS software, information services like Care.com or PeopleSmart), other internet players are catching on to the subscription model. JustFab and BirchBox are probably the biggest examples to date, but others like Dollar Shave Club are knocking on the door. We have seen this model come through in the e-pharmacy space in India where chronic customers are encouraged to adopt the subscription model for their monthly medicines.

Ideally, we would like to look at models that can recover CAC within 12 months – at least in the subscription business. CLV should be about 3x CAC for a viable SaaS or other form of recurring revenue model. Most of the public companies like Salesforce.com, ConstantContact, etc., have multiples that are more like 5x CAC.

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Data – The new oil! Banks historically have had a natural advantage in the data world; they have more data per unit of revenue than any other industry. However, banks have invested in a limited way to enhance their big data analytics and their ability to process combined information set. As such, most banks have restricted their data sets and struggle with legacy technologies, even as consumer technology goes digital. We think some of the emerging market banks might be better positioned from a technology stack perspective, but we are not sure if all of them are building comprehensive customer scoring models using big data. In our view, most of them are still dependant on traditional credit bureau information.

 Emerging technologies impact customers The cost of compute and Emerging technologies across various layers such as data, analytics, front storage will continue to end customer experience and backend (infrastructure and operations) are fall with the adoption of transforming the customer journey or purchase of product and/or service. cloud Further, the technology allows companies (innovators) to offer customer- centric product and services rather than ‘one size fits all’ approach that legacy players have had. Also, infrastructure-based technology through Application Programming Interface (API) will reshape industries such as financial services. We are already seeing technology that enables operational excellence in the form of BOTS (A computer program designed to mimic the actions of a person) and Distributed ledger technology (DLT). Robust infrastructure-based technology, powered by data, including platformication, cloud-based services and open APIs will enable even smaller firms to offer innovative solutions.

Exhibit 19: Emerging technologies

Data-Focused Technologies Operational Excellence

• Analytics • Robotic Process Automation • Artificial Intelligence and • Chatbots Machine learning • Distributed Ledger Technology (DLT) • Sensor-based Technologies • Biometrics

Front-End Interface Infrastructural Enables

• Intuitive User Interface • Platformification • Gamification • Cloud • Augmented and Virtual Reality • Open APIs

Source: Capgemini, IDFC Securities Research

 The need to build memory and brain! Companies that use data across external and internal sources will be able to better deliver customer value and potentially use levers such as differential pricing, customised product, sharper credit risk assessment and reduce cost of delivery. Companies need to build memory and brain within their organisation that would allow them to manage huge amounts of data or data lakes (memory) and run analytics (brain) to draw information for quicker and accurate decision making. In our view, the cost of compute and storage will continue to fall with the adoption of cloud.

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 Big data – Critical to success Organisations need to Before the era of big data, the enterprise architect ‘only’ had to worry build-in complex data about the data and systems within its own data centre. However, over the architectures to process past decade there have been revolutionary changes to the way complex information information is being used by businesses and how data management platforms support the information available from modern data sources. Adoption of cloud and mobile influences continue to push outside the data centres of enterprises. The challenge is to maintain the data flows from multiple data sources. This implies that organisations need to build-in complex data architectures to process complex information. This will remain a key challenge for the traditional brick-and-mortar business models – and we think that pure technology-oriented or internet first companies will have lighter technology architectures that will drive better and faster decisioning at lower costs.

Exhibit 20: Complex data view

Source: IBM, IDFC Securities Research

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 Kabbage – Predictive analytics About Kabbage Kabbage Inc. is an online financial technology company based in Atlanta, Georgia. The company provides funding directly to small businesses and consumers through an automated lending platform. Kabbage’s small business product is a line of credit up to US$250,000, based on a number of data factors, which include business volumes, amount of time spent in the business, transaction volumes, social media activities, and the seller’s credit score. Kabbage uses big data and analytics to deepen customer engagement, which allows the company to build and pre-empt customer demand and service it.

Kabbage predictive analytics

Source: Company, IDFC Securities Research

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Rising role of BigTechs! In our view, as customers shift to the digital world, it will be more and more difficult to 1) acquire customers at reasonable costs, 2) retain these customers and 3) monetize the customers. In our view, certain companies (BigTech) such as FB, Amazon, Google, Apple, Whatsapp have built a solid customer base through their base products. Incrementally, we expect to see a lot of these companies bundle more product and services to their millions of customers, which would impede and eventually annex the territories of legacy providers such as financial services. We have already seen some of that play out in China. Bundling of products allows companies to extract more revenue/value from their existing customer/subscriber base and adds - a source of competition for legacy businesses.

 Expect BigTech’s penetrating into new areas BigTechs are now looking Diversifications, which seemed unrelated a few years ago, will likely change to expand their footprint over the next 3-5 years, as users continue to shift their time spent from in the financial services brick-and-mortar models to digital. Bundling will push companies that sector, leveraging their have customers and customer insights (Data! Data! Data!) into newer strength business areas, as they try and address customers’ multiple requirements.

BigTechs have been successful within their sectors and are now looking to expand their footprint in the financial services sector, leveraging their strength. As consumers begin to spend more time on the internet and turn digital, it is imminent that boundaries between industries would blur, particularly in consumer-focused sectors such as retail banking and insurance. BigTech customers have the customers and their attention in terms of time spent on the platform. If BigTech firms unconditionally cross financial services boundaries, the long-term impact could be momentous.

 BigTech dominant in China, India could be next BigTechs have redefined customer experience, which has had a profound impact on all sectors, including financial services. Although the BigTech phenomenon has been most strongly felt in certain China and Southeast Asian markets, we expect it to eventually become mainstream. Alibaba’s Ant Financial in China is a case in point; you could see this coming from the likes of Amazon, Facebook and Google in India. India is a large market for these BigTechs, as they already have a large English-speaking urban population as customers. We have already seen Google enter payments space in India.

Exhibit 21: BigTech advantage

Redefined Customer Experience

Innovative Products Economies and of Scale Services

High Bigtech High Customer advantage Operational Trust and Efficiency Loyalty

Personalize Vast d Offerings Customer Data

Source: Capgemini, IDFC Securities Research

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In China, FinTech players In China, FinTech companies managed to gain scale rapidly by leveraging are utilizing online-to- their existing large online user base or acquiring massive customer offline apps as gateways volumes through low-cost, high-reach means, such as funnelling customers to cross-sell financing, through reputable ecosystems. Beyond payments, FinTech players are investments, and utilising online-to-offline apps as gateways to cross-sell financing, insurance offerings investments, and insurance offerings. For example, travel site and app Ctrip collaborates with FinTech companies to offer consumer credit – to borrow for immediate trips and for investment to save for future trips in China. It works with online insurers to provide travel-related insurance.

Exhibit 22: China internet users moving towards financial products (m) 771.9 800

600 527

400

200 129

0 China Internet users China Mobile payment China Online wealth users users Source: CNNIC, IDFC Securities Research

Exhibit 23: China’s BigTech diversifying and gaining share (m) Monthly Active users 1000 889 800 750 600 600

500

250

0 Wechat Users Tenpay/Wechat Taobao Alipay Pay Source: CNNIC, Tencent, Oliver Wyman, IDFC Securities Research

 The Alibaba economy Alibaba’s execution is an Emergence of Alibaba’s economy and the company’s vision to enable example of how BigTech, businesses across the internet chain can be seen from its platforms that who have consumers, will straddle across segments such as entertainment, core commerce, local try and leverage their base services and financial services, apart from technology services (like cloud to drive value migration computing). Alibaba’s execution is an example of how BigTech, who have consumers, will try and leverage their base and move across industries to drive value migration.

Exhibit 24: The Alibaba economy

Source: Alibaba, IDFC Securities Research

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The biggest of the Chinese FinTech firms are aggressively creating multi- product platforms. Ant Financial, for instance, wants to embed its services into customers’ daily lives to raise the percentage of users with multiple products, and boost customer stickiness and generate ever more complete customer data in the process. Ant Financial is building an ecosystem that goes beyond financial services to encompass transportation, dining, medical services, and much more. Alibaba has already reaped initial successes, as measured by the speed of customer acquisition, with the period for a financial product within the Ant ecosystem to reach 100m users reducing from 31 months for insurance, down to 20 months for Yu’e Bao, then 11 months for Sesame Credit.

Exhibit 25: The Alibaba economy

Source: Alibaba, IDFC Securities Research

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GLOBAL FINANCIAL SERVICES RIPE FOR DISRUPTION

Financial services is always a large addressable market in developed and developing economies. Since 2008, at least in the developed markets, low interest rates, higher compliance and rapid technology shift has put this legacy market at the critical point in disruption. As the customer base began to push itself deeper into the digital economy, traditional firms found it challenging to quickly take advantage of mobility, Bigdata, cloud, etc. As per Mckinsey, 2bn individuals and 200m businesses in emerging markets lack access to savings and credit, creating a credit gap of nearly US$2.2trn.

 Gaps left by financial services firms led to the rise of FinTech FinTech can help bring Even in their existing avatars, large financial institutions could not down the cost of delivery completely address the entire market. If we pick an example of lending – substantially even in developed markets like the US, which has high credit penetration, a lot of small medium businesses (SMB) faced challenges in getting new credit. Further, the approach of legacy financial services firms centered around one-size fits all, and generally the product portfolio lacked customer centricity.

In our view, FinTech models can potentially bridge some of these gaps, both from a customer centricity perspective, i.e, creating products and services driven by customer demands. Further, FinTech can help bring down the cost of delivery substantially, as digital adoption allows companies to capitalise on technology to do so. FinTech companies are using this to innovate and disrupt almost every segment of financial services. We discuss these in the subsequent segments.

Traditional financial services firms have struggled around 5 key areas • Financial Inclusion • Customer experience • Increasing transparency • Security and compliance • Support through technology

Exhibit 26: Value drivers for FinTech

Source: KPMG, IDFC Securities Research

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Financial inclusion has been a major issue in most markets despite the existence of the financial services sector for long. While emerging markets face issues in terms of evolution, capital and cost of delivery, surprisingly, even in major developed markets financial inclusion remains a core issue.

FinTechs have One of the reasons is the high cost of ownership, which either stems from significantly reduced the fat fees that banks want to generate and/or high cost of delivery. This costs by providing effectively translates into high cost for a customer and is one of the services through reasons that prevents consumers from getting the product or services they innovative yet simple need. High cost incrementally leaves out a large segment of customers in ways poor financial situations. FinTechs have significantly reduced the costs by providing services through innovative yet simple ways.

Empowered by digital experiences offered by tech and retail players, customers have greater expectations around experience and engagement from the providers of financial services. FinTechs have been able to increase consumer confidence in financial services by providing products that are engaging and give more control to the customer. Apart from customer experience, simplified and targeted solutions for each customer segment again have helped drive FinTech penetration.

Transparency and compliance is another driver that has brought about changes in the financial services industry. For example, implementation of MIFID in Europe is changing the business model and the face of securities with the unbundling of research and trading. Additionally, technology can ease the burden of regulatory compliance with effective implementation of technological tools.

With a larger number of financial products available to customers and many purchasing more than one product, it has become more difficult to consolidate in a single place. A number of FinTechs are offering solutions that focus on organising financial products (for example, insurance policies or pension plans) in one place and using technology like AI to help customers identify gaps in their financial needs.

 FinTech’s provide the necessary technology support In digital age, consumers don’t have the time to manually monitor, search and collect information on their own. To address this, FinTechs have come to the aid of consumers and introduced digital platforms that address several of these issues, which range from linking bank accounts, spending patterns, robo advisory, etc. Certain FinTech’s are also helping traditional legacy financial services companies get more efficient in their customer support delivery or leverage technology to achieve operational excellence.

Types of Fintech However, not all FinTech firms are the same, as companies deliver a range of value propositions at the consumer level and enterprises. Capgemini, categorizes FinTech firms into three broad buckets – Enablers, Customer services, Value added.

Enablers – Fintech firms that provide technology-based offerings to traditional enterprises or other FinTech companies, like blockchain, data mining

Customer services – Fintech firms that provide financial services solutions directly to customers and/or distribute financial services offerings. They compete directly with banks.

Value added providers - Firms that provide value-added services to customers such as comparison of financial products, like online portals for insurance product comparison. They essentially become value-added digital distributors.

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Exhibit 27: Types of FinTech firms

FinTech firms that provide FinTech firms that provide technology-based offerings to financial services to customers or traditional firms or other help in distributing financial FinTech Firms. Eg., firms that services offerings. Eg., Neo- provide data mining services Banks or Challenger banks

Value-Added Firms Providers

Firms providing value-added services to customers such as comparison of financial products. Eg., online portals to compare insurance products

Source: Capgemini, IDFC Securities Research

FinTech companies are We delve a little deeper into key competitive advantages of FinTech more agile, improve companies over traditional players. As per the World Fintech report, customer experience, and agility, customer experience and product innovations are three key the modern technology advantages cited in favour of FinTech companies over traditional financial stack allows for an easier services players globally. In our view, FinTech companies benefit from integration building business models by leveraging new technologies from scratch, which eliminates the burden of legacy systems. As a result, FinTech companies are more agile, improve customer experience, and the modern technology stack allows for an easier integration.

Exhibit 28: Capgemini Survey on key competitive advantages of FinTech companies

More Agile due to Absence of 90.9% Legacy Systems Enhanced Customer 90.9% Experience

New Product Development 76.4%

Innovation in Existing 76.4% Products and Services

Cost Reduction 67.3%

Improved Data Management 56.4%

0.0% 25.0% 50.0% 75.0% 100.0% Source: Capgemini, IDFC Securities Research

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Segments of FinTech Financial services is a large opportunity and we have broken down financial services into 4 broad sub segments from a FinTech perspective. We have divided these segments based on market opportunity size, collaboration potential and cross-selling opportunity.

In our view, the 4 key segments within FinTech are: • Payments • Financing /Lending • Savings and Investments • Others – Insurtech, Regtech, Data Technologies

Exhibit 29: Segments of FinTech

FinTech

• Online savings platform • Direct Bank transfer system • Online asset management • Mobile payments • Online only Bank • Payment service provider / Gateways • Investment services • Remittances Payments Savings/Investment • Market places

• Personal lending • Regtech • SME lending • Insurtech • Crowd funding (P2P) • Personal credit scoring • Transactional (White Label) banks • Technology – Blockchain, RPA Financing • Payday Loan Others

Source: IDFC Securities Research

 Payments Digital payments is Digital payments is the FinTech megatrend that has been driven by 1) expected to increase to Rising mobile phone penetration, 2) Shift in customer experience, and 3) 18-24% by 2020E entry of internet economy players. Payments landscape has seen the entry of multiple players across the supply chain ranging from device manufacturers, telcos, internet giants and payment companies like Square, iZettle and Transferwise.

The payment FinTech spans a broad canvas ranging from payment processors, wallets, integrated point of sale (POS), close loop and peer-to- peer (P2P). BCG report has estimated the total value of global retail payments transactions at US$16trn in 2015, which is estimated to increase to US$21trn by 2020E. Further, proliferation of IoT could potentially accelerate expansion in the payments space. As of 2015, digital payments stood at ~ 8% of global retail payments market, which is expected to increase to 18-24% by 2020E.

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Exhibit 30: Payments

Source: BCG, IDFC Securities Research

 Financing/Lending – FinTech to push boundaries with technology Digital disruption has the As discussed in the previous sections, it is fairly clear, that digital potential to change the ecosystem will have a profound impact on financial services. This is already role and relevance of underway in markets like the US and China, which we believe will filter today’s banks through to other markets. That said, the impact of this on current players in banking is not as well defined. In our view, digital disruption has the potential to change the role and relevance of today’s banks, and simultaneously help them create better, faster, and cheaper services that make them even more essential part of institutions and individuals’ daily lives.

The current market lending landscape we see in most markets, especially in emerging markets, where most banks and NBFCs address only the super prime and prime customers in the income group. We attribute this either to lack of credit information and/or high cost of customer acquisition through traditional branch models. This is exactly where we believe FinTechs will continue to push boundaries with technology. The applications or players participating across different credit classes might vary with internet companies operating in the prime and near-prime segments, while P2P and payday loan companies in the sub-prime and below.

Exhibit 31: How players are addressing the market

Near Super prime Prime Sub-prime Thin filers prime

E-commerce affiliated finance companies Banks Offline consumer P2P finance lender Payday loan companies lenders Consumer finance penetration rate penetration finance Consumer

Personal income group

Source: IDFC Securities Research

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 Current state of Banking – US Banks have been ineffective in expanding their credit footprint beyond the super prime and sub-prime categories. This implies hyper competition, lack of differentiation and product commoditisation, which has widened the gap between large banks and other banks.

 QED’s view of banking revolution - Copernican leap in banking As defined by one of the premier venture capital (VC) investor in the US (QED), banks are going through the Copernican revolution in banking. That is to say, the share will get concentrated in the hands of best-in-class product providers as channel barriers break down with technology. As a result, we could see the emergence of 4 types of banking product delivery models – 1) Transactional Banks, 2) General Population Banks, 3) Vertical Banks and 4) Non-Bank players (Amazon, FB, Apple, etc).

QED's Model

Manufacturer Distributor

Transactional Banks Yes No

Genpop Banks Yes Maybe to general population for core product(s) Yes Vertical Banks to specific segments

Yes Non-Bank Players No to existing customers

Source: QED, IDFC Securities Research

Likely evolution of the banking system 2019 2020 2021 2022 2023 2024 2025 2026 2027

Next 1-3 years Next 3-6 years Next 6-10 years

Large banks partner with non- Transactional Banks gain scale as Several Transactional Banks are banks, setting themselves up to they serve smaller banks in powering the Banking ecosystem, offer Transactional Banking addition to non-banks capturing half of all economics services Banks choose to offer best-in- Battle for the customer intensifies – class products (own and third market share consolidates to best- party) or watch market share and in-class product manufactures and profitability erode distributors

Source: QED, IDFC Securities Research

Just in case: Copernicus was the first scientist to challenge the a priori notion that the Earth was at the center of the universe, also popularly known as the geocentric theory.

 Legacy success model of banks may not hold for all banks The legacy model of success for banks was that banks must offer and manage a complete suite of banking products (core banking, lending, payments, wealth management, etc.). Secondly, banks were expected to build capabilities to deliver services to customers from all segments (Retail, SMB, and Corporates) across channels. This needed infrastructure creation (brick-and-mortar) and investments in product portfolio, even though banks may not be the best at offering each of these products.

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Exhibit 32: Typical product portfolio of a bank – Is all of this best in class? Treasury Deposits Credit Capital Markets Investment Insurance Management

• Savings accounts • Credit cards • Receivables (cash • Financial risk • Estate settlement • Life insurance • Checking accounts • Mortgages services, lockboxes) management • Guardianship • Disability insurance • Debit cards • Home equity loans • Payables (checks, • Investment banking • Investment • Employee benefits wires • Prepaid cards • Auto loans • Debt capital markets management services plans (dental, • Merchant Services medical, etc.) • Certificates of • Lines of credit • Equity capital • Individual retirement • Payroll services markets account • Long-term insurance deposit • Equipment leasing • Liquidity sweeps • Institutional • Custody accounts • Property & casualty • Foreign currency brokerage • Trusts • Reinsurance • Tax services • ID theft protection • Securities • Short-term investments 300+ products across segments • Portfolio management (consumer, SME, and corporate) products

Source: QED, IDFC Securities Research

 Are banks losing the data advantage? Additionally, we conjecture if banks are losing the data advantage, as customers shift to the digital economy and companies such as BigTech know their customers much better than a typical bank. Additionally, some of these tech companies have efficient delivery models that capture the customer and address their product/services gaps at reasonable costs. Additionally, while a large product portfolio of the bank might work for few larger ones, the same cannot continue to be the business model for success incrementally.

 ROEs - Why has this changed so drastically? Banks, at least in the However, as customers shifted to digital ecosystem and incrementally developed markets, have spent more time online, banks, at least in the developed markets, have struggled to deliver ROEs struggled to deliver ROEs. We assign a part of it to low interest rates and de-leveraging. However, it would be fair to say that some of this could be because of plummeting relevance and/or margin pressures, as digital customers who are now equipped with perfect information, want best-in- class product and experience.

Exhibit 33: Landscape of the US banking industry $10 ~200 banks $8

C $6 WFC $4 Totalassets BAC (in Trillions USD) $2 ~500 ~3.3K banks banks ~1.3K JPM banks $0 >$1 TRN $5BN - 1TRN $1 - 5BN $100M -1BN <$100M Asset size

Source: QED, IDFC Securities Research

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Exhibit 34: ROE of US banks Exhibit 35: ROE of US banks by asset size

Big Banks Average ROEs Return on average equity (%) 18.0 9.0 15.6

13.5 8.0

9.0 7.6 7.0

6.0 4.5

5.0 0.0 >US$trn Wells Fargo

Exhibit 36: ROE of large banks 1997 to 2007 2010 to 2017 24.0 19.3 17.7 16.4 16.7 15.9 18.0 14.3 11.5 12.5 12.0 12.0 9.9 7.1 4.7 4.9 6.0 3.2 1.4 0.3 0.0 Corp Hsbc Bank Of America Chase Societe Holdings BankAg Barclays Deutsche Generale Citigroup Jpmorgan

WellsFargo Source: Bloomberg, IDFC Securities Research

Exhibit 37: US banks versus BigTech (Share price 2010-current) Sector Returns*(2010-2018) US Banks

JP Morgan Chase 292 Bank Of America Corp 200 Wells Fargo & Co 205 Citigroup Inc 207 European Banks

HSBC Holdings Plc 104 Barclays Plc 73 Societe Generale Sa 84 Deutsche Bank Ag-Registered 29 Big Tech

Amazon.Com Inc 1,501 Alibaba Group Holding-Sp Adr 191 Alphabet Inc-Cl A 465 Facebook Inc-A 607 Microsoft Corp 382

Source: Bloomberg, IDFC Securities Research. Note: * Rebased to 100

 SMB lending Access to financial products is also a problem for businesses. As per Mckinsey, at least 200m micro, small, and medium-sized enterprises (MSMEs) in emerging economies have none or insufficient access to credit. The gap between the amount of credit currently extended and the need of businesses is estimated at US$2.2trn. In our view, this problem is not only for very small businesses, but also spills over to MSMEs that are part of the 34 | IDFC SECURITIES 7 September 2018

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formal economy. Even in cases where business have access, either the products do not address or cater to their requirements or have very high collateral levels, as banks struggle to judge risks. Finally, all this translates into exorbitant interest rates.

Exhibit 38: Access of SMBs to credit

Advanced % of MSMEs unserved MSMEs unserved or MSMEs unserved or economies or underserved underserved by credit underserved by credit services (million) services (% of total MSMEs) <50 >70 Credit gap ($ billion)

Latin America Africa and Eastern Europe South Asia Southeast China Middle East and Central Asia Asia

52% 53% 51% 48% 51% 49%

27 35 11 35 39 51

$620B $528B $323B $170B $175B $338B

200 million $2.2 trillion total number of unserved or underserved MSMEs total credit gap

Source: Mckinsey, IDFC Securities Research

 Financing FinTech models At least 200m MSMEs in SMB lenders o emerging economies have Personal lending none or insufficient access o to credit White-labelled lenders o P2P & Payday for sub-prime o  SMB lenders – Room for collaboration While the common understanding is that FinTech will disrupt the legacy models, which we believe they will, we also see tremendous room for collaboration with existing lenders (banks). FinTechs don’t have an established brand and thus lack customer trust, capital and/or access to capital and expertise in regulatory compliances. Fintech address the shortcomings of traditional lenders and the latter address it for Fintech, which in our view makes the collaboration effective.

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Exhibit 39: Effective collaboration

Source: Capgemini

Regulators in some of the Regulators in some of the developed markets are also turning favorable developed markets are towards FinTech and traditional lender collaboration. In Europe, PSD2 also turning favorable regulation pushes legacy financial services players to open up their tech towards FinTech and systems and adopt application programming interfaces (APIs). traditional lender collaboration Exhibit 40: Collaboration model

Banks FinTechs 1 Effective Utilization of Data

Broad Customer Base Innovative Products 2 Rise of New Business Models Extensive Network Agility

APIs Customer-Centric Products and Regulatory Expertise Nimble Solutions 3 Services

Funding Capabilities Distinct Culture 4 Enhanced Customer Trust

Source: IDFC Securities Research, Capgemini

 Emergence of white-labelled lenders – AWS of lending? As we expect power to get transferred to the owner of customer experience, pure manufacturers must therefore become hyper‐scaled or hyper‐focused. The rise of platforms means incumbents can no longer rely on controlling both product manufacturing and distribution, allowing product distributors to leverage control of their customer experience and place pressure on manufacturers.

A B2B2X model White-labelled lenders are likely to emerge as the customer acquisition keeps getting expensive and the customer base/engagement moves towards non-financial tech companies. In our view, a B2B2X is an interesting and scalable model whereby lenders offer credit as a service to enterprises who own the customers and wish to offer financial service as a product (Ex- Apple wants to offer credit as a service). Do think of it like Amazon Web services (AWS) of lending.

Amazon Web services (AWS) is a good analogy of how transactional banks that specialise in specific service layers and core functionalities can create an impact. AWS is a proof of how well-managed back-end functionalities can generate a large profit pool potential. AWS has white- labelled transactional banks that don’t compete for end customers but focus on providing a strong back-end experience and generating varied products to suit customers.

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Exhibit 41: White-labeled transactional bank model White labelled Internet Cos Effective Utilization of Data Fintech

Open tech stack Customer Base Rise of New Lending Models Agile and Neutral Extensive Network

APIs Customer-Centric Products and Regulatory Expertise Customer data Services

Funding Capabilities Alternate data for credit Great customer engagement

Source: IDFC Securities Research, Capgemini

Exhibit 42: How AWS has scaled AWS Revenues (US$ m) 20,000 17,459

15,000 12,219

10,000 7,880 4,644 5,000 3,108

0 2013 2014 2015 2016 2017 Source: Company, IDFC Securities Research

Customers with non-bank players Rise of platforms means We expect customers to interact with fewer distributors in future, as incumbents can no longer market consolidates and major firms gain market share. The rise of rely on controlling both platforms means incumbents can no longer rely on controlling both product manufacturing product manufacturing and distribution, allowing product distributors to and distribution leverage control of their customer experience and place pressure on manufacturers.

Exhibit 43: Customer base of non-banks

87% >215MM 1.9BN 90MM share iPhone Active Amazon of search sold in 2017 monthly users Prime members

Content and Entertainment Social and Commerce and advertising and software distribution fulfilment

Source: Company, IDFC Securities Research

Exhibit 44: Acceptability of banking products from non-banks (%) 18-34 35-54 55+

Paypal

Google

Amazon

Apple

0 10 20 30 40 50 Source: Accenture, Company, IDFC Securities Research

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Incumbents in the US accelerating investments Banks in the US have been accelerating their FinTech investments across the value chain and segments.

Banks’ number of investment in FinTechs (US$ m) Total FinTech investment, 2013-2017 YTD 37

25

14

10

10

9

7

5

1

Source: CB Insights, IDFC Securities Research

 Goldman Sachs - Marcus and beyond Marcus by Goldman Sachs is an online platform that offers no-fee personal loans and high-yield savings accounts to consumers. Since the establishment of the Marcus brand, Goldman has been one of the most active acquirers of FinTech start-ups, having acquired 37 firms so far. Many of their investments in the most recent past focus on lending and POS, with additions of Nav, Better Mortgage and Neyber. At the end of 2017, Marcus had more than US$2.3bn in loans and US$17bn in deposits.

 Marcus offering PERSONAL LOANS • No fees • Fixed interest throughout life of loan

ONLINE SAVING ACCOUNTS • Rates higher than national average (~1.85%) • No transaction fees • Minimum $1

Goldman Sachs- FinTech investments

Source: CBS Insights, IDFC Securities Research

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VC capital investment in FinTechs VCs in FinTechs grew to FinTech has grown significantly in recent years with investments having ~US$28bn in 2017 peaked in 2015 and a significant pick up in deals in 2017. Global investment by VCs in FinTechs grew to ~US$28bn in 2017, spurred by high deal value in the US, UK and India. Digital payments and lending services attracted the most investment capital. Although growth in deal values moderated from 2013-2015, we note deal volumes continue to expand.

Exhibit 45: FinTech deal flow Deal value ($bn - LHS) Deal volume (RHS) 32 160 128 139 119 114 24 120 91 78 16 62 66 80

8 40

0 0 2010 2011 2012 2013 2014 2015 2016 2017

Source: KPMG, IDFC Securities Research

Exhibit 46: Global median venture financing size (US$ mn) by stage in FinTech

(US$ m) Angel/Seed Early VC Late Stage VC 25 21 19.1 20 15.4 16 15 10 8.5 10 7 7.9 5.5 4.3 5 5 5 2.8 3.1 2.6 3 1 1 1.5 0.6 0.6 0.5 0.6 0.7 0 2010 2011 2012 2013 2014 2015 2016 2017 Source: KPMG, IDFC Securities Research

Interestingly, corporate participation in all VC (CVC) deals globally continued to contribute to overall transaction volumes as also support aggregate capital invested. FinTech, in particular, stood out with CVC participating in 19% of all FinTech financings, as per KPMG.

Exhibit 47: Global venture activities in FinTech with CVC participation % of Total Deal Count 19% 20% 16% 14% 15% 11% 10% 10% 9% 10% 8%

5%

0% 2010 2011 2012 2013 2014 2015 2016 2017 Source: IDFC Securities Research

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In general, it seems that characteristic of the FinTech investors is changing as VC deal volumes at the early/angel stage has declined as the investments are moving to more mature stage. These signs indicate that both, FinTechs and investors have matured and incrementally, companies are looking for larger funding rounds to scale further. This is where we are seeing an uptick in PE activity, as the number of deals continues to escalate. As PEs have had the experience of owning and managing financial services assets, it justifies rising PE participation, as FinTech companies begin to gain scale. Further, as some areas such as lending need permanent access to capital, it could be a large opportunity for PE players.

Exhibit 48: Global PE activity in FinTech Deal value ($bn - LHS) Deal volume (RHS) 32 160 128 139 119 114 24 120 91 78 16 62 66 80

8 40

0 0 2010 2011 2012 2013 2014 2015 2016 2017

Source: KPMG, IDFC Securities Research

Exhibit 49: Sub segments seeing funding activity 1 Insurtech h 2 Lending

3 Payments Area 4 Investment platforms

5 B2B FinTech

6 Technology Centric (AI + ML + NLP + Blockchain)

Source: KPMG, IDFC Securities Research

FinTechs focused on the B2B market, including payments platforms, SME lending platforms and SaaS solutions aimed at making back office processes efficient and effective, which remains a priority for FinTech investors. Globally, many financial institutions face significant financial pressures and challenges, particularly related to regulatory reporting and compliance. With regulatory requirements only expected to rise in most jurisdictions, Regtechs are becoming key focus area for B2B investors and corporates.

Globally there are 29 Global FinTech M&A produced aggregate figures that compare favourably FinTech Unicorn’s valued to those of 2016, at 336 transactions completed for US$18bn in associated at US$84.4bn deal value. Consolidation is still a considerable driver of overall FinTech M&A, as financial services companies look to stay abreast of innovation and also increase potential synergies in the face of stiff competition from nonfinancial services startups.

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From a regional standpoint, Asia is on par and could likely surpass the US in FinTech deals in 2018, primarily driven by a spike in early stage deals, particularly in China. The explosive growth in China FinTech is further characterised by its relatively short maturity curve. For example, it took four years for peer-to-peer (P2P) transaction volumes to exceed US$5bn in the US, while the same took only two years in China. Lufax, a Chinese P2P lending platform founded in 2011, reached an annual loan origination amount of RMB9bn in just two years, compared with five years for Lending Club, the biggest P2P lending company in the US.

Exhibit 50: Capital invested from a VC in China versus global FinTech

US China Others

2016 4.6 6.4 2.6

2015 6 3.1 3.6

2014 3.9 0.5 2.3

2013 1.6 0.1 1.2

Source: OliverWyman, IDFC Securities Research

Exhibit 51: Global VC-backed FinTech companies with a private market valuation of US$1bn+

Source: CB insight, IDFC Securities Research

Exhibit 52: Most active FinTech VC investors (past 1 year)

Source: CB insight, IDFC Securities Research

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Exhibit 53: Select online lending venture financings VC financing Company name Type Lending focus Region size ($M) Kabbage 250 Series F SME US Dianrong 220 Series D P2P lending China Blend Labs 100 Series D Mortgage US Wecash 80 Series C Credit assessment China Residential solar Solar Mosaic 65 Series C1 US installations Creditas 50 Series C Consumer lending Brazil Younited Credit 47.7 Late Stage P2P lending France Smartkarma Innovations 13.5 Series B Regtech Singapore

Source: KPMG, IDFC Securities Research

Insurtech and Blockchain Both Insurtech and Blockchain saw strong VC investments through CY17. KPMG cites Insurtech’s VC deals at US$2bn in 2017, while blockchain investments at US$512m. Although the value is smaller compared with overall investments in the FinTech space of US$31bn, we note the number of deals are high. Importantly, corporate and PE participation in the sub segment has been expanding and total deals stood at 339 worth US$7.4bn during the period.

Blockchain had 92 VC Insurtech is both mature enough to experience a fair degree of M&A, but is deals in 2017 also fresh enough, as massive sums of VC still flow into the multiple new startups that are looking to tackle different niches in the vast insurance sector. Mature businesses, such as Lemonade, are looking to raise massive rounds, while deep-pocketed investment firms are more than willing to supply sums to the extent seen in 2017, which saw a new record total both in terms of deal value and volumes.

Exhibit 54: VC, PE and M&A activities in Insurtech Insurtech Deal value (US$bn - LHS) Insurtech closed deals 14.0 400 339 299 10.5 300 236 270 186 7.0 153 200 134 103 3.5 100

0.0 0 2010 2011 2012 2013 2014 2015 2016 2017

Source: KPMG, IDFC Securities Research

Exhibit 55: Insurtech deals by region (%) Latin America Middle East, Africa, Russia & Turkey Asia Pacific Europe North America 100% 1.8 0.7 2.1 2.7 5.5 0.9 4.6 4.2 8.6 7.6 11.8 12.6 11.5 75% 23 20.6 32.3 50% 80 63.2 60.5 25% 45.9

0% 2014 2015 2016 2017 Source: Accenture, IDFC Securities Research

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VC-lending deals are now While blockchain technology remains promising, it is still young. Most of shifting towards the investments in the segment are VC led. While crypto currencies is the developing markets like most prominent application of the technology, we think that there are lot India of other applications, particularly in financial services space, such as smart contracts, etc.

Exhibit 56: Global venture investments in blockchain companies Deal value (US$m - LHS) Deal volume (RHS) 600 100 92

450 72 75

300 51 50

150 29 25

9 0 0 2013 2014 2015 2016 2017 Source: KPMG, IDFC Securities Research

VC-lending deals have moved out of China to an extent and are now shifting towards developing markets like India.

Exhibit 57: India VC FinTech landscape

Source: CB insights, IDFC Securities Research

Exhibit 58: India funding trend Financing Company name Financing Type Focus Region size ($M) Capital Float 45.6 Series C SME India Niyogin 36 Public SME India Mswipe 41 Series D Payments India Bankbazaar 30 Series D Lending India Policybazaar 77 Series E Insurtech India

Source: KPMG, IDFC Securities Research

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FinTech progress in China While China might have lagged the US on other technologies, though marginally, the former is clearly the most established model for success in the FinTech space. Given China’s high levels of growth, internet and mobile penetration, the country has already become the world’s largest e- commerce market.

 Why look at China? India is at a similar stage We do appreciate that consumer behaviour, privacy-related issues and to what China was 5-6 government support towards internet economy in China are different from years ago in terms of that in India. However, we do think that there are multiple parallels that device ecosystem one could draw between the two – rise of smartphones and device ecosystem driving digital adoption, gap of financial services in China, high cost of service delivery etc. We think that India is at a similar stage to what China was 5-6 years ago in terms of device ecosystem. Thus rising internet penetration should result in the emergence of new delivery models. We have already seen success in payments (Paytm), ride sharing (Ola) and food delivery (Zomato & Swiggy) spaces in India, similar to China. We expect emergence of scale Fintech players in India too. However, unlike China, which has local BigTechs (Alibaba, Tencent and Baidu), India’s BigTechs are global companies (Google, Amazon, Facebook).

 China story - Mobile the primary device Mobile is the primary internet access device in China. By Dec 2017, 97.5% of Chinese netizens accessed the internet via their mobile phones, an annual increase of 2.4 percentage points from the end of 2016, showing a record-high utilization ratio; 53.0% used desktops and 35.8% used laptops, both declining from the end of 2016.

Exhibit 59: Usage of internet access devices in China Exhibit 60: Percentage of broadband subs accessing the internet 2016 2017 120% Subs Accessing the Internet at a Speed of > 8Mbps 97.5% Subs Accessing the Internet at a Speed of > 20Mbps 95.1% 90% 100% 91.0% 69.7% 91.2% 60% 75% 77.8% 36.8% 31.5% 35.8% 28.2% 50% 40.9% 30% 25.0% 27.1% 22.6% 33.4% 25% 16.0% 0% 10.4% Desktop Laptop Mobile TV 0% 4.5% Phone 2012 2013 2014 2015 2016 2017 Source: CNNIC, IDFC Securities Research Source: CNNIC, IDFC Securities Research

Exhibit 61: China – Average online duration per week Exhibit 62: China - Internet users and penetration Internet Users (m - LHS) Average Online Duration of Internet Users, per Week Internet Penetration (% - RHS) 30 27 800 60.0% 26.1 26.2 26.4 25 25 600 45.0% 20.5 20 400 30.0%

15 200 15.0%

10 0 0.0% 2012 2013 2014 2015 2016 2017 2010 2011 2012 2013 2014 2015 2016 2017

Source: CNNIC, IDFC Securities Research Source: CNNIC, IDFC Securities Research

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Improving speed and device ecosystem have led to the growth of users of various applications. For example, users of online meal ordering grew 64.6% annually in 2017. In China, in terms of mobile phone applications, users of mobile meal ordering and mobile travel booking increased 66.2% and 29.7% yoy, respectively.

The proportion of internet The proportion of users for offline payments increased in rural areas, and users in China paying the user scale of internet finance rose significantly. China’s mobile payment offline bills via mobile users have continued to expand, and their habits have further phones has increased to consolidated. The proportion of internet users paying offline bills via 65.5% from 50.3% at the mobile phones increased from 50.3% at the end of 2016 to 65.5% currently. end of 2016 Offline payments have penetrated rural areas at a faster pace, with the proportion of rural Internet users using offline payments having increased from 31.7% at the end of 2016 to 47.1% currently.

 China – High Internet application adoption rates Over the past half-decade, China’s FinTech industry has seen phenomenal growth - 2013 is widely recognised as the onset of the boom. Since then, major segments of the FinTech market – namely, online P2P lending, online wealth management, digital insurance, and third-party payment – have on average doubled or even tripled every year.

Exhibit 63: China - Usage rate by application type Dec. 2017 Dec. 2016

The percentage The percentage Number of Number of Annual growth Applications of internet users of internet users Internet users internet users rate using the using the (10,000) (10,000) application application Instant messaging 72,023 93.3% 66,628 91.1% 8.1%

Search engine 63,956 82.8% 60,238 82.4% 6.2% Online news 64,689 83.8% 61,390 84.0% 5.4%

Online video 57,892 75.0% 54,455 74.5% 6.3%

Online music 54,809 71.0% 50,313 68.8% 8.9%

Online payment 53,110 68.8% 47,450 64.9% 11.9% Online shopping 53,332 69.1% 46,670 63.8% 14.3%

Online games 44,161 57.2% 41,704 57.0% 5.9%

Online banking 39,911 51.7% 36,552 50.0% 9.2% Online literature 37,774 48.9% 33,319 45.6% 13.4%

Travel booking 37,578 48.7% 29,922 40.9% 25.6%

E-mail 28,422 36.8% 24,815 33.9% 14.5% Internet financing 12,881 16.7% 9,890 13.5% 30.2%

Online stock or fund trade 6,730 8.7% 6,276 8.6% 7.2%

Microblog 31,601 40.9% 27,143 37.1% 16.4%

Map query 49,247 63.8% 46,166 63.1% 6.7% Online meal ordering 34,338 44.5% 20,856 28.5% 64.6%

Online education 15,518 20.1% 13,764 18.8% 12.7%

Online tax-hailing service 28,651 37.1% 22,463 30.7% 27.5% Online car-hailing service or fast 23,623 30.6% 16,799 23.0% 40.6% ride

Live streaming 42,209 54.7% 34,431 47.1% 22.6%

Shared bike 22,078 28.6% - - -

Source: CNNIC, IDFC Securities Research

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Rapid economic growth in China’s economy and its booming middle class, have paved the way for a corresponding rise in financial services in the country. However, on traditional parameters of banking services infrastructure was below developed markets like the US and Europe.

Exhibit 64: Banking infrastructure per 100,000 adults in 2014 China USA & Canada Europe

Commercial bank branches 8.1 28.2 28 ATMs 55 222 81

Source: EY, RBI, IDFC Securities Research

State-owned banks in China have largely underserved the SME and retail customer segments. SMEs, which lack qualified collateral and credit repayment track records, receive only 20-25% of bank-disbursed loans. Yet, they account for 60% of GDP and 80% of urban employment. This coupled with shortened maturity curve, led to a sharp rise in VC activity in China.

 China’s FinTech landscape About 129m netizens purchased internet financing products, an increase of 30.2% yoy, and the internet financing market featured diversified development. At the same time, P2P credit market continued to lower interest rate on loans, and loan business was in fuller compliance with relevant laws.

As per Ernst & Young (EY), China’s FinTech activity spans across 4 key verticals, in our view China constitutes 47% of • Payments global digital retail sales • Financing • Investments • Others

Exhibit 65: China’s FinTech landscape

Direct Bank Debit Transfer System

Mobile Payment Solution

PAYMENT Payment Service Provider

Personal Lending

SME Lending

FINANCING Crowd - Funding

Online Saving Platform

Online Asset Management

SAVING/ Online-only

INVESTMENT Bank

Cloud Computing

Personal Credit Scoring

OTHERS Online-only insurance Company

Source: IDFC Securities Research, Company

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India FinTech

 Payments in China has 530m users By Dec 2017, China had 531m online payment users, an annual increment of 56.61m or 11.9%, with a utilization ratio of 68.8%. Specifically, mobile payment users grew rapidly to 527m, an increase of 57.83m or 12.3% over the end of 2016, with 70% utilization ratio.

Exhibit 66: China online payment users Mobile payment users (m - LHS) % of internet users using online wealth (% - RHS) 540 70.0%

520 68.0%

500 66.0%

480 527 64.0%

460 62.0% 469 440 60.0% 2016 2017

Source: CNNIC, IDFC Securities Research

 Savings/Investments growing rapidly through FinTechs Internet financiers in China Up to December 2017, 129m netizens had purchased internet financing have been able to address products, an increase of 30.2% yoy, and the utilization ratio stood at 16.7%, financing across the credit up 3.2 percentage points. In 2017, China’s internet financing market was spectrum becoming diversified. Driven by regulations in the financial sector and strategic realignment of Ant Financial, Yu'e Bao (Chinese money market fund) lowered the ceiling on single-day investment of an individual investor to RMB20,000 and put a cap of RMB100,000 on the total investment. This impacted AUM growth in 2017, but by itself the size of these players is already large and showcases how much some of these business models can potentially scale – especially in underpenetrated markets like India. Various short-term and regular products of online wealth management launched by traditional financial institutions including banks and fund companies maintained rapid growth. Tencent and Industrial and Commercial Bank of China (ICBC) launched Micro-Gold, a wealth management product, and JD and Industrial Bank rolled out Industrial Bank-JD Small Financial Gold Card. All these efforts further diversified products in the field of online wealth management.

Exhibit 67: China - Online wealth management users Online wealth users (m - LHS) % of internet users using online wealth (% - RHS) 140 20.0%

105 15.0%

70 10.0% 129 99 35 5.0%

0 0.0% 2016 2017 Source: CNNIC, IDFC Securities Research

 China’s internet financing straddles from prime to payday The scale of internet financing has been tremendous in China, as the Chinese economy has been in the process of shifting from manufacturing to consumption. Most internet financiers have been addressing the market that is outside of the typical ‘super prime’ bracket, which had been the forte of banks so far. As discussed previously - we believe China’s FinTech 47 | IDFC SECURITIES 7 September 2018

India FinTech

market is peculiar, as internet financiers there have been able to address financing across the credit spectrum and have achieved the scale. However, at the far end of the spectrum, the quality of credit has been getting thin, thereby inviting a lot of regulatory scrutiny in China – particularly in payday financing.

Exhibit 68: How players are addressing the market

Near Super prime Prime Sub-prime Thin filers prime

E-commerce affiliated finance companies Banks Offline consumer P2P finance lender Payday loan companies lenders Consumer finance penetration rate penetration finance Consumer

Personal income group

Source: IDFC Securities Research

Exhibit 69: China’s household debt to GDP (%) China's household debt to GDP 48.4 50 46.9 44.4 45 41.7 38.8 40 36.4 37.3 35

30

25

20 Jan 15 Jul 15 Jan 16 Jul 16 Jan 17 Jul 17 Jan 18 Source: IDFC Securities Research`

Exhibit 70: Unsecured consumer finance market in China

China Unsecured credit demand (US$ bn) FinTech companies in 2,000 1,885 China have managed to gain scale rapidly by leveraging their existing 1,500 large online user bases 1,000 666

500

0 2015 2019E

Source: Yirendai, IDFC Securities Research

FinTech companies in China have managed to gain scale rapidly by leveraging their existing large online user bases or acquiring massive volumes of customers through low-cost, high-reach means, such as funnelling customers through reputable ecosystems. Beyond payments, FinTech players are utilising online-to-offline apps as gateways to cross sell financing, investment, and insurance offerings. For example, travel site 48 | IDFC SECURITIES 7 September 2018

India FinTech

and app, Ctrip, collaborates with FinTech companies to offer consumer credit – to borrow for immediate trips – and for investments – to save for future trips. The company also works with online insurers to provide travel- related insurance.

Exhibit 71: O2O apps with embedded financial services and products

Source: Oliver Wyman, IDFC Securities Research

 Others – Fintech, an important part of Alibaba economy Ant Financial is building The biggest of the Chinese FinTech firms are aggressively creating multi- an ecosystem that goes product platforms. Ant Financial, for instance, wants to embed its services beyond financial services into customers’ daily lives to raise the percentage of users with multiple products, in the process of boosting customer stickiness and generating ever more complete customer data. Ant Financial is building an ecosystem that goes beyond financial services to encompass transportation, dining, medical services, and much more. This has already reaped initial success, as measured by the speed of customer acquisition, with the period for a financial product within the Ant ecosystem to reach 100m users reducing from 31 months for insurance, down to 20 months for Yu’e Bao, then 11 months for Sesame Credit.

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Exhibit 72: The Alibaba economy

Source: Alibaba, IDFC Securities Research

China has started a Social To further enable credit scoring, which is currently done through China Credit System (SCS), Credit Reference Center (CCRC), a centralised database is set up to check which is expected to be on credit histories of Chinese citizens. However, this data is insufficient and operational by 2020 mostly restricted to super prime or prime borrowers.

To address these gaps, China has started a Social Credit System (SCS), which is expected to be operational by 2020. The system will assign a credit score to every citizen and business in China, based on their financial and social behaviour. Government has granted licenses to 8 private enterprises to develop their scoring systems using online data sources. Three of these eight licenses have gone to BigTech in China. Maturing mobile money sector with new and more rounded credit assessment initiatives raise the possibility of interoperability across wallets and other banking services, which we believe could lead to a more open architecture.

Exhibit 73: 3 Licenses for credit scoring with Chinese BigTech Company Business Alibaba Internet Tencent Internet Ping An Financial Services Pengyuan Credit Services Credit Scoring China Chengxin Credit Information Credit Scoring IntelliCredit Credit Scoring Blue Focus Credit Scoring Yin Zhi Jie Credit Scoring

Source: EY, IDFC Securities Research

Exhibit 74: Private entities putting in data for social credit scoring platform

Source: EY, IDFC Securities Research

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An evolving regulatory framework International standard- Financial innovation has become a focal point for a lot of attention, and setting bodies are taking some jurisdictions have decided to take a more active approach in steps to actively monitor facilitating this innovation. Towards achieving financial innovation, they FinTech developments have taken a variety of regulatory and supervisory initiatives such as regulatory sandboxes, innovation hubs, innovation incubators or accelerators, etc. The regulatory uncertainty surrounding FinTech could potentially hamper development. As a result, international standard-setting bodies (BCBS, FSB, CPMI, WBG, etc), including regulatory authorities of different jurisdictions, are taking steps to actively monitor FinTech developments both domestically and in co-operation with international organizations.

Market place lending can come in many forms – P2P, payday loans, balance sheet-based lending and a platform lender. The regulations related to market place lenders are still under development, and the market responses of regulators have been varied, depending on their experiences.

Exhibit 75: Regulatory snapshot China Uk US Regulatory approach to Rule and principle based Principle based Rule based MPL Funding source Platform lender, as broker and MPL regulation limited to platform A hybrid of several different B/S lender lending funding models Securitization Yes, but only sponsored by No securitizations to date Yes, can be sponsored by both third parties MPLs and third parties Capital requirement No for platform lender, yes for Yes for platform lender, no for B/S No B/S lender lender Risk retention No No No, but under consideration Deposit insurance Yes No Yes Client funding Yes Yes No specific regulatory requirement, segregation but applies in market practice Disclosure to investors Yes Yes Yes, when filing securities Secondary service No Yes No specific requirement, but agreements institutional investors require MPLs to arrange substitute serivces Tax promotion Yes, but only for early-stage Yes No Fin-Tech firms Promotion of SME Yes Yes No lending Data protection Yes Yes Yes Anti-money launders Yes AML rules exist, but they are not May apply, depending on structure (AMLs) reporting/info yet extended to MPL of MPL: bank partners must comply disclosures Disclosure to borrowers Yes, in the SLB 1.0 for B/S Yes Yes, but fewer protections for SME lender, no specific requirement borrowers in the draft AMBA for platform lenders Registration requirement Yes Yes Some state lending licensing laws Credit Existing CRC system that Requirements for platform lenders; Requirements such as the ECCA underwriting/Credit needs further development for UK government promoting greater apply; market participants calling information SME lending access to credit information for greater access to credit data Interest rate Requirement on interest rate Limited interest caps MPLs partnering with banks to cap utilize favourable usury laws Clearing/Settlement Two major settlement and Partnering with banks Partnering with banks clearing models with banks

Source: WEF, IDFC Securities Research

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 Standardization and data – Key challenge As regulators and policy makers develop their understanding of marketplace lenders and attempt to implement appropriate regulations, key challenges that FinTech players face hover around the fact that non- traditional players rely on large amounts of digital data to make credit and other decisions. How these players exploit such data remains a key concern and a hot potato for the FinTech industry.

 India P2P – Regulated as an NBFC by RBI There is absence of a clear Currently, there is absence of a clear regulatory framework on Indian P2P regulatory framework on lending. Most P2P start-ups are registered under the Companies Act and Indian P2P lending abide by The Negotiable Instruments Act. RBI has brought P2P lending under its ambit. The idea is to bring the P2P lending platforms within the scope of NBFC governance ‘NBFC-P2P’ licensing regime.

Exhibit 76: RBI NBFC-P2P RBI NBFC-P2P prudential norms 1 NBFC-P2P shall maintain a leverage ratio not exceeding 2 The aggregate exposure of a lender to all borrowers at any point of time, across 2 all P2Ps, shall be subject to a cap of Rs10,00,000 The aggregate loans taken by a borrower at any point of time, across all P2Ps 3 shall be subject to a cap of Rs10,00,000 The exposure of a single lender to the same borrower, across all P2Ps, shall not 4 exceed Rs50,000 5 The maturity of the loans shall not exceed 36 months P2Ps shall obtain a certificate from the borrower or lender, as applicable, that the 6 limits prescribed above are being adhered to

Source: RBI, IDFC Securities Research

 Emergence of regulatory sandbox We are of the view that more than just the description for traditional banks, collaboration between FinTech’s and banks offers large market opportunities. FinTech Sandbox also known as API sandbox is used by innovators to test their products. Sandbox is effectively a testing environment for new technologies. Regulatory sandboxes allow FinTech companies to make sure they comply with the regulatory framework while working on innovative products.

Regulatory Sandbox

Source: PWC, IDFC Securities Research

UK was the first place where institutional commitment to implement sandbox came into place. Financial Conduct Authority (FCA) started with project innovate in 2015 and the first edition of British regulatory sandbox began in 2017. Since UK, regulators of more countries are adopting sandbox to test innovative FinTech products in a stable environment.

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 EU- Payment Service Directive 2 What is PSD2? PSD2 enables bank customers, both consumers and businesses, to use third-party providers to manage their finances. The directive obligates banks to provide these third-party providers access to their customers’ accounts through open APIs. This will enable third-parties to build services on top of banks’ data and infrastructure.

The EU directive introduces two new types of players to the financial landscape: Account Information Service Provider (AISP) and Payment Initiation Service Provider (PISP).

AISP - AISP are service providers that have access to the account information of bank customers. Such services could use transaction data to analyze a user’s spending behaviour or aggregate a user’s account information from several banks into one overview.

AISP - Before and after PSD2

Source: EVRY PSD2 whitepaper, IDFC Securities Research

PISP - A retailer needs to go through multiple channels to complete the payment transaction. A PISP will create a software ’bridge’ between the customer’s and the retailer’s accounts, where the necessary information is exchanged to make the transaction. This solution involves fewer parties and does not require the customer to reveal its payment card details.

PISP - Before and after PSD2

Source: EVRY PSD2 whitepaper, IDFC Securities Research

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 Implications Allowing other qualified non-banks to access a bank customer’s account data to initiate payments is effectively further commoditisation of banks. PSD2 puts banks under considerable economic pressure and exposes them not only to greater competition with higher IT costs, but also creates a tough challenge for banks to differentiate themselves when offering loans, as non-banks start accounting for a significant chunk of customer interactions. We could see the creation of specialist banks for the sole purpose of enabling partners, like retailers and telecom players.

Creates another layer for transactions “Access to account” prior to PSD2 “Access to account” with PSD2 Payer (PSP’s customer) Payer (PSP’s customer)

Mobile Mobile Online Branch/ Online Branch/ banking Terminal banking Terminal PISP AISP banking Phone banking Phone (App) (App)

Payer’s payment account Payer’s payment account Infrastructure of ASPSP Infrastructure of ASPSP

Source: EY, IDFC Securities Research

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 India Payments - WATAL committee report on payments A committee was constituted under the Finance Ministry, with the objective to push digital payments in India and recommend the way forward from a regulatory standpoint. Payments now need to be regulated independently. RBI’s approach to lightly regulate non-banks in payments has enabled the latter to emerge as significant players in a relatively short time. This growth now needs to be nurtured, so that banks have the competitive pressure to innovate and non-banks have an equal opportunity to compete.

The committee suggested that NPCI could potentially be classified as Critical Payment Infrastructure Company (CPIC). The suggestion is to diffuse current shareholding of NPCI, which is controlled by 10 banks. Additionally, the report suggests creating a law to define CPIC only as operators and providers of payments infrastructure. This can democratise innovation and adoption of payments

NPCI shareholding Entities Shareholding Total per entity

SBI, PNB, Canara Bank, Bank of Baroda, Union Bank of India, Bank of India, ICICI Bank, 7.47% 74.7% HDFC Bank, Citibank N.A., HSBC

Dena Bank, Central Bank of India, Allahabad Bank, Bank of Maharashtra, Andhra Bank, Syndicate Bank, UCO Bank, Oriental Bank of Commerce, Corporation Bank, Indian bank, Vijaya Bank, United Bank of India, Punjab & Sind Bank, Axis Bank, Kotak 1.06% 20.14% Mahindra Bank, Yes Bank, The Jammu & Kashmir Bank, Indusind Bank, Federal Bank

South Indian Bank, Karur Vyasya Bank, Karnataka Bank, Tamilnad Mercantile Bank, City Union Bank, Lakshmi Vilas Bank, Catholic Syrian Bank, RBL Bank, DCB Bank, 0.42% 4.20% Deutsche Bank AG

The Saraswat Co-operative Bank, The Cosmos Co-operative Bank, The Shamrao Vithal Co-operative Bank, Abhudaya Co-operative Bank, The Bharat Co-operative Bank (Mumbai), TJSB Sahakari Bank, Janta Sahakari Bank (Pune), Punjab & Maharashtra Co- operative Bank, NKGSB Co-operative Bank, Kalupur Commerical Coop. Bank, Baroda 0.05% 0.85% Uttar Pradesh Gramin Bank, Pragati Krishna Gramin Bank, Kerala Gramin Bank, Kaveri Grameen Bank, Andhra Pradesh Grameena Vikas Bank, Karnataka Vikas Grameen Bank, Gramin Bank of Aryavart

Source: Finance.du.ac.in, IDFC Securities Research

Key highlights from the report Key recommendations of Watal Payments report 1 Make regulation of payments, independent from the function of central banking 2 Promote digital payments within the government 3 Promote eKYC and paperless authentication 4 Allow non-bank PSPs to directly access payment systems 5 Require shareholding and governance of important retail payment organisations to be improved 6 Enable payments to be inter-operable between bank and non-banks as well as within non-banks Recommends that CICs be allowed access to alternate data from non-financial sources like telecom and utility bill 7 payments, etc 8 Open access

Source: finance.du.ac.in, IDFC Securities Research

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Financing – A Case study

SOLARISBANK – TRANSACTIONAL BANK

• SolarisBank offers a completely digital banking platform to which other businesses can connect in order to offer financial services themselves. • SolarisBank was founded in March 2016, after receiving a full banking license from the German regulator

• Offering a banking platform, which lets them seamlessly integrate financial services into their offerings • Any company can create a banking offering and/or lend to their customers powered by SolarisBank

• White-labelled bank that provides financial services platform through modular APIs

Financing – A Case study

APOLLO FINVEST – AWS OF LENDING

• Apollo Finvest is a technology company with an NBFC license. India’s only white-labelled digital lender • Listed on BSE with a networth of Rs200m. Unlevered book

• Build the perfect financial product for customers using their proprietary data • Products include short term/long term personal loans, consumer financing, checkout financing, pay later services, settlement financing, business loans

• Provides financial services platform through modular APIs • Pure B2B2X platform

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Personal lending – A case study

TALA – Alternate Lender in Emerging Markets

• Consumer lending app that underwrites customers in real time using thousands of alternative data signals • Bring credit access to people who don’t have credit history and offer small ticket loans • Tala already operates in Kenya, Tanzania, and the Philippines, where it has delivered credit to more than 1.3m customers and originated more than US$300m

• Anyone with an Android smartphone in Tala’s markets can apply for a loan and receive an instant decision, regardless of their financial history • Tala disburses loans between US$10 and US$500 to a mobile wallet or via payment rails as per customer choice

• The data that Tala looks at includes social connections, texts and calls, merchant transactions, app usage, and personal identifiers • Anyone with an Android smartphone in Tala’s markets can download the Tala app, apply for a loan, and receive an instant decision

Savings/Investment – A Case study

Yu’e Bao – World’s Largest Money Market Fund

• Yu’e Bao (English translation – Left over treasure) online money market fund – part of Alipay ecosystem • Assets of about US$250bn with 370m account holders

• Taobao users can deposit surplus and more in their wallets into a Yu’e Bao money market fund • Yu’e Bao offers about 5-6% annual interest rate on deposits, much higher return than banks

• Yu’e Bao retails through PayPal-like Alipay of Alibaba • Alipay, the payment tool of choice for hundreds of millions of online shoppers who use Alibaba's online marketplace, Taobao, which functions as a virtual wallet • The process of depositing money into one's Yu’e Bao account takes no more than five clicks. It also allows users to set everything automatic so their account surplus would be transferred into Yu’e Bao at the end of the day without the user being aware of it

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Others – Regtech: Smartkarma – A Case study

Smartkarma– Marketplace for investment research

• Smartkarma is a Regtech company servicing the asset management industry • Funded by Sequoia in the latest Series B round takes the total funding to US$21m

• Operates a digital marketplace that provides investment insight into Asian markets • Most investment banks have conflicts with investment research offered • Pricing model per user per month

• MIFID regulation key driver for adoption as regulators unbundle investment research and trading commissions • Users access Smartkarma's platform by paying a yearly subscription fee. Smartkarma pays all of its contributing research analysts a monthly fee based on the reach and influence • 70% of the fee distributed to insight providers

Others – Insurtech: Lemonade – A Case study

Lemonade – Insurtech

• Lemonade is a technology company with an insurance license that offers insurance to homeowners and renters. Backed by Softbank, Alphabet and Sequoia • 90,000 customers as of Dec 2017 and 60 employees

• A full-stack insurance company, Lemonade underwrites its own policies and is reinsured at Lloyd’s of London

• Lemonade uses artificial intelligence in the form of chatbots and machine learning to provide insurance policies and handle claims, replacing brokers and paperwork • Lemonade's business model differs from that of typical insurance companies; Lemonade keeps a flat 20% fee of a customer's premium while setting aside the remaining 80% to pay claims and purchase reinsurance

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India - Market structure India remains one the After having laid out our key mobility and FinTech framework in the largest addressable previous sections, we now narrow our focus to the Indian market. India markets in the world remains one the largest addressable markets in the world with a rising middle class, a growing economy and rising smartphone and internet penetration. The trend towards mobility and digitisation is a secular one and we explore a basket approach to addressing the addressable market and investment opportunities within the India theme.

 India’s shift to digital economy Strong internet adoption in India is only going to accelerate, as lower hardware prices translate to higher wireless broadband access in the country. We see strong prospects for India’s internet economy, which comprise (1) transactions, (2) services, (3) subscription and (4) advertising. Already, companies are allocating more marketing (advertising) and content development funds to digital/online content delivery. Digital advertising revenue posted strong 40% CAGR (CY09-CY14) and is poised for 30% CAGR over CY14-CY19E. We have seen strong emergence of e- commerce (companies like Flipkart, Snapdeal, Jabong, Olx) as a new category in India. The next wave of growth for the digital industry will be increased adoption of the internet for a broader set of services across industry use cases. Financial services is one of the key areas that we are currently exploring in this report.

 India’s mobile revolution has led to 400m+ internet users India has ~700m unique wireless subscribers and wireless broadband penetration currently at about 30%. The Indian mobile market has seen a massive shift in trajectory over last two years, post the launch of Jio’s 4G LTE services. Jio has made large investments in best-in-class network at extremely affordable data prices. Following Jio, other incumbents have consolidated their market position and accelerated their capex investments. We believe this augurs well for pushing India into a digital ecosystem and has brought in millions of new users into the internet connected world. This, coupled with rising affordability of smartphones has enhanced data penetration from 16% in CY15 to 27% as of CY17.

Exhibit 77: Rising smartphone penetration Exhibit 78: Rising internet subs

India Smartphone penetration Total Internet Subs - India (m) 29% 30.0% 500 446 391 21% 400 22.5% 332 17% 267 300 239 15.0% 11% 200 5% 7.5% 100 2% 1% 22 25 0 0.0% 2011 2012 2013 2014 2015 2016 2017 2011 2012 2013 2014 2015 2016 2017 Source: Company, IDFC Securities Research Source: Company, IDFC Securities Research

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Exhibit 79: Significant improvement in data speeds Exhibit 80: Wireless broadband users (Top 3 Operators)

3G (Mbps) 4G (Mbps) Wireless Internet Subs (m) 20.0 450 17.3 360 15.0

9.6 270 10.0 7.0 7.4 180

5.0 2.8 2.4 2.4 90 0 0.0 0 Airtel Idea Vodafone Jio 2014 2015 2016 2017

Source: TRAI, IDFC Securities Research Source: IDFC Securities Research

Extremely affordable data prices and generous allowances on bundles have ensured not only sharp rise in adoption but also in stupendous rise in average consumption per subscriber per month. This trend, in our view, seems irreversible and is propelling Indians into a digital world for the very first time at extremely good speed.

Exhibit 81: Data usage (Airtel) Exhibit 82: Data affordable India – Jio popular plans Plan Monthly Monthly Data useage per sub/month (GB) Daily Validity 7.7 Price Data ARGB ARPU Calls 8.0 Data (days) 6.4 (Rs.) (Rs.) (Rs) 6.0 5.2 98 2 GB* 28 3.5 105 Unlimited 4.0 149 1.5GB 28 5.3 160 Unlimited 4.0 2.6 198 2GB 28 7.1 212 Unlimited 1.3 349 1.5GB 70 5.0 150 Unlimited 2.0 0.9 1.0 0.9 449 1.5GB 91 4.9 148 Unlimited 0.0 398 2GB 70 5.7 171 Unlimited 448 2GB 84 5.3 160 Unlimited 16 June- Mar-17 Mar-18 Sep-17 Dec-17 Sep-16 Dec-16 498 2GB 91 5.5 164 Unlimited

June-17 June-18 Source: TRAI, Company, IDFC Securities Research Source: TRAI, Company, IDFC Securities Research. * for a month, TRAI

 Rural mobile penetration still low India in India Rural penetration low at India’s teledensity has been increasing consistently over the past decade 56% and currently stands at 92%, given the sharp drop in device prices, especially feature phones. We believe mobile phone remains the key internet access device for the broader Indian populace and thus penetration improvement will continue to bring in new internet users in India.

Exhibit 83: India –Teledensity Teledensity % 100 88 92 80 76 73 75 80 68 71

60 50 37 40

20

0 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

Source: RIL, IDFC Securities Research

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However, we note that a lot of this is driven by proliferation of dual SIMs, especially in urban areas. We believe rural penetration still remains low at 56% and has room for improvement.

Exhibit 84: India – Urban and rural teledensity Urban % Rural % 168 180 163 165 150 141 140 143 147 135 112 89 90 53 56 43 45 49 33 38 40 45 23 15

0 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Source: RIL, IDFC Securities Research

 How affordable is data in India now? We look at annual ARPU spend of subscribers and compare it with the GDP per capita trend to judge the affordability of telecom services for Indians.

Exhibit 85: India- GDP per capita Exhibit 86: India – Annual ARPU India's GDP per capita (US$ - LHS) Telecom ARPU (Annual) (US$ - LHS) YoY Growth (% - RHS) YoY Growth (% - RHS) 2400 10.0% 64 8%

1800 7.5% 48 0%

1200 5.0% 32 -8%

600 2.5% 16 -16%

0 0.0% 0 -24% 9 2011 200 2011 2012 2015 2013 2016 2014 2010 2012 2015 2013 2016 2014 2010 2008 2009 2008 Source: Tradingeconomics, IDFC Securities Research Source: Company, IDFC Securities Research.

R-Jio’s entry has increased data affordability Entry of R-Jio in India’s telecom market has increased the affordability of data. Post entry of Jio, per GB of data cost has fallen US$4 to less than US$1. We think this makes a strong case for adoption of data packs among users and push a larger set of people further into the digital economy.

Exhibit 87: India – Price of 1GB of data utilized

Data cost ($) per GB 5.8 6.0 5.1 4.5 4.5 3.8

3.0 2.7

1.5 0.5

0.0 FY13 FY14 FY15 FY16 FY17 FY18 Source: RIL, IDFC Securities Research

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ARPU/GDP per capital lowest in a decade Telecom services affordability has been rising consistently in India over the past decade and the telecom ARPU/GDP per capita has nearly halved from 2% to 1.3% over last two years. With affordability levels now good, improvement in smartphone adoption and handset ecosystem will accelerate data adoption, in our view.

India has now reached the Exhibit 88: Blended ARPU($) as a percentage of GDP per capita affordability levels of China ARPU % of GDP per Capita - India 8.0% 6.8% 6.0% 3.9% 5.0% 4.0% 2.8% 2.4% 3.3% 1.7% 2.0% 2.5% 2.0% 1.3% 0.0% 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Source: Trading economics, Company, IDFC Securities Research

India’s ARPU affordability levels same as China now Importantly, India has now reached the affordability levels of China. Although absolute ARPU levels are not comparable, given the higher GDP per capita, we note ARPU (annual) to GDP per capita ratio is a better metric for like-for-like comparison. We believe telecom service affordability levels in India are now comparable to China.

Exhibit 89: Blended ARPU($) as a percentage of GDP per capita

ARPU % of GDP per Capita - China ARPU % of GDP per Capita - India 8.0%

6.0%

4.0%

2.0%

0.0% 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Source: Trading economics, Company, IDFC Securities Research

Lower ARPU/GDP per capita drives 4G penetration Affordability and lower China saw strong adoption of 4G services, as affordability levels improved smartphone prices there. This was also driven by drop in smartphone prices. However, we strengthen adoption of 4G think device affordability levels in India are still not as comparable to China services and thus we see lot of telcos such as Jio making efforts to introduce cheaper smartphones.

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Exhibit 90: China -ARPU($) as a percentage of GDP per capita and 4G penetration ARPU % of GDP per Capita - China China 4G Penetration (% - RHS) 4.0% 0.8

3.0% 0.6

2.0% 0.4

1.0% 0.2

0.0% 0 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

Source: Trading economics, Company, IDFC Securities Research

 Handheld devices to drive internet access not PCs The primary access device for internet in India is most likely to be a handheld device and not a traditional desktop/laptop, as is the case in developed markets. For Infoedge, 35-60% of traffic, depending on the property, is mobile-led (either app or mobile web). We reckon this is happening where high-speed internet penetration wireless is 12-13% of subscribers and we expect this trend to accelerate, as new users across various socioeconomic strata get onto high-speed internet.

Exhibit 91: India – Desktop versus mobile penetration Exhibit 92: % of traffic on mobile for internet properties

2018 2015 100 92 100% 90%

75 80% 70% 62% 55% 60% 50% 50 40% 35% 25 15 20%

0 0% Mobile penetration % Desktop penentration % Jeevansathi Naurki 99acres

Source: , IDFC Securities Research Source: Company, IDFC Securities Research.

Device affordability is a key factor that has enabled the growth of telecom services in India. Based on census data from 2001-11, household phone penetration has jumped nearly 15x in rural markets, while television households have nearly doubled during the same period. Television penetration will continue to rise, but it is the mobile device ecosystem that will fuel content delivery in India over the next 3-5 years, in our view.

Exhibit 93: India: Households having a phone (%) Exhibit 94: Device affordability Households having a phone % India Device Affordabilty Rs. Households having a TV % 18,000 100 82 13,500 76.7 9,000 75 63.2 54.3 4,500 47.2 50 0 33.4

25 screen screen screen Laptop16

0 inchscreen inchscreen Tablet7 inch Tablet8inch

Urban Rural Total Tablet10 inch Smartphone4 Source: Census, IDFC Securities Research Source: Company, IDFC Securities Research.

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 India - Handset market shifting to smartphones Handset ecosystem and better devices are the key to strong digital adoption in India. India currently has 1bn wireless subscribers and annual handset. However India still remains one of the largest feature phone shipment markets. Despite the price correction in data pack prices we think that smartphone penetration has be rather slow. We think that, continued price deflation on the handset prices will certainly shift larger market towards data phones. Jio through its Jio-Phone offerings reducing the entry barrier.

Exhibit 95: Total handset shipments Exhibit 96: Total feature phone shipments Total handset shipments (mn) Featurephones 350 250 288 206 206 280 247 257 253 245 200 177 164 221 150 210 150 136

140 100

70 50

0 0 2012 2013 2014 2015 2016 2017 2012 2013 2014 2015 2016 2017

Source: TRAI, Company, IDFC Securities Research Source: TRAI, Company, IDFC Securities Research

Exhibit 97: Jiophone 1 & 2 specifications General Jio Phone 2 Jio Phone Release date Jul-18 Jul-17 Battery capacity (mAh) 2000 2000 Removable battery - Yes Colours - Black DISPLAY

Screen size (inches) 2.4 2.4 Resolution 240x320 pixels 240x320 pixels HARDWARE

RAM 512MB 512MB Internal storage 4GB 4GB Expandable storage Yes Yes Expandable storage type SD card microSD Expandable storage up to (GB) 128 128 Processor - 1.2GHz dual-core Processor make - SPRD 9820A/QC8905 CAMERA

Rear camera 2-megapixel 2-megapixel Front camera 0.3-megapixel 0.3-megapixel SOFTWARE

Operating System KAI OS KAI OS CONNECTIVITY

Bluetooth Yes Yes, v 4.10 NFC Yes Yes USB OTG - No Number of SIMs - 1 SIM 1

SIM Type - Nano-SIM 4G/ LTE - Yes Source: Company, IDFC Securities Research

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India’s smartphone handset market has seen continued market share dislocation from Nokia to Samsung to Chinese OEMs (Xiaomi, Oppo/Vivo, Oneplus) now. Indian manufacturers control a large part of featurephone segment.

Exhibit 98: India feature phone market share by OEM Exhibit 99: India smartphone market share by OEM Lava 4QCY17 4QCY17 10.2% OPPO 7.2% Reliance Industries Lenovo Micromax 38.0% 8.2% Xiaomi 13.7% 39.4% Vivo 9.6% Transsion 15.3%

Samsung Samsung 35.6% 22.8%

Source: IDC, IDFC Securities Research Source: IDC, IDFC Securities Research

 Decline in handset prices should continue to drive penetration Declining handset prices is a key factor behind strong high-speed data adoption. In the 2G penetration cycle as well, growth spiked once prices of devices fell to sub-US$50 levels, and we expect a similar trend in the 3G/4G cycle. The price decline in the 2G era was slow and chipset makers were relatively reluctant to move down the price curve, but since then, most handset BOM components have been commoditised and even fabless players such as Qualcomm and Marvel have been dropping prices and building affordable chips for emerging markets. (Refer annexure)

 Indian smartphone market to grow to 257m units by 2023E Total handset shipments in India has over 1bn wireless subscribers, but smartphone penetration India should register a remains low at 27%. The overall handset market in India stood at ~288m modest 2% CAGR over units in CY17 and is growing in mid-single digits, but the real shift is from CY17-23E feature phones to smartphones, which is driving volumes as well as ASP improvement for handset players and giving more capable phone in the hands of the users. This shift is being led by continued price erosion, entry of new players and improved distribution reach. As per various reports, smartphone shipments for CY17 stood at 125m, up ~14% YoY.

Exhibit 100: Smartphone shipments Exhibit 101: India – Share of smartphones in shipments

Smartphones (m - LHS) YoY Growth (% - RHS) Share of smartphones in shipments % 140 124 200% 50.0% 109 103 105 150% 40.0% 80 30.0% 70 100% 41 20.0% 35 50% 15 10.0% 0 0% 0.0% 2012 2013 2014 2015 2016 2017 2012 2013 2014 2015 2016 2017 Source: IDC, IDFC Securities Research Source: IDC, IDFC Securities Research

We expect smartphone shipments in India to post 13% CAGR to 257m over CY17-CY23E. Total handset shipments in India should register a modest 2% CAGR over the same period; however, we expect the share of smartphones in total shipments to accelerate from 43% in CY17 to 78% by 2023E. This could further accelerate depending on the pace of price correction on devices and/or handset subsidies by operators such as Jio who are trying to accelerate adoption. Improving shipments should 65 | IDFC SECURITIES 7 September 2018

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translate into increase in smartphone device penetration from 29% in CY17 to 59% by 2023E.

Exhibit 102: India smartphone shipment estimates Smartphone shipments (m - LHS) YoY growth (% - RHS) 257 280 244 20% 225 210 195 15% 166 141 140 124 10%

70 5%

0 0% CY2017 CY2018E CY2019E CY2020E CY2021E CY2022E CY2023E Source: IDC, IDFC Securities Research

Exhibit 103: Smartphone shipment as percentage of total shipments in India

% of handset shipments 90%

75%

60%

45%

30% CY2017 CY2018E CY2019E CY2020E CY2021E CY2022E CY2023E

Source: IDC, IDFC Securities Research

Exhibit 104: India smartphone penetration India Smartphone penetration 59% 60% 54% 48% 44% 45% 39% 34% 29% 30% 21% 17% 11% 15% 5% 1% 2% 0% 2011 2017 2012 2015 2013 2016 2014 2021E 2018E 2019E 2022E 2023E 2020E Source: IDC, IDFC Securities Research

 Government-led digital push creating infrastructure India has seen India has seen transformation of mammoth proportions in the enterprise transformation of world too, with consumers adopting smartphones and shifting into a more mammoth proportions in connected world. Several government programmes have aided the the enterprise world transformation, with Goods and Services Tax (GST) being one of the key enablers. GST brings in more SMBs into the formal and digital connected economy and more importantly, prepares the agents in the SMB supply chain to be more tech-savvy and enabled. Currently, both direct and indirect Tax filings take place digitally in India. India currently processes 3bn invoices per month and India’s GST monthly tax collection is around US$15bn. Importantly, India has added nearly 20m tax-paying SMEs in first year of operation. This allows companies to access GST network (GSTN) through APIs and gives financial services players (Banks and FinTechs) data for better credit decisioning and designing new products for the SME segment.

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Exhibit 105: India GST monthly tax collection (US$ bn)

India's GST Monthly Tax Collection (US$ bn - LHS) yoy growth (% - RHS) 16 150%

15 100%

14 50%

13 0%

12 -50% Jul/17 Jan/18 Oct/17 Mar/18 Apr/18 Sep/17 Dec/17 Feb/18 Nov/17 Aug/17 May/18 Source: Govt of India, IDFC Securities Research

 IndiaStack - Key enabler for FinTech IndiaStack is a set of APIs that allows governments, businesses, start-ups and developers to utilise a unique digital Infrastructure to solve India’s hard problems towards presence-less, paperless, and cashless service delivery. It allows companies to digital authenticate, paperless KYC, pay digitally with consent architecture. This is essential for end-to-end digital service delivery and substantially reduce the cost of customer KYC processing. The Open API team at iSPIRT has been a pro-bono partner in the development, evolution, and evangelisation of these APIs and systems.

Exhibit 106: Evolution of IndiaStack

NeGD launches DigitalLocker, a platform for issuance and verification of documents & certificates in a digital way

CCA launches eSign as an open API to 2016 facilitate an Aadhaar holder to digitally sign a document and MeitY launches DigiLocker, a platform for issuance and verification of documents & certificates 2016 NPCI launches Unified Payments in a digital way, thus eliminating the use Interface, the most advanced public of physical documents payments system in the world to revolutionise digital payments in India NPCI launched Aadhaar 2015 Payments Bridge & Aadhar Enabled Payments System which uses Aadhaar number as a central key for electronically 2012 channelizing the Government benefits and subsidies. UIDAI launched eKYC which allows UIDAI was created with the businesses to perform Know Your objective to issue Unique 2011 Customer verification process digitally Identification numbers using Biometric or Mobile OTP. (UID), named as "Aadhaar 2010 2009 UIDAI launched Aadhaar Auth API even before the first Aadhaar was issued. Source: IndiaStack, IDFC Securities Research

End-to-end digital process for lending possible now India is seeing good Advancements and adoption of digital KYC platforms allow technology- progress in the digital centric companies to address the broader market in India, which is lending infrastructure underpenetrated due to the high cost of delivery in the physical medium. space These platforms have been enabled by Aadhar adoption, Jan Dhan bank accounts, GST and United Payments interface. The cashless layer along with identification helps reduce the cost of delivery substantially. It also can reduce the commission (third party) and processing fees for customers. With the India technology stack, end-to-end digital process is now possible in lending. In our view, India is seeing good progress in the digital lending infrastructure space, having the infrastructure needed for seamless lending and low turnaround time (TAT).

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Exhibit 107: India technology stack in place Consent Layer

Open personal Data Cashless Layer Source IMPS, AEPS, APB, Paperless Layer and UPI Aadhaar e-KYC, Presence-less Layer e-sign, Digital Locker Aadhaar Authentication

Supported by major reforms and policy interventions

Pradhan Mantri Aadhaar Goods and Unified Bharat Bill Jan Dhan Yojana eKYC Services Tax Payments Payment System Network Interface

Source: IDFC Securities Research, IndiaStack and BCG

 India’s credit information coverage improving; has good depth India’s coverage is still India’s credit bureau coverage has been improving progressively. As per below the key Fintech World Bank’s report, ‘Doing Business’, Indian credit bureau now covers markets of China, US and 43.5% of Indian adults. India’s credit infrastructure is clearly rated among UK the best in the world by World Bank, with a rating of 7 (0-8) versus OECD’s average of 6.6 in CY17. We think a strong credit bureau infrastructure provides the bedrock for lending and effectively transforms into an end-to-end digital process. This allows instant credit decision while maintaining the credit quality.

India’s credit bureau coverage has increased rapidly over last 6 years from 15% in CY12 to 43.5% in CY17. However, India’s coverage is still below the key Fintech markets of China, US and UK. Additionally, India ranking in the World Bank report in terms of getting credit is significantly better at 29 versus the country’s overall ranking in the report. That said, India scores well on depth of credit information, and is in line and/or better than developed markets with large FinTech penetration. We see this as a positive, as credit information quality is essential for not only quick but also accurate decision making.

Exhibit 108: India - Credit bureau coverage Exhibit 109: India - Global credit ranking better and improving

Credit bureau coverage (% of adults) India Getting Credit global rank 50% 43.5% India ease of doing business rank 160 142 40% 132 120 30% 100 22.4% 20% 15.1% 80 40 36 10% 40 29

0% 0 CY12 CY15 CY17 CY12 CY15 CY17

Source: Company, IDFC Securities Research Source: Company, IDFC Securities Research

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Exhibit 110: India scores well on depth of credit coverage Exhibit 111: India’s credit coverage below key FinTech markets

India China USA UK CY17 10.0 120% 8 8 100% 100% 8.0 7 7 90% 82.5% 6 6 6 6 6 6.0 4 4 4 60% 4.0 43.5%

2.0 30%

0.0 0% CY12 CY15 CY17 India China USA UK Source: Doing Business report - World Bank, IDFC Source: Doing Business report - World Bank, IDFC Securities Research Securities Research

Exhibit 112: India’s getting credit rank versus US/China/UK

India China USA UK 80 71 67 67

60

40 40 36 29 17 20

4 1 2 4 1 0 CY12 CY15 CY17 Source: Company, IDFC Securities Research

 Data largely consists of prime borrowers with history While India has a good depth of credit data, as sourced from CIBIL, most of the customer profile acquired by existing institutions is broadly stable over the years, considering the score (CIBIL) ranges. This points to the fact that probably, financial institutions have been focussing only on the higher end of the credit (prime) - those who have a credit history or their data is accessible. We believe this measure is a constraint for most of the current financial institutions who rely only on specific data to rate their customers.

Opens opportunity for subprime borrowers for FinTechs We believe a larger open addressable market has been left out and below prime market potential hasn’t been explored due to lack of traditional data sets. This is where we think digital data analytics can be utilised to judge customers’ credit potential. Further, a lot of existing new app economy companies (even non-banks) that have transaction data and are closer to the customer through other services. Such companies have greater capability to make a credit decision on the customers given they are already close to the customer and this gives them an edge over banks to make a better credit decision.

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Exhibit 113: CIBIL score distribution (%)

> 700 600-700 <600 100 4 4 4 4 3 3 95 6 7 7 8 8 9 90

85 90 90 89 88 88 88

80 2011 2012 2013 2014 2015 2016

Source: IDFC Securities Research, Transunion CIBIL and BCG

 Consent architecture – Additional driver India is at the cusp of India is seeing innovation on the retail and commercial lending fronts, digital adoption scale especially on lower ticket assets. While India is doing well on the basic KYC architecture, we see lack of data availability on consent architecture across FinTechs. Electronic consent architecture allows potential lender to access transaction records with banks and utilities that customers transact with and regulations can nudge banks to provide data in a sandbox model.

Exhibit 114: Consent architecture

Digital Consent Architecture (WIP) • Solutions that are aiding/Complementing Personal Data Exchange the digital infrastructure – IndiaStack, GST platform Ubiquitous Payments • For example alternative data credit bureaus, Verification Digilocker platforms etc.

Identity • These solutions have potential to become a India Stack layers critical part of the process flow of business models of GST Network startups & incumbents

Source: IDFC Securities Research, Transunion CIBIL and BCG

 Digital adoption to gain scale India is at the cusp of digital adoption scale, led by a growing economy and expected improvement in data/smartphone penetration. Expanding digital infrastructure in the form of data networks and government initiatives such as GST, Aadhar and IndiaStack allow for seamless digital delivery. Moreover, India has a growing heterogeneous consumption class that is fuelling demand.

 Favourable demographics As per IBM report, India currently has about 120m households who fall in the next billion category, whose annual incomes currently range between US$2300 and US$7000. Additionally, 40m households currently have annual income in the range of US$7700-US$15400. Both these segments are expected to witness a rise in consumption and by 2025, the next billion and the aspiring should have 140m and 61m households in each category, respectively. At an aggregate level, India currently has 64m households in consumption class that drive 54% of the total consumption spend, which is expected to grow to 110m by 2025E.

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Exhibit 115: India's consumption class # of households by income class

Elite (>$30,800) Affluent ($15,400 - $30,800) Aspirers ($7,000 - $15,400) Next Billion (<$2,300 - $7,000) Stuggler (<$2,300) 16 7 $1.2T 33 $2.7T Total household 17 Total household Consumption spend Consumption spend 40 61

64M 110M # of consumption 121 # of consumption class household 140 class household

54% 65% Of household spend 82 Of household spend from Consumption class 55 from Consumption class

2017 2025

Source: BCG, IBM, IDFC Securities Research

Rise in consumption led by better incomes will push a large number of users and households into the digital economy in future. Currently, India has 80m online users and 200m payment/recharge users, expected to increase to 220m and 500m, respectively.

Exhibit 116: India's digital class # of households by income class

220m 80m Struggler (<$2,300) Next Billion ($2,300 - $7,000) Online shoppers Online shoppers Aspirers ($7,700 - $15,400) Affluent ($15,400 - $30,800)

Elite (>$30,800) 16 7 33 17 200m 40 61 500m Payment/recharge users Payment/recharge users

121 140 250m Social media users 82 800m 55 Social media users

2017 2025 Source: BCG, IBM, IDFC Securities Research

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 Rise of big data in India Rising internet penetration is driving data explosion owing to digitisation and emergence of new sources of data is creating newer digital plays. India has been catching up with both in terms of time spent on internet and data consumption.

Exhibit 117: India's data consumption

3.2X 1.5-4hrs 90mins growth in mobile banking Total time spent average time spent transactions (2016-17) per day per month per user Digital payments Mobile Apps usage Mobile Apps usage

250million 250million total monthly highest no. of active users users globally

3X 20billion rise in total minutes messages on new year’s spent (2016-17) eve by 200m Indians Online entertainment Social media outburst

Source: IBM, IDFC Securities Research

Digital adoption across The rise of data is not only limited to individuals with even enterprises income classes presents a (both small and large) digitizing, led by efficiency, shift in consumer massive digital consumer preferences and government regulations (ex-GST). This could lead to large opportunity across influx of data of varied types, which will create opportunities for new segments models, in our view.

Exhibit 118: Traditional businesses adopting digital 30% CAGR gorwth in ecommerce market (2016-20) (~$100bn size by 2020)

2X 15% growth in public cloud Technology rise in enterprise software services market (2017-20) adoption spending (2017-18) ($1.9bn in 2017) (Compared to 9% globally)

~1.4X rise in industrial automation market (2017-20) (CAGR of 11.6%)

Source: IBM, IDFC Securities Research

Digital adoption across income classes presents a massive digital consumer opportunity across segments ranging from e-commerce, payments, social media and even financial services.

India’s online retail market has posted 70% CAGR (albeit over a smaller base) over last five years - fastest growth among the developing markets, although on a smaller base. That said, India’s online retail sales penetration is still low at 2%.

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Exhibit 119: Online retail spending Exhibit 120: Online retail spending (US$) Average online spending per online buyer (2017) Total ecommerce retail sales (2017) USD mn 2500 2,337 E-commerce retail % of total retail sales 2000 1,862 1000 25% Highest growth 23% in online 800 20% 1500 spending across 1,099 major economies 600 15% 1000 13% 400 10% 374 8% 500 224 161 200 5% 3% 0 2% 0 1% 0% US China Japan Brazil India Mexico US China Japan Brazil India Mexico Source: Bain, Forrester, IDFC Securities Research Source: Bain, Forrester, IDFC Securities Research

Exhibit 121: Large non-transactors Exhibit 122: First online transaction

(% of respondents) Transportation 100% (cab booking, etc.) Ticketing (cinema, 80% Travel events, etc.) (railway, bus, air, etc.) 60% Online finance and ransaction 40%

Online utility 20% bill payment

0% NCCS A & B/C (C5,C6) Source: Bain, Forrester, IDFC Securities Research Source: Bain, Forrester, IDFC Securities Research

 India financial services – A large potential digital opportunity While the digital economy will have an impact across sectors, retail, media and financial services would be most prone to digital adoption among all sectors. We have already seen strong adoption to TV on demand and e- commerce in India over last 3-5 years. However, most of the transformation in the financial services sector has been limited to shift digital banking and the payments segment to an extent. Despite being underpenetrated, the financial services sector is a large addressable market in India. In our view, technology-oriented financial services business models will both disrupt and democratise the financial services industry as a whole in India.

Exhibit 123: Digital impact by sector

Financial Telco services Logistics Retail IT/ITes Mfg. Healthcare (Process) Media Utilities Prof Agriculture Construct services ion Mfg. Education (Discrete) CPG Pharma

ImpactDigitalon Economy Mining

Digital Adoption

Source: IBM, IDFC Securities Research

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We are already seeing a shift in the age of incremental bank accounts. Citizens below the age of 35 now comprise 40% of new bank accounts opened versus 25% in FY12. This rapid shift is also visible in the market share of loans taken and preference of financial institutions. 40% of loan accounts are held by people under 35 and nearly 50% of loans taken in the 21-35 age groups have gone to NBFCs. In our view, this age bracket is more likely to experiment, look for premium customer experience and more willing to adopt newer business models.

Even the nature of retail credit in India, share of products in new accounts opened has evolved with gold loans and consumer durables gaining significant volumes and accounting for ~50% of all new accounts opened. As per FIBAC, there has been a drop in ticket sizes and even banks are adjusting to extend credit for lower-value assets.

Exhibit 124: Percentage share of institution in loans taken Exhibit 125: 40% of new account holders below 35 by 21-35 age group 26-35 Upto 25 >35 NBFC PSU Pvt Others 100 100 8 9 8 8 23 23 75 75 29 26 60 76 24 20 50 50 30 35 9 25 3 25 45 49 36 31 27 22 0 0 CY14 CY15 CY16 CY17E CY13 CY17*

Source: BCG, FIBAC, FICCI, IBA, IDFC Securities Research Source: FIBAC, CG, IDFC Securities Research

 The J-A-M trinity - creating the necessary digital infrastructure The J-A-M trinity, which is Jan Dhan account, Aadhar and Mobile phone for interconnect connectivity is creating the necessary digital infrastructure that provides a strong base for digital delivery of financial services. India is seeing strong growth in internet users and smartphone penetration, led by lower data prices and push from players like Jio for affordable devices. Jan Dhan is a powerful medium that brings the unbanked into the banking ambit and allows them flow of credit and other financial services. Finally, Aadhar is a unique digital identity that helps build the authentication layer.

Exhibit 126: Smartphone penetration Exhibit 127: Internet users

India Smartphone penetration Wireless Internet Subs (m) 29% 30.0% 450

21% 360 22.5% 17% 270 15.0% 11% 180 7.5% 5% 2% 90 1% 0.0% 0 2011 2012 2013 2014 2015 2016 2017 2014 2015 2016 2017 Source: UIDAI, IDFC Securities Research Source: UIDAI, IDFC Securities Research

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Exhibit 128: Aadhar statistics (m) Exhibit 129: Jan Dhan account snapshot

Jul-18 Jandhan Accounts (m) 1,400 1220 350 320 1098 1,050 280

210 188 700 132 302 140 350 70 0 Aadhar Cards Avg. Monthly Avg. Monthly e 0 Authentication KYC Rural/Semi Urban Total Urban Source: UIDAI, IDFC Securities Research Source: PMJDY, IDFC Securities Research

Exhibit 130: Aadhar authentication requests Exhibit 131: Aadhar eKYC requests Cumulative Aadhar Authentication (bn) Cumulative Aadhar eKYC (bn) 24.0 7.5

18.0 2.3x 6.0 2.2x 4.5 12.0 3.0 6.0 1.5 0.0 0.0 M a y - … M a y - … J u l - 2 0 1 8 J u l - 2 0 1 8 J a n - 2 0 1 8 J a n - 2 0 1 8 Jun-2018 Jun-2018 O c t - 2 0 1 7 O c t - 2 0 1 7 Mar-2018 Mar-2018 Apr-2018 Apr-2018 S e p - 2 0 1 7 S e p - 2 0 1 7 D e c - 2 0 1 7 D e c - 2 0 1 7 F e b - 2 0 1 8 F e b - 2 0 1 8 Nov-2017 Nov-2017 Aug-2017 Aug-2017 Source: UIDAI, IDFC Securities Research Source: UIDAI, IDFC Securities Research

 IndiaStack, J-A-M and technology reducing cost of delivery The implementation of IndiaStack coupled with the J-A-M trinity has helped reduce the cost of delivery, making it feasible for financial institutions to service the low-ticket segment. It is the cashless layer, which is meant to ease the process of digital financial transactions and reduce costs in addition to smoothening the entire process. Lower cost benefits derived from this can then be passed on to customers in the form of lower commissions and processing fees too. Based on BCG analysis, wealth management and savings account cost of service delivery is lower by 1/10th to 1/6th. IndiaStack thus makes end-to-end digital process feasible.

Exhibit 132: Reducing cost of service delivery Small ticket loans / MFI Savings account Wealth managment

Loan Customer Break even Customer Break even Addressable Disbursement acquisition MAB (Rs) acquisition investment market Cost (Rs) cost (Rs pa) cost (Rs) portfolio (Rs)

20 1,800 60K 1,500 200K 3M

Physical Physical Physical

1/4th 1/6th 1/10th

Aadhaar Digital Based (Fintech) APBS 5 300 10K 150 20K 30M

Source: FBAC, BCG, IDFC Securities Research

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 Current market dominated by banks; to be attacked by NBFCs/FinTechs The current lending market structure is dominated by banks. Areas inaccessible to banks in terms of reach and/or prohibited by high cost of delivery and service, tend to remain unbanked and this is a potential opportunity for tech centric FinTech companies.. We see banks facing immense competition from players like NBFCs, FinTechs, wallets and other third party intermediaries, once they begin to participate in revenue pools traditionally accessible only to banks. NBFCs have already begun to invade into the traditional lending segment. Moreover, performance of non-bank players in distribution of insurance & mutual fund product segments has been impressive.

Exhibit 133: Banking revenue pool Banking revenue pool (FY17)

(Rs bn) Bank Non-bank 1640 690 540 360 1060 310 300 410 700 290 50 30 0.1% 3% 9% 11% 22% 33% 34% 68% 78%

85%

99.9% 67% 91% 97% 78% 100% 100% 89%

66%

32% 22% 15% Deposits Retail MSME Agri Corporate Retail Transaction Other Insurance MF IB & Charges Banking Income DCM Processing Fee Advances Distribution Source: BCG, RBI, IDFC Securities Research

 SMB lending – Significantly underpenetrated India’s SMB segment, which employs ~40% of India’s workforce, contributes ~29%to national GDP, has ~45% share in manufacturing output and accounts for about 40% of India’s total exports, plays a significant role in India’s economy. Despite its size, the SMB segment is beset with many problems such as, highly unorganised and fragmented, supply chain inefficiencies, scalability and funding issues, etc.

Exhibit 134: Contribution of MSMEs in India’s economy at the current price Shared of Share of MSME Growth Year Total GVA MSME in Total GDP MSME in GVA (%) GVA (%) GDP (%)

2011-12 2,583,263 - 8,106,946 31.86 8,736,329 29.57

2012-13 2,977,623 15.27 9,202,692 32.36 9,944,013 29.94

2013-14 3,343,009 12.27 10,363,153 32.26 11,233,522 29.76

2014-15 3,658,196 9.43 11,481,794 31.86 12,445,128 29.39

2015-16 3,936,788 7.62 1,258,642 31.60 13,682,035 28.77

Source: Central Statistics Office (CSO), Ministry of Statistics & Programme Implementation, IDFC Securities Research

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Exhibit 135: Distribution of MSME in India

Other services Manufacturing 33% 31%

India has 64m MSMEs

Trade 36%

Source: Central Statistics Office (CSO), Ministry of Statistics & Programme Implementation, IDFC Securities Research

MSME numbers posted 7% CAGR over last 10 years. However, the shift has been towards services sector MSMEs incrementally.

Exhibit 136: MSME growth Exhibit 137: Mix towards services (2015 onwards)

No. of MSMEs (m) 68.0 63.4

Manufact 51.0 Services uring SME SME 36.2 45% 55% 34.0

17.0

0.0 Fourth All India Census NSS 73rd Round 2015-16 of MSMEs, 2006-07

Source: India MSME AR, IDFC Securities Research Source: India MSME AR, IDFC Securities Research

Uttar Pradesh had the largest number of MSMEs with the share estimated at 14.20% of MSMEs in India. West Bengal comes as a close second with 14% share. The top 10 states together accounted for 74.05% share of the total estimated number of MSMEs in the country.

Exhibit 138: MSME distribution by state

Number of SMEs by state 18.0 16

13.5 9 9 9.0 5 5 4 3 4.5 3 3 3 3

0.0 Bihar Others Gujarat Andhra Madhya Pradesh Pradesh Rajasthan Karnataka Tamil Nadu Tamil Maharashtra WestBengal

Uttar Pradesh Uttar Source: India MSME Annual Report, IDFC Securities Research

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 MSME(SMB) lending remains a significant white space Only 10% of the SMBs India’s MSME customer base remains highly underserved, with only 10% of having access to formal the SMBs having access to formal credit. Lack of data and high cost of credit credit delivery has primarily driven such low penetration rates. We expect the scenario to change, as SMBs digitise their businesses to drive efficiencies, more importantly led by regulatory compliance (ex- implementation of GST in India). Further, as discussed, the digital infrastructure (IndiaStack) too would allow companies to build data analytics, reduce cost of delivery and drive penetration.

Exhibit 139: MSME lending underpenetrated (m) No of MSME in India

51.1 48.8 46.8 42.9 44.8 Total number of MsME (51 m)

Nof current >90% account (40 m) Penetration gap

No of MSME borrowers (4.5 m) Total FY11 FY12 FY13 FY14 FY15 employees (m) 96 101 106 112 117

Source: FIBAC 2017, IDFC Securities Research

While 40m MSMEs have current accounts in India, there are only 4.5m MSME borrowers – implying massive under penetration.

Exhibit 140: India SMB - Large addressable market Total SME Lending Market Able/willing to (Rs trn) 35 Interest Rates address only Potential addressable Informal Lenders 30 24%+ top-end of credit gap: market 25 Rs20.46trn 20 Bulk of market 33.2 15 Unaddressed Interest Rates underserved 2.8 0.7 Market 16-24% by existing 10 financiers 12.7 5 9.2 0 SCBs NBFCs Other Total Total Interest Rates Model self- Banks/Govt Formal Addressable Banks/NBFCs 12-16% limiting to Institutes Supply Demand certain niches

Source: Niyogin, IDFC Securities Research

 FinTech and banks can work together The traditional banking ecosystem is already getting into a network with multiple players and has non uni-dimensional relationships with players across the ecosystem. Banks in the Indian context are already struggling with high NPAs and lack of credit growth. This is despite the fact that there are large sections of demand that remain underserved. The prime borrower category remains hotly contested and thus, opening of the higher yield market by FinTech companies can improve yields and ROEs for banks. The collaboration can come from either product or origination or distribution.

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Exhibit 141: Traditional banks moving into a network of players

Source: IBM, IDFC Securities Research

Others will need to think However the prori notion that ‘every bank’ needs to be at the center of about collaboration with financial services offered to customers, needs to be relooked at by banks. best in class players In our view, there will 5-6 large general population banks that can address the needs of customers while others will need to think about collaboration with best in class players. Collaboration can come from multiple dimensions - product innovation, distribution, capital allocation opportunity among a few. This would help companies expand their customer base and scalability into new businesses and markets. We think that smallers banks in India will be better off collaborating with the Fintech’s for customers and/or product delivery. As discussed in our earlier section about transactional banking model – Banks can leverage their strengths around Capital and partner with Fintech’s to participate in the new digital ecosystem.

Exhibit 142: Room for collaboration across dimensions

Source: IBM, IDFC Securities Research

 Hyper growth in India digital payments space India continues to prefer India has also seen hyper growth in the digital payments space. This has pre-paid instruments over been visible both in India’s shift from traditional physical paper banking credit cards transactions to digital transactions. A similar adoption is visible in shift and adoption of e-wallets. Demonetization by the government in 2016 to reduce the usage of cash in the economy, accelerated the adoption. We expect digital adoption to accelerate further, led by the adoption of prepaid instruments such as wallets.

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India continues to prefer pre-paid instruments over credit cards, as seen from the continued growth in debit cards and usage of debit cards at POS. Further, we expect the same trend to translate into m-wallets, which continues to see strong growth in India.

Exhibit 143: Debit cards constitute 90% of card volumes Exhibit 144: Healthy growth in debit card transactions

Debit card transaction volume % of total card Debit Cards transactions volume (m) transaction volume 14,000 94% 94% 11,907 93% 93% 10,841 92% 10,500 9,247 92% 91% 7,805 6,707 7,000 5,775 90% 89%

3,500 88%

0 86% FY13 FY14 FY15 FY16 FY17 FY18 FY13 FY14 FY15 FY16 FY17 FY18 Source: RBI, IDFC Securities Research Source: RBI, IDFC Securities Research

Merchants in India increasingly adopting POS terminal India has been seeing strong POS growth and in terms of usage, customers are reducing their usage of debit card for ATMs and opting for direct payments. This, in our view, is habit forming and suggests that Indians are increasingly more comfortable using electronic payments instruments over cash. The trend is evident, as merchants are increasingly accepting cards and installing POS terminals.

Exhibit 145: Number of POS terminals in India Exhibit 146: ATM usage of debit cards stagnating

Number of POS (m) Debit Card transactions at ATM (m) 40 10,000 35 8,537 8,589 8,073 7,500 6,996 30 6,088 5,308 20 20 5,000 15 12 13 9 10 2,500

0 0 FY13 FY14 FY15 FY16 FY17 FY18 FY13 FY14 FY15 FY16 FY17 FY18 Source: RBI, IDFC Securities Research Source: RBI, IDFC Securities Research

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The shift is visible in the adoption of pre-payment instrument (PPI) in India. The growth has accelerated post demonetization, with rising internet and smartphone penetration continuing to push through the adoption.

Exhibit 147: Volumes in pre-paid instrument transactions Exhibit 148: Value of pre-paid instrument transactions

Prepaid Payment Instruments transactions (m) PPI transaction value Rs bn 4,000 1,600 3,459 1,416

3,000 1,200

1,963 836 2,000 800 488 748 1,000 400 213 314 67 134 79 81 0 0 FY13 FY14 FY15 FY16 FY17 FY18 FY13 FY14 FY15 FY16 FY17 FY18

Source: RBI, IDFC Securities Research Source: RBI, IDFC Securities Research

Exhibit 149: M-wallet transaction volume Exhibit 150: M-wallet transaction value

m-Wallet transactions (m) M-wallet transaction value in Rs bn 3,056 3,200 1,200 1,087

2,400 900 1,630 1,600 600 532

800 604 300 206 255 82 33 108 10 29 0 0 FY13 FY14 FY15 FY16 FY17 FY18 FY13 FY14 FY15 FY16 FY17 FY18

Source: RBI, IDFC Securities Research Source: RBI, IDFC Securities Research

Mobile wallet used for small ticket transactions M-wallets remain the most As per a Deloitte report, 69% of the total mobile wallet market constituted preferred PPI (after debit money transfer and bill payments in 2017. The remaining 31% included cards) in India online shopping for clothes, electronics, food, etc. and reservations for hotels, entertainment and transport. Average ticket size for a mobile wallet transaction in FY17 was Rs327 versus Rs2,506 for cards. Mobile wallet transactions comprise mainly of money transfers and recharge & bill payments.

M-wallets remain the most preferred PPI (after debit cards) in India. We note, m-wallets constituted 88% of total PPI transaction volumes in India.

Exhibit 151: M-wallet transactions as a percentage of PPI transactions

M-wallet transactions as a % of PPI transactions 100% 88% 83% 85% 80% 81% 81%

70%

55% 49%

40% FY13 FY14 FY15 FY16 FY17 FY18 Source: BCG-Google, IDFC Securities Research

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Exhibit 152: Mobile payment volumes Exhibit 153: Cash payments to trend down Mobile payments Volume Some estimates have non-cash overtaking (Number of Transactions in billion) cash payments

(%) Cash Non-cash 92 89 78

60 59 460 40 22 41 11 2.9 8

2016 2022E 2005 2010 2015 2020E 2025E

Source: Axis Bank, IDFC Securities Research Source: Axis Bank IDFC Securities Research

 Regulatory environment favorable in India The Indian government’s push towards a digital and cashless economy has been well documented. Demonetization in 2016 and regulations around KYC supported adoption of the payments industry.

The following changes in regulations aided adoption of wallets

• Aadhar eKYC streamlined the KYC process for companies • Exemption from Two-Factor Authentication (2FA) – Card usage in India needs to go through a 2FA process, which wallets are exempted from. The user needs to go through the 2FA when loading the cards, which makes the payment process seamless in case of wallets versus cards • Unified Payments Interface (UPI) – UPI is a system that powers multiple bank accounts into a single mobile application (of any participating bank), merging several banking features, seamless fund routing & merchant payments into one hood. It also caters to the P2P collect request, which can be scheduled and paid as per requirement and convenience.

National Payments Corporation of India (NPCI), an umbrella organization that operates retail payments and settlement systems in India, is an initiative of the Reserve Bank of India (RBI) and Indian Banks’ Association (IBA) under the provisions of the Payment and Settlement Systems Act, 2007, for creating a robust Payment & Settlement Infrastructure in India.

Exhibit 154: Use cases of Digital payments

Prepaid recharge still the Metro Users Non Metro Users largest use case across 80 73 metro and non-metros 66 Bill payment POS payment and second largest usage for other 55 services low 60 1021 51 use case

36 40 31 31 29 28 102129 22 22 18 20 20 14 16

0 Prepaid Mobile bill Other utility Ecommerce Travel Fund transfer in store (POS) other services mobile payment bills booking recharge

Source: BCG-Google, IDFC Securities Research

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Exhibit 155: Number of use cases per user Exhibit 156: Frequency of usage

No of use cases per month Frequency of usage per month 3.5 3.2 8.6 2.7 2.8 8.2 2.2 8.2 2.1 7.8 7.7 1.4 7.5

0.7 7.4

0.0 7.0 All Metro Non-Metro All Metro Non-Metro

Source: BCG-Google, IDFC Securities Research Source: BCG-Google, IDFC Securities Research

 Hyper competition makes us cautious on India profitability Indian market remains Payment is generally one of the first sub-segment to be taking off, as the hotly contested in economy shifts from brick-and-mortar to digital. As users transact for payments and highly products and services online, there is a need to deliver payments online. populated with both bank However, we think the Indian market remains hotly contested and highly and non-bank players populated with both bank and non-bank players. Globally, pricing power in the payments space is solid and/or is helped by an internet-closed ecosystem that some of the players such as Alibaba or Tencent have been able to create. This, in our view, is missing in India. Moreover, ccompetitive intensity among the top players in the industry is increasing as well. In September 2016, PayU acquired Citrus Payments for US$130m. This deal allowed PayU to add 30m users. Axis Bank acquired Freecharge for Rs3.85bn.

Further, we note government’s focus and push for a cashless economy has led to the emergence of new payment gateways such as UPI and Bharat Interface for Money (BHIM), which have taken down the pricing in order to promote adoption. This makes it difficult for payment platforms and gateways to price their service competitively.

Exhibit 157: Applications of NPCI

Bharat Interface for Money (BHIM) is an app that lets you make simple, easy and quick payment BHIM transactions using Unified Payments Interface (UPI). You can make instant bank-to-bank payments and Pay and collect money using just Mobile number or Virtual Payment Address (UPI ID

Unified Payments Interface (UPI) is a system that powers multiple bank accounts into a single mobile application (of any participating bank), merging several banking features, seamless fund UPI routing & merchant payments into one hood. It also caters to the “Peer to Peer” collect request which can be scheduled and paid as per requirement and convenience

For transferring funds real time and 24X7X365 interbank was a major challenge faced in banking IMPS industry. Only NEFT & RTGS were available to user for fund transfer during banking hours

The Bharat bill payment system is a Reserve Bank of India (RBI) conceptualised system driven by National Payments Corporation of India (NPCI). It is a one-stop ecosystem for payment of all bills Bharat Billpay providing an interoperable and accessible “Anytime Anywhere” bill payment service to all customers across India with certainty, reliability and safety of transactions

Source: NPCI, IDFC Securities Research

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India FinTech – A US$1trn opportunity Massive underpenetration We believe growth in the Indian economy will continue to cause a shift in in MSME segment the revenue pool of the banking sector. BCG estimates banks aggregate revenues ‘to move in line with their historic growth of ~11%, as the mix across segments would continue to shift towards retail and MSME advances. We believe FinTech’s could participate and build a share in the revenue pool on their own, or through collaboration. Breakdown of the cost structure in a digital economy should lead to large market expansion for financial services in India.

Exhibit 158: India consumer debt to GDP

120% 100% 87% 90% 79%

57% 60% 48%

25% 30% 16% 11%

0% Canada UK USA Japan China Brazil Russia India Source: IBM, IDFC Securities Research

Exhibit 159: Large opportunity for Fintech’s due to lower cost of delivery Current average size of personal loan for banks is 2,00,000 INR 1,000 1.25% of INR 2,00,000 Loan Avg cost of customer Acquisition INR 2,500 + = This cost escalates even more INR 1,500 7.2% of INR 35,000 Loan as one goes down the income Avg. Cost of Servicing pyramid But an eligibility of an average middle-class Indian earning 15,000 per month is ~35,000

Source: IBM, IDFC Securities Research

Exhibit 160: Revenue pool across segments FY17 (Actual) FY22 (Projected) 25% 43% 32% 24% 41% 35%

Term Retail Retail Term Retail Retail 17% 28% 29% charges & 16% 35% 29% charges & proc fee proc fee

Savings MSME Savings MSME 48% 20% TxB 56% 24% TxB 20% 20% Agri 13% Distribution Agri 14% Distribution 16% 19% 0.15% DCM 0.3% DCM Current Corporate 34% Current Corporate 32% 34% 39% Other 27% 27% Other income income Deposits Advances Fee / Other Deposits Advances Fee / Other ~161 ~274 income ~266 ~460 income ~650 ~208 ~1,100 ~308 (CAGR ~ 11%) (CAGR ~ 11%) CAGR 10% 10% 12% CAGR 11% 10% 13%

Source: BCG, FIBAC, IDFC Securities Research

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MSMEs in India have 40m current accounts but, the number of MSME borrowers are only 4.5mn – implying massive underpenetration in the segment. We believe this opens up Rs20trn unaddressed opportunity in the MSME segment alone.

Exhibit 161: India SMB - Large addressable market (Rs trn) 35 Potential addressable credit gap: 30 Rs20.46trn

25

20 33.2 15 2.8 0.7 10 12.7 5 9.2 0 SCBs NBFCs Other Banks/Govt Total Formal Total Addressable Institutes Supply Demand Source: Niyogin, IDFC Securities Research

SMB a large addressable market Both (consumer and SMB) these put together create a large addressable market opportunity of US$1trn over the next 5 years. Unlike most other internet-centric business models, a lending-centric model won’t be a winner takes all kind of market. We do think there is room for multiple players to grow and scale given a very large addressable market.

Exhibit 162: India consumer lending Middle of pyramid (US$bn) Total consumer loan (US$bn) Consumer lending market size (US$ bn) 4,000 600 3,000 30 1200 2,000 280

1,000 2017 2025

0 2017 2025 Source: Company, IBM, IDFC Securities Research

Exhibit 163: India digital lending opportunity

Digital Lending (US$ bn) 400 350

300 270

200 200 150 110 75 100 58 33 46 9 14 23 0 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 Source: BCG, Company, IDFC Securities Research

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 Payments – A US$500bn market but hotly contested PPIs will register 40% The mobile wallet industry is expected to maintain its pace of expansion. CAGR over the next 5 As of FY18, digital (card+PPI) constituted US$619 of transaction in value years to US$1bn by terms, with cards comprising a majority of it. However, in terms of volume FY2023E of transactions, PPI gained a higher share, suggesting that customers are shifting towards PPI for small-ticket transactions. As penetration of mobile internet and smartphones aggregate, mobile wallets with their ease of use & convenience will continue to grow in popularity.

Exhibit 164: Payment mix in major markets

Card Digital Cash Other 2% 100% 2% 4% 1% 13% 25% 75% 24% 44% 47% 14% 15% 78% 50% 13% 27% 59% 25% 49% 39% 25% 13% 0% 7% US UK Brazil China India

Source: BCG-Google, Euromonitor Passport 2015, IDFC Securities Research

Exhibit 165: Total digital transaction value (Cards+PPI) Exhibit 166: Total digital transaction volume (Cards+PPI)

Cards PPI Card transaction (m) PPI (m) 640 22 18,000 3,459

480 8 12 13,500 1,963 3 1 748 320 596 9,000 314 134 459 450 13,327 397 11,934 160 346 4,500 10,039 7,219 8,424

0 0 2014 2015 2016 2017 2018 2014 2015 2016 2017 2018

Source: RBI, IDFC Securities Research Source: RBI, IDFC Securities Research

Exhibit 167: Digital transaction mix

PPI transaction volume mix 24% 21%

18% 14%

12% 7% 6% 4% 2%

0% 2014 2015 2016 2017 2018 Source: RBI, IDFC Securities Research

PPIs, currently valued at US$22bn have posted 100% CAGR over FY14- FY18, which we estimate will register 40% CAGR over the next 5 years to US$1bn by FY2023E.

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Exhibit 168: What constitutes PPPI Exhibit 169: Transaction value mix within PPI Pre-payment instruments PPI cards Paper 22% vouchers m-Wallets 1% PPI cards Paper vouchers

m-Wallets Source: RBI, IDFC Securities Research 77%

Source: RBI, IDFC Securities Research

Exhibit 170: India PPI estimates

Value of Pre-payment instruments (US$ bn - LHS) yoy growth (% - RHS) 140 180% 121

105 89 135%

66 70 90% 48 34 35 22 45% 12 3 8 0 0% 2015 2016 2017 2018 2019E 2020E 2021E 2022E 2023E Source: RBI, IDFC Securities Research

Companies will look to build on payments customer base Payments form the core of Payments form the core of all customer transactions and are generally the all customer transactions first service that customers use and are most frequently engaged with. We expect rising internet penetration to drive the adoption of payment services platform, with companies looking to enhance customer engagement and sell multiple services - a key value driver for the payment platform.

Exhibit 171: Payment at the core of online ecosystem

Source: BCG-Google, Euromonitor Passport 2015, IDFC Securities Research

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Exhibit 172: Paytm leading the integrated ecosystem push

Source: Paytm, IDFC Securities Research

 India’s FinTech landscape mushrooming with players across segments We expect to see the rise India may not have achieved the scale of US and China in FinTech, but of India’s FinTech players opportunities galore. Further, as India trails these markets in terms of across verticals once smartphone adoption, we expect to see the rise of India’s FinTech players density improves across verticals once density improves. There has been a proliferation of FinTechs addressing nearly all segments and each has either raised or are in process of raising growth capital. This makes at least the company landscape fairly populated across the space, but we are yet to see many scale-up – except the payments space, where players such as Paytm have scaled up sizably.

As per KPMG, India FinTech is moving from a nascent to emerging stage, based on parameters such as regulatory support, business environment, funding and technology and readiness, among others.

Exhibit 173: India’s FinTech landscape Exhibit 174: FinTech landscape in the US Entrepreneurial & Entrepreneurial & Innovative mindset Innovative mindset

Government incentives Government incentives

Technology readiness Technology readiness

Regulatory support Regulatory support

Business environment Business environment

Funding Funding

Nascent Emerging Mature Nascent Emerging Mature

Source: KPMG, IDFC Securities Research Source: KPMG, IDFC Securities Research

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India FinTech

Exhibit 175: India FinTech landscape

Incumbents Disruptors

Direct Bank Debit Transfer System Visa • Paytm • FINO Paytech Mobile Payment • Simpl Mastercard • Mobikwik Solution Mswipe • Freecharge Banks •

PAYMENT • UPI Payment Service Provider

Personal Lending • Niyogin • ApolloFinvest • Capital Float Banks • Incred SME Lending • LendingKart NBFCs • Neogrowth • Faircent • Avail Finance

FINANCING • Dhani Crowd - Funding

Online Saving Platform

Banks • PolicyBazaar • Cleartax Online Asset Management • Zerodha • Coverfox Retail brokerages • Bankbazaar • Perfios SAVING/

INVESTMENT Online-only Bank

Cloud Computing

• Digit • Creditseva Personal Credit • Heckyl Scoring Transunion CIBIL • Digio • Unocoin • InCights OTHERS Online-only insurance Company Source: IDFC Securities Research, Company

 Business model – Back the channel strength We expect multiple business models to emerge, given the large-scale of opportunities in the financial services market. We suggest investors look at the business models rolled into 3 key segments

1) Product - Does the product seamlessly solve a painful problem?

2) Pricing and market size- Enough revenue to generate attractive returns?

3) Distribution channel - Does the distribution channel densely contain the target audience ?

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Exhibit 176: Business trinity

Source: IDFC Securities Research

 Look for business models with strong channels Companies with strong In our view, the product demand, under penetration and market size, are customer relationships fairly established and/or easy to assess in companies for investors. and sound distribution will However, we do think there will be product innovators on the lending have better credit- front, but money as such is a commoditised product. Thus we believe decisioning capabilities business models with channel strength should deliver superior returns for customers. The quality of distribution channels, defined by control of the channel and the depth of customer relationship, would be big differentiators in a business model. This will be a critical driver for a business model’s ROE and capital efficiency. Further, companies with strong customer relationships and sound distribution will have better credit-decisioning capabilities, and would be able to attract more partners either for product or for capital.

Exhibit 177: Channel – Customer ownership a huge driver for ROE

Channel Density Marketing efficiency

• A dense distribution channel drives • Customer acquisition easier marketing efficiency • Lower CAC

Cross-selling Customer ownership

• Ownership drives ability to cross sell • Higher capital efficiency • Enhances LTV • Ability to attract partners • Product penetration RoE accretive

Source: IDFC Securities Research

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While we see payments as a large opportunity, yet, it would be difficult for multiple players to deliver returns and will continue to be a loss leader. Further, unlike lending, where we think there is room for multiple players, payments might be more of a ‘winner takes all’ market. While there would exist segmentation between retail and enterprise, competition would also be high. Here again, we think returns would depend not on payment as a product, but more on the ability to retain the customer and drive returns through cross selling.

Niyogin Fintech– An attractive business model On the channel front, MSME in India remains an underpenetrated category given high cost of Niyogin is uniquely customer acquisition, limited credit history and lower ticket size products positioned for large banks. Niyogin has a technology-centric service delivery model that builds a scalable technology and data platform for MSME business. The user interface (UI) interface has been built with a mobile first approach, as well as established partnerships for core banking systems and decisioning engine. On the channel front, Niyogin is uniquely positioned, as the company uses Information Interface India Pvt. Ltd (3i) network, which has professionals in its ambit.

3i leads processing treasury transactions in India and is a partner of choice for most multinational financial firms such as Bank of America, Citi, HSBC, Deutsche Bank, among others. 3i is one of the largest independent financial distribution platforms in the country with presence in 340 cities, a network of 2,500 professionals and a client base of over 20,000.

Niyogin ticks the box on 1) Product, 2) market size and 3) Strong channel.

Exhibit 178: Niyogin – Strong channel

Source: IDFC Securities Research

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ANNEXURE

 What is an IoT? IoT is a system of interrelated computing devices, mechanical and digital machines, objects, animals or people that are provided with unique identifiers and the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction.

IoT The building blocks of IoT IoT comes to life when its multiple building blocks simultaneously operate and communicate with each other:

Application and user interaction Collaboration involving people, applications and business processes

Cloud Server Computing systems/platforms such as enterprise and cloud with real-time processing and data analytics capacity, storage and content delivery, application hosting

Network (connectivity) Internet access: wireless/wired, Wi-Fi, Bluetooth, ZigBee, VPN, Cellular 2G/3G/4G

Gateway Communication standards and protocols that enable connectivity down to the sensors and up to the network

Physical objects and devices Objects and equipped with sensors and actuators and thus given the ability to emit, accept and process signals • Sensors: Convert information from the physical environment into a signal • Actuators: Act on the signal form the sensors and convert it into output

Source: Company, IDFC Securities Research

IoT has already started seeing deployments in market like China and with fabless chipset players working on innovative chipsets, the market for cellular IoT connections is expected to expand sharply. As per Ericsson, IoT connections are expected to touch 3.5bn by 2023 (0.7bn currently) with North Asia accounting for 2.2bn connections.

New massive IoT technologies are evolving such as NB-IoT and Cat-M1) are taking off. These technologies effectively support a low power wide area network use cases build on an underlying LTE network.

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 What is NB-IoT technology? NB-IoT is a new wireless technology that was standardized by 3GPP in 2016. It is fast emerging as the best in class LPWAN technology to enable a wide range of new Industrial IoT (IIoT) devices including smart parking, utilities, wearable, and industrial solutions. This is because, the technology has the ability to efficiently connect a large fleet of devices, up to 50,000 per NB-IoT network cell, while minimizing power consumption and increasing coverage range in locations not served by conventional cellular technologies.

What are the business benefits? 1. Power Efficiency Efficiently powering IoT devices is critical. Think about it - who wants to be out there changing the batteries on 20bn devices every six months? While nearly all IoT technologies are developed to save power when they aren’t operating, they do draw energy when the modem is running and handling signal processing.

2. Cost Savings Technologies with simpler waveform — like NB-IoT — will consume less power. A 200 kHz NB-IoT frontend and digitizer offers reduced complexity of analog-to-digital (A/D) and digital-to-analog (D/A) conversion, buffering, and channel estimation. Power savings = cost savings. Plus, NB-IoT chips will be simpler to create and thus come cheaper.

3. Reliability Rolling out NB-IoT on a licensed spectrum means improving reliability for users as well as the guaranteeing resource allocation needed for managed Quality of Service (QoS).

4. Wider deployment Compared to LTE-M1, NB-IoT has lower bitrates and better link budgets. Additionally, as per Huawei’s Emmanuel Coehlo Alves in an IoT Hub article, NB-IoT doesn’t need gateways to provide connectivity. Instead of “creating another piece of equipment you need to manage and operate,” he said, “NB-IoT can directly connect sensors to the base station. This can boost flexibility while lowering costs”.

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 What is Cat-M1 technology?

Source: RIL, IDFC Securities Research

 What is LTE Cat M1? LTE Cat M1 is a low-power wide-area (LPWA) air interface that lets you connect IoT and machine-to- machine (M2M) devices with medium data rate requirements (375 kb/s upload and download speeds in half duplex mode). It enables longer battery lifecycles and greater in-building range, compared to standard cellular technologies such as 2G, 3G, or LTE Cat 1. Key features include:

• Support of voice functionality via VoLTE • Full mobility and in-vehicle handover • Low power consumption • Extended in-building range

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LTE Cat M1

Voice support via VoLTE

LTE Cat M1

Low power Extended range and consumption with deep penetration battery life of in buildings and basements 5+ years

Full Mobility and in-vehicle hand-over

Source: Company, IDFC Securities Research

Infra of LTE Cat M1

Smart Buildings

Smart cities LTE Automotive & Cat Transportation M1

Smart Metering Connected Health

Source: Company, IDFC Securities Research

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 Use cases of LTE Cat M1 Automotive & transportation LTE Cat M1 supports full handover between network cells from a moving vehicle and is therefore well-suited for mobile use cases with low to medium data rate needs, such as vehicle tracking, asset tracking, telematics, fleet management and usage-based insurance.

Smart metering Cat M1 is also ideal for monitoring metering and utility applications via regular and small data transmissions. Network coverage is a key issue in smart metering rollouts. Since meters are commonly located inside buildings or basements, Cat M1's extended range leads to better coverage in hard-to-reach areas.

Smart buildings Cat M1 can easily provide basic building management functionality, such as HVAC, lighting, and access control with its enhanced indoor range. Since it also features voice functionality via VoLTE, it is also well-suited for critical applications like security systems and alarm panels.

Connected health Due to its extended in-building range, voice support, and mobility, Cat M1 is also a well-matched air interface choice for connected health applications, such as outpatient monitoring and stay-in-place solutions.

Smart cities Within smart cities, Cat M1 can meet a variety of needs and effectively control street lighting, determine waste management pickup schedules, identify free parking spaces, monitor environmental conditions, and survey the condition of roads in a matter of milliseconds.

China has selected NB-IoT technology for nationwide deployment and this is supporting smart cities and smart agriculture. However, North America is still deploying Cat M1. Overall, large scale deployments of these technologies will keep pushing down chipset prices and accelerate adoption and use case for IoT.

Cellular IoT connections per region (billion)

Source: RIL, IDFC Securities Research

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 Mobile case study on NB-IoT electric smart meter deployment China Mobile has developed NB-IoT smart metering and partnered with the State Grid Electric Power Research Institute and Provincial Metrology Institute to deploy and test the NB-IoT connected smart meters in the field. 200 NB-IoT smart meters have been deployed by China Mobile in a number of cities in co-operation with State Grid Corporation of China (CEPRI) in Yingtan, Wuxi, Zhuhai, Chengdu, Chongqing and Beijing. Using 2G or 4G network, the China Mobile AMR service today is able to collect real-time voltage, current, power consumption and other information from the meters. Through big data analysis, the actual electricity consumption of each device can be assessed, allowing an effective electricity supply.

Benefits • Simplification: Compared to existing meter reading services available to Chinese utilities, the NB-IoT smart meters are much simpler to install and operate.

• Network Coverage: NB-IoT is designed to offer enhanced coverage over existing mobile networks. • Deployment: As NB-IoT coverage is already in place, there are no restrictions on how the smart meters are rolled out. This means coverage planning is not required, which makes rollout planning more straightforward. • Data Security: NB-IoT is designed to be secure. It operates in licensed spectrum, meaning that interference from other networks is avoided and quality of service can be assured based on 4G networks.

 Conclusion It has proven that NB-IoT technology is a very good fit to the demands of China Mobile’s AMR solution and wider smart metering connectivity. This technology offers high quality of service, essential for operation of critical national infrastructure such as smart meters and grids and a wider network coverage to connect.

Source: GSMA Mobile IOT CSe Study Report on Greater China Mar 2018

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 How much data are we generating? Domo estimates that 90% of the data in the world today has been created in last two years alone. Current output of data is roughly 2.5 quintillion bytes a day. This is likely to grow as the world becomes more connected with an ever-increasing number of electronic devices and IoT.

Data generation

Source: Domo, IDFC Securities Research

The recent explosion of the so-called ’sharing economy’ has been astronomical. Airbnb and Uber have become household names. Data has been a big driver for successful execution of such business models. Over the past decades, massive data sets of information created by internet has made sharing economy not only infinitely more efficient, but also extremely lucrative for mediator startups that have used this data to build their businesses.

Sharing economy has huge implications for traditional companies operating in Industries being disrupted by data-centric technology companies.

 How is Marriot improving its asset monetization? Marriott’s Workspace on Demand website uses a partnership with the start-up, LiquidSpace, to maximize the value the company and consumers can extract from the hotel chain’s unused conference rooms and public spaces. Using the site, people can book nearby meeting spaces by the hour — and some of them are even free. While traditional companies are sometimes burdened by all of the capital they possess, these holdings can be turned into an advantage if data is used strategically to unlock previously unrealized value from capital that bears excess utility

Source: Domo

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 What is a data lake? A data lake is a shared data environment that comprises multiple repositories and capitalizes on big data technologies. It provides data to an organization for a variety of analytics processing, which include: • discovery and exploration of data • simple ad hoc analytics • complex analysis for business decisions • reporting • real-time analytics Organizations are increasingly exploring the data lake approach to address the demand for an agile yet secured and well-governed data environment that would support both structured and unstructured data.

 A Data Lake is • An environment where users can access vast amounts of raw data • An environment for developing and proving an analytics model, and then moving it into production • An analytics sandbox for exploring data to gain insight • An enterprise-wide catalogue that helps users find data and link business terms with technical metadata • An environment for that enables the reuse of data transformation and queries

 A Data Lake is not • A data warehouse or data mart for housing all of the data in an enterprise • A replacement operational data store (ODS) • A high-performance production environment • A production reporting application • A purpose-built system to solve a specific problem (though a purpose-built data mart could be fed from a data lake)

There is a vital distinction between data lake and data warehouse. Data lake stores raw data in whatever form that data source provides. There are no assumptions about the schema of the data, with each data source using whatever schema it likes. It is upto the consumer of that data to make sense of that data for its own purpose. The complexity of this raw data means that there is room for something that curates the data into a more manageable structure (as well as reducing the considerable volume of data.). Ideally, data lake shouldn't be accessed directly. Few data scientists filter information and a larger number of downstream users can then treat these lakeshore marts as an authoritative source for that context.

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Data Lake Operational systems communicate with each other via services connections, ignoring the data lake

Operational systems feed data into the lake using their own schemas

Lakeshare marts curate A few data scientists and organize the data investigate the lake for most analytics uses for potential insights

Source: Martinflower, IDFC Securities Research

Compute capability continues to progress at a rapid pace and this has been the key driver for some of the progress that we see in areas of analytics and our ability to process large amounts of data rather quickly. Though performance drivers are flattening out, supercomputing continues to hit new milestones. The next one on the list is exascale computing – and at that level, machines will be capable of a million- trillion calculations a second. All these advances are pushing us closer to a major symbolic milestone - computers that would be as powerful and complex as the human brain.

Compute

Source: Visualcapitalist, IDFC Securities Research

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We think dropping costs of storage and compute should allow companies to build data lakes and capture data for analytics in a rather cost-efficient manner. This would open up room for AI and machine learning (ML) applications. We see there is a lot of training time going into providing accurate results through AI and ML. The amount of compute used in the largest AI training runs has been increasing exponentially, with a 3.5 month-doubling time (in comparison, Moore’s Law had an 18-month doubling period). Since 2012, this metric has grown by more than 300,000x (an 18-month doubling period would have yielded mere 12x increase). Improvements in compute have been a key component of AI progress, so as long as this trend continues, it’s worth preparing for the implications of systems far outside today’s capabilities.

AI training compute

Source: OpenAI, IDFC Securities Research

Based on BCG analysis, ML can drive tremendous efficiency for document identification, classification and data extraction. Companies can deliver an automation rate of about 70%, an efficiency gain of 56% over humans after training on 3,000 samples.

ML efficiency curve

Source: BCG, IDFC Securities Research

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 How much compute got first humans to the moon? On 20 July 1969, millions of people received an inspirational jolt from watching two brave astronauts take humankind’s first steps on the moon.

The Apollo Guidance Computer (AGC) was a digital computer produced for the Apollo program that was installed on board each Apollo Command Module (CM) and Lunar Module (LM). The AGC provided computation and electronic interfaces for guidance, navigation, and control of the spacecraft.

With processing power equivalent to a pair of Nintendo consoles, the AGC wasn’t flashy. But despite its technical limitations, AGC functioned admirably as the interface for guidance, navigation, and control of the spacecraft to get humans to their first lunar destination.

Processing power of Apollo guidance computer versus Nintendo

Source: Company, IDFC Securities Research

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 India handset affordability We also have to focus on supply and demand scenario in the smartphone market. On the supply side, there are factors related to manufacturing, inbound and outbound supply chains and exchange rates that can impact device pricing. On the demand side, drivers include peoples’ ability to pay, their value perception of the device to justify the expenditure - coupled with levels of awareness and understanding of the total cost. On the demand side, issues are usually associated with consumers‘ ability and willingness to pay for smartphones.

Supply and demand factors of smartphones

What drives affordability of smartphones?

Supply / Price Demand / Willingness and ability to pay

COST Ability to pay Manufacturing costs • Income and wealth (e.g. assets / livestock that can be traded) • Hardware (e.g. cost of chip, screen, battery) Access to credit • Software (e.g. operating system, preinstalled • applications, etc.) • Alternative sources of income (e.g. family, third- • Packaging parties, etc.) • Customisation Willingness to pay Content and relevance Inbound supply chain • Business use case • Import taxes/duties o Social / community use case • Transport (emerging markets in Africa especially o high cost) Personal use case (usefulness, justify use) o • Storage / Warehousing and inventory • Community influence management Social norms o • Delivery Status o Outbound supply chain and distribution • Awareness/know-how costs (via agents, retailers, online) • Safety (e.g. concerns of online harassment, • VAT misuse of personal images/data) • Transport • Trust in handset quality/authenticity • Storage • Perceived need • Damages and liabilities Access via other means (sharing handsets, o • Commissions and mark-ups use at work, etc.) Advertising & marketing Being gifted handset (no need to buy) o PRICING DECISIONS Ability and willingness to pay is influenced by a Business decision about mark-ups number factors including, age, geographies, gender, education, urban/rural pricing (e.g. share of overheads attached to devices) Understanding of the total cost Manufacturer suggested pricing • Actual handset cost • Acquisition cost (e.g. transport and time) • On-going cost (e.g. data, maintenance and access to power)

Source: Company, IDFC Securities Research

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 India - Handset market Handset ecosystem and better devices are key to strong digital adoption in India. India currently has 1bn wireless subscribers and annual handsets. However, India still remains one of the largest feature phone shipment markets. Despite the correction in data pack price, smartphone penetration has been rather slow. We expect continued deflation in prices of handsets to certainly shift the larger market towards data phones. Jio, through its Jio-Phone offerings, is reducing the entry barriers.

What’s an affordable smartphone in India!

Source: Company, IDFC Securities Research

Average price of smart phone is falling from 2012 to 2017 (US$) 2012 2017 -43% 320 -32% -36% -52% -37% -27% 240 -32% -45% -44% -35% -14% 160 318 276 296 245 240 249 207 209 211 178 200 181 187 181 80 145 152 140 115 118 121 125 117

0 Brazil Colombia India Indonesia Kenya Mexico Nigeria Pakistan Tanzania Venezuela Vietanam Source: Company, IDFC Securities Research

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Phone specifications General Xiamoi X1s Jio Phone Micromax X78 Release date Aug-18 Jul-17 Nov-11 Form factor Bar Bar Slider Dimensions (mm) 132.00 x 53.80 x 8.50 - 106.00 x 57.00 x 15.00 Battery capacity (mAh) 1480 2000 950 Removable battery No Yes Yes Colours Black, White Black Black, White Weight (g) - - 140 Display Screen size (inches) 2.8 2.4 2.8 Touchscreen Yes No Yes Resolution 240x320 pixels 240x320 pixels 240x320 pixels Pixels per inch (PPI) - - 143 Hardware Processor dual-core 1.2GHz dual-core - SPRD Processor make Spreadtrum SC9820E - 9820A/QC8905 RAM 256MB 512MB - Internal storage 512MB 4GB - Expandable storage No Yes Yes Expandable storage type - microSD microSD Expandable storage up to - 128 8 (GB) Connectivity Wi-Fi Yes Yes Yes GPS Yes Yes No Bluetooth Yes, v 4.20 Yes, v 4.10 Yes, v 3.00 Number of SIMs 2 1 2 NFC - Yes No Infrared - No No USB OTG - No No Headphones - Yes 3.5mm FM - Yes Yes Sim 1 SIM Type Nano-SIM Nano-SIM Regular GSM/CDMA GSM GSM GSM 3G Yes No No 4G/ LTE Yes Yes No Sim 2 SIM Type Nano-SIM - Regular GSM/CDMA GSM - GSM 3G Yes - No 4G/ LTE Yes - No Camera Rear camera - 2-megapixel 3.2-megapixel Front camera - 0.3-megapixel No Rear Flash - - LED Software Operating System - KAI OS Proprietary Skin - - NA Source: Company, IDFC Securities Research

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GLOSSARY

Glossary Meaning LTE Long Term Evolution- A 4G mobile communications standard Internet of Things is a system of physical things embedded with sensors, software, electronics and IoT connectivity to allow it to perform better by exchanging information with other connected devices, the operator or the manufacturer Voice over Long-Term Evolution is a standard for high-speed wireless communication for mobile VoLTE phones and data terminals - including IoT devices and wearable Network Functions Virtualization is a network architecture concept that uses the technologies of NFV IT virtualization to virtualize entire classes of network node functions into building blocks that may connect, or chain together to create communication services AR Augmented reality is the integration of digital information with the user's environment in real time. Virtual Realty - An artificial environment, which is experienced through sensory stimuli (such as VR sights and sounds) provided by a computer and in which one's actions partially determine what happens in the environment NarrowBand-Internet of Things is a standards-based low power wide area (LPWA) technology NB-IoT developed to enable a wide range of new IoT devices and services Cat M1 is a technology that functions on a 1.4 MHz (reduced from 20 MHz) spectrum, has a Category M1 (Cat-M1) transmit power of 20Bm, and provides average upload speeds between 200kpbs and 400 kpbs. This technology can extend battery life, potentially by up to 10 years Customer lifetime value (CLV or often CLTV), lifetime customer value (LCV), or life-time value CLV (LTV) is a prediction of the net profit attributed to the entire future relationship with a customer A Point of Sale purchase is the ‘point’ where a transaction is finalized or the moment where a POS customer tenders payment in exchange for goods and services. Any form of payment can be used, such as cash, debit cards, credit cards, mobile payments and even Bitcoin QED Venture Capital Fund - Primarily investing in FinTech companies The Basel Committee on Banking Supervision is the primary global standard setter for the BCBS prudential regulation of banks and provides a forum for regular cooperation on banking supervisory matters. The Financial Stability Board is an international body that monitors and makes recommendations FSB about the global financial system The Committee on Payments and Market Infrastructures promotes the safety and efficiency of CPMI payment, clearing, settlement and related arrangements, thereby supporting financial stability and the wider economy. WBG World Bank Group Peer-to-peer lending, also abbreviated as P2P lending, is the practice of lending money to P2P individuals or businesses through online services that match lenders with borrowers The Financial Conduct Authority (FCA) regulates the financial services industry in the UK. Its role FCA includes protecting consumers, keeping the industry stable, and promoting healthy competition between financial service providers Source: Companies

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India FinTech

COMPANY

107 | IDFC SECURITIES 7 September 2018

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[email protected] 91 Rumit Dugar 2,400 For Private Circulation only. Circulation For Private

Niyogin Fintech

INVESTMENT ARGUMENT

 Niyogin is set to ride India’s digitalization wave with a unique delivery model for tech-centric financial services.

 Niyogin’s platformised approach to financial services with partner-led distribution network as well as direct-to-customer will drive market share gains in the SMB lending segment.

 SMB credit penetration in India remains low and is a large unaddressed market with credit gap of Rs20trn. The model allows Niyogin to expand beyond credit such as SaaS and financial product distribution.

 Niyogin is backed by a strong board and professional management. The company is well capitalized with an equity base of US$40m.

 We estimate 93% revenue CAGR over FY18-FY23E and initiate coverage with an Outperformer rating and target price of Rs250/share.

Large addressable market

 SMB lending market is significantly underpenetrated

 India has 63m MSMEs and only 4.5m have access to credit  India’s SMB segment has potential credit gap of Rs20trn  IndiaStack and technology to enable lower cost of delivery

 SMB lending – Significantly underpenetrated Areas where banks cannot India’s SMB segment plays a significant role in India’s economy - employs reach and/or are ~40% of India’s workforce, contributes ~29% to national GDP, has ~45% prohibited by high cost of share in manufacturing output and accounts for about 40% of India’s total delivery and services tend exports. Despite its size, the SMB segment is beset with many problems to remain unbanked such as supply chain inefficiencies, scalability, funding issues and is highly unorganised and fragmented, etc.

MSME numbers in India have registered 7% CAGR over last 10 years. However incrementally, the shift has been towards services sector MSMEs. As the current lending market structure is dominated by banks, areas where banks cannot reach and/or are prohibited by high cost of delivery and services tend to remain unbanked.

Exhibit 1: Growth of MSMEs Exhibit 2: Mix towards services (2015 onwards) No. of MSMEs (m) 68.0 63.4

51.0 Manufact Services 36.2 uring SME SME 45% 34.0 55%

17.0

0.0 Fourth All India Census NSS 73rd Round 2015-16 of MSMEs, 2006-07

Source: India MSME AR, IDFC Securities Research Source: India MSME AR, IDFC Securities Research

109 | IDFC SECURITIES 7 September 2018

Niyogin Fintech

MSME lending remains a significant white space Only 10% of the SMBs India’s SMB customer base remains highly underserved. Credit penetration having access to formal for SMBs remains low, with only 10% of the SMBs having access to formal credit credit. Lack of data and high cost of credit delivery have primarily driven such low penetration rates. We expect a change in this scenario, once SMBs digitize their businesses to drive efficiencies, more importantly, led by regulatory compliance (ex-implementation of GST in India). Further, digital infrastructure (IndiaStack), which allows companies to build data analytics, should help reduce cost of delivery and drive penetration.

Exhibit 3: MSME lending underpenetrated (m) No of MSME in India

51.1 48.8 46.8 42.9 44.8 Total number of MsME (51 m)

Nof current >90% account (40 m) Penetration gap

No of MSME borrowers (4.5 m) Total FY11 FY12 FY13 FY14 FY15 employees (m) 96 101 106 112 117

Source: FIBAC 2017, IDFC Securities Research

Although India has 40m current accounts in MSMEs, the number of MSME borrowers is only 4.5m, implying massive under penetration.

Exhibit 4: India SMB - Large addressable market (Rs trn) Total SME Lending Market Able/willing to (Rs trn) 35 Interest Rates address only Potential addressable Informal Lenders 30 24%+ top-end of credit gap: market 25 Rs20.46trn 20 Bulk of market 33.2 15 Unaddressed Interest Rates underserved 2.8 0.7 Market 16-24% by existing 10 financiers 12.7 5 9.2 0 SCBs NBFCs Other Total Total Interest Rates Model self- Banks/Govt Formal Addressable Banks/NBFCs 12-16% limiting to Institutes Supply Demand certain niches

Source: Niyogin, IDFC Securities Research

110 | IDFC SECURITIES 7 September 2018

Niyogin Fintech

Unique business model

Niyogin is a technology and data science-centric NBFC. The company is building its model around 4 key components 1) Capital, 2) Distribution channel, 3) Technology & Data and 4) Collaboration. We believe Niyogin’s vision to effectively execute a platform and build a network that allows for distribution of products and services, as of now starts with lending and can expand to other segments. This makes the model unique with potential to generate ROEs above a typical lender.

Exhibit 5: What makes Niyogin’s model unique

Existing players Niyogin

• Sourcing channel – DSA • Sourcing channel – 3i • Asset growth the primary focus • Customer is the focus • One size fits all approach • Ecosystem-driven approach • Paper driven • Digitization Lenders Traditional Traditional

• Judgmental Decisioning ‘man • Automated Scorecard behind the machine’ approach Decisioning • Bootstrapped Capital Access • Publicly Listed /permanent • Limited operating leverage capital vehicle

FinTech • Volume scalability • Digital data ingestion

Source: Company, IDFC Securities Research

 Technology and data-centric business model Niyogin has integrated 42 Niyogin has a technology-centric service delivery model that builds a applications by building scalable technology and data platform for MSME business. The user an open source API-driven interface (UI) interface has been built with a Mobile-First approach, as well middleware as established partnerships for core banking systems and decisioning engine. The company has been able to execute its technology infrastructure at a rapid pace and has built its technology stack in 7 months. Niyogin has integrated 42 applications by building an open source application programming interface (API)-driven middleware.

111 | IDFC SECURITIES 7 September 2018

Niyogin Fintech

Exhibit 6: Niyogin’s technology stack

Engage

API

Core Apps

Infra & Database

Analytics

Source: Company, IDFC Securities Research

The technology stack flows all the way to credit decisioning, which is automated for MSME lending versus a manual judgemental and paper- intensive decision making process. Digital infrastructure improvement in India (discussed in the sections above), is allowing the emergence of technology-centric credit-decisioning models.

Exhibit 7: Credit decisisoning

Prequalification - Applicant details (PAN, GST, Customer and Supplier information) - Financial details ( Banking, GST, ITR)

Scorecard based decisioning - Leverage CRIF data set - Additional parameters based on banking transaction & Tax - Partner scorecard - Social and legal scorecard

Credit decision and disbursal - Automated trigger based on scorecard - Post approval checks outsourced - Disbursal post collection of documents. Agreements are e-signed

Source: Company, IDFC Securities Research

112 | IDFC SECURITIES 7 September 2018

Niyogin Fintech

 Channel – A long term differentiator Niyogin uses 3i network, We like business models with distribution and channel advantage. While which has professionals in there are FinTech companies that have been successfully filling the its ambit product gap at attractive price points, we think a low entry barrier can disrupt – as seen in payments. This is where Niyogin is uniquely positioned, as the company uses Information Interface India Pvt. Ltd (3i) network, which has professionals in its ambit. As most MSMEs are closely-held promoters and their service partners are the interface, Niyogin’s channel to on-board these service partners on the platform, can build into a unique long-term and sustainable channel advantage. Not only does this give Niyogin relatively low-cost access to multiple MSMEs, but if incentivised correctly, could lead to better loan origination quality.

Leveraging 3i to deliver O2O model 3i leads processing treasury transactions in India and is a partner of choice for most multinational financial firms such as Bank of America, Citi, HSBC, Deutsche Bank, among others. 3i is one of the largest independent financial distribution platforms in the country with presence in 340 cities, network of 2,500 professionals and a client base of over 20,000.

 Platform and channel strength drives collaboration with Banks The common understanding is that FinTech will disrupt legacy models, which they will to an extent. However, there is tremendous room for collaboration with existing lenders (banks). As FinTechs do not have an established brand, there is lack of customer trust, capital and/or access to capital and expertise in regulatory compliances. In such a scenario, collaboration would be effective, as a FinTech would address the shortcomings of traditional lenders and the latter in turn would address trust and Capital for the FinTech. Regulators in some developed markets too are turning favourable towards FinTech and traditional lender collaboration. In Europe, the PSD2 regulation pushes legacy financial services players to open up their tech systems and adopt APIs.

Exhibit 8: Collaboration between a traditional lender and a FinTech

Source: IDFC Securities Research, Capgemini

Niyogin’s business model, with a platform-centric approach, drives values across stakeholders, which in our view, opens room for partnerships and collaboration. With a channel in place, unsecured credit is an entry product that could be scaled up further to cross-sell other products and services. Further, technology-centric decisioning opens up room for analytics and enhances their ability to drive hyper-localised products suited for a particular market and/or industry.

113 | IDFC SECURITIES 7 September 2018

Niyogin Fintech

Exhibit 9: Room for multiple partners

Banks

Niyogin FinTech Service Platform innovators

Product innovators

Source: IDFC Securities Research, Capgemini

Exhibit 10: Collaboration model

Ability to attract partners

Hyperlocalise products Niyogin Platform Cross sell other financial products

Unsecured credit is the entry product

Source: IDFC Securities Research, Capgemini

 Collaboration to help build and run an asset-light model In our view, the company’s ability to build a platform and drive collaboration with partners across segments should help in attracting multiple players to execute a hybrid and efficient capital structure. In our view, Niyogin’s business model strength and platformification will manifest into the company being able to run an asset-light model. As a result, we believe a model that can operate on multiple sources of capital in the form of securitisation and co-lending are factors that would make the model asset light, capital efficient and provide scalability without the need to raise recurring capital.

Exhibit 11: Potential asset-light structure

• Securitisation

Potential • Co-lending by Indian banks Equity asset-light structure • Alternate Funds

• Rising leverage - Debt

Source: Company, IDFC Securities Research

114 | IDFC SECURITIES 7 September 2018

Niyogin Fintech

 Why co-lending is attractive for banks? Niyogin’s platform and Co-lending is an attractive proposition for banks, as Niyogin’s platform and banks have banks have complementary strengths. Banks bring in low cost of funds complementary strengths (CASA), balance sheet size and the ability to leverage. However, the high cost of customer acquisition, cost of delivery and credit decisioning are challenges for most banks, which we believe can be addressed through Niyogin’s platform. A co-lending collaboration would help banks expand their addressable market. We estimate ~5% pre-tax RoA for banks can be delivered in the model, which is attractive for banks.

Exhibit 12: Co-lending model with banks- A win-win proposition

Banks Niyogin • CASA funds • Low cost of delivery • Ability to leverage • Credit decisioning

Source: Company, IDFC Securities Research

Exhibit 13: Banks can make decent RoA in the co-lending model Co-lending RoA

Niyogin Customer's Yield (a) 20% Niyogin Fee on Co-Lending (b) 5% Yield transferred to Bank (c ) = (a) - (b) 15% Cost of Funds for Banks (d) 7% Credit Costs (e ) 3% Pre-tax RoA (f) = (c ) - (d) -(e ) 5%

Source: Company, IDFC Securities Research

The co-lending model should help Niyogin evolve into a capital-efficient business model with the ability to build greater scale, deliver superior RoEs without consistent need to use an equity capital base to scale. Effectively, co-lending will allow Niyogin to leverage its equity base much more than a typical NBFC.

Exhibit 14: Capital structure evolution of Niyogin

Securitisation

Alternate Funds

Co-lending with Indian banks

Debt Equity

Source: Company, IDFC Securities Research

115 | IDFC SECURITIES 7 September 2018

Niyogin Fintech

Growth strategy

 Drive market coverage and penetrate distribution  Partnerships and collaboration to drive products, customer acquisition, engagement and analytics

 Expand products beyond lending and build hyper-localised products

Exhibit 15: Growth strategy • Currently partner network • On boarded 203 partners covers 70 cities across 4 currently. states – Gujarat, • Expand to 500 by FY19 Maharashtra, Rajasthan and • Improve activation Karnataka rates of the partners • Cover 120 markets by Market Distribution on-boarded FY19 coverage channel

Products Partnership • Unsecured credit • 1 partnership signed • Expand the product in Q1FY19 with portfolio beyond credit Instamojo • Build localised products • Look for partnership for customers and products

Source: Company, IDFC Securities Research

 Accelerating partner network to enhance market coverage Niyogin has already Distribution and partnerships are key drivers for any business model, both doubled its customer base from loan origination pipeline and cross-selling perspectives. Expanding from 50 in Q1FY19 to 100 channel and partner on-boarding would be key growth drivers for Niyogin. as of early August The company has a stated target of reaching 500 retail partners by FY19E and they are already at 203 as of Q1FY19. Importantly, the company’s distribution now spans 70 cities in 4 states (Maharashtra, Gujarat, Rajasthan and Karnataka). Niyogin aims to add 100+ more partners in Q2FY19 with the primary focus to accelerate activation of partners on- boarded in Q1FY19 and to be on-boarded in Q2FY19.

Customer addition momentum is building with rising market coverage and partner on-boarding. Management indicated a month on month run rate of above 60% in customer acquisition. The company has already doubled its customer base from 50 in Q1FY19 to 100 as of early August.

Exhibit 16: Retail partners Exhibit 17: Number of customers

Partners on Niyogin No of customers 600 1,200 500 1000

450 900

300 600 203

150 100 300 100 50 0 0 4QFY18 1QFY19 FY19E Jun-18 10-Aug-18 FY19E

Source: Company, IDFC Securities Research Source: Company, IDFC Securities Research

116 | IDFC SECURITIES 7 September 2018

Niyogin Fintech

Exhibit 18: Estimated on boarding of retail partners Exhibit 19: Number of customers Partner Network Customers 8,000 7,500 32,000

6,000 6,000 24,000

4,000 4,000 16,000

2,000 2,000 8,000 500 0 0 FY19E FY20E FY21E FY22E FY23E FY19E FY20E FY21E FY22E FY23E Source: Company, IDFC Securities Research Source: Company, IDFC Securities Research

 Partnerships drive customer engagement and capital efficiency Partnerships will aid Niyogin’s immediate focus is to expand market coverage and partner on- expansion in market boarding. From a medium-term perspective, the company is investing in coverage partnerships to drive both customer acquisition and improve engagement. In Q1FY19, Niyogin entered into a partnership arrangement for direct-to- customer channel with Instamojo, a leading FinTech in the payments space for acquiring SME merchants. The company expects this partnership to go live in Q2FY19. In addition to product leverage, these partnerships will also aid expansion in market coverage.

Exhibit 20: Number of cities Exhibit 21: Number of partnerships No of cities Partnerships 80 70 2.4 2

60 1.8

36 40 1.2 1

20 0.6

0 0 0 4QFY18 1QFY19 4QFY18 1QFY19 FY19E

Source: Company, IDFC Securities Research Source: Company, IDFC Securities Research

 Expanding product offerings Niyogin’s ability to expand product offerings and drive hyper-localisation will help drive customer engagement and long-term RoE for the company. With the partner network in place, unsecured credit is the foot in the customer’s door. Niyogin’s platformised approach allows the company to offer solutions beyond credit and would also allow it to expand offerings to other financial products such as secured credit, wealth advisory, insurance, etc. Further, there is room to even cross-sell business services such as IT solution, payroll, tax/audit compliance, etc. Companies such as Square in the US too have been deploying a similar model, wherein they enter the customer space through payments and then cross-sell other services, including business services. Although this would be a long-term process, Niyogin expects to have at least 1 solution beyond credit by the end of FY19.

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Niyogin Fintech

 Target –20x growth in loan book over 3-4 years The company has laid out The company has laid out targets for FY19E and beyond FY21E, wherein it target to disburse over expects to expand its partner network to 5000+ with over 50,000 US$500m by FY2021E customers and disburse over US$500m by FY2021E.

Exhibit 22: Targets set by the company Customers 1000+ 50,000 Partners 500+ 5000+ Goals Disbursals FY19E US$25mn+ US$500mn+ Partnerships 2+ 50+

Solutions 1 FY21E Beyond 5+ beyond credit

Source: Company, IDFC Securities Research

Exhibit 23: Capital structure can support growth upto AUM of US$760m US$760m

Securitization US$200m

Off Balance Sheet – US$640m Co-lending US$340m Indian Banks

International Fund – US$100m Alternative lending

US$40m On Balance 3X Leverage US$120m Equity Sheet – US$120m

Source: Company, IDFC Securities Research

118 | IDFC SECURITIES 7 September 2018

Niyogin Fintech

Model can deliver premium RoEs

A platformised model has We have drawn parallels with Square (SQ US) to see how Niyogin is the potential to deliver building its business, given parallels of customer-centric approach and superior RoEs over time tech platform-centric solutions in the SMB segment. In our view, a with maturity platformised model has the potential to deliver superior RoEs over time with maturity than that generated by typical lenders.

 Square is a good parallel As India’s FinTech ecosystem is nascent, we have tried to draw parallels of business models in developed markets with that of Niyogin. We believe Square (SQ) is a potentially good parallel to how Niyogin is trying to build its FinTech business.

About Square SQ is a cohesive commerce ecosystem that helps sellers (SMBs) in the US start, run, and achieve growth in their businesses. Foundation of SQ’s ecosystem is its full service, managed payments offerings. Once sellers download SQ’s POS mobile app, they can quickly and easily take their first payments, because the company can typically bring them onto their system within minutes. With SQ’s offering, a seller can accept payment in person via magnetic stripe (a swipe), EMV (Europay, MasterCard, and Visa) (a dip), or Near Field Communication (NFC) (a tap); or online via Square Invoices, Square Virtual Terminal, or the seller’s website.

What is SQ’s strategy? SQ used payments as the entry product to tap into SMB customers in the US, and then expanded into various other products such as a SaaS, food delivery, lending, etc. The commerce ecosystem also includes services (SaaS software) that help sellers make informed business decisions through transaction-based pricing model or subscription model. Additionally, SQ offers capital as a service with processing loans, based on seller’s payment processing history. SQ also serves its sellers through Caviar, a food-ordering service that helps restaurants reach new customers and increase sales without additional overheads.

Exhibit 24: SQ’s product expansion

Source: Company, IDFC Securities Research

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Niyogin Fintech

Exhibit 25: SQ’s seller mix (GPV mix) Exhibit 26: SQ’s new product mix

Charities & Others Products launched since 2014 as percentage of Health Education 1.0% Adjusted Revenue services 4.0% 7.0% 32% 29%

Individuals Retail 7.0% 20.0% 24%

Health/bea 16% uty Food 12.0% Related 20.0% 8%

Contractor 1% /Repair Services 0% 13.0% 16.0% 1QCY14 1QCY17 Source: Company, IDFC Securities Research Source: Company, IDFC Securities Research

Exhibit 27: SQ - Rising share of non-transaction oriented revenue

Subscription and Service based revenue 11% 12%

9% 8%

6% 5%

3% 1% 0% 0% 0% CY12 CY13 CY14 CY15 CY16 CY17

Source: Company, IDFC Securities Research

Exhibit 28: Square Capital – Lending snapshot

US$1.5bn in cumulative Default rate loans since ~4% 2014

Source: Company, IDFC Securities Research

Exhibit 29: SQ - Snapshot of financials Square (In US$ m) CY14 CY15 CY16 CY17 GPV 23,780 35,643 49,683 65,343 YoY Growth 60% 50% 39% 32% Transaction Revenue 708 1,050 1,456 1,920 YoY Growth 63% 48% 39% 32% Subscription and Services Revenues 12 58 129 253 YoY Growth NM 382% 123% 95% Total Revenues 850 1,267 1,709 2,214 YoY Growth 54% 49% 35% 30% Gross Profit 226 370 576 839 Gross Margins % 27% 29% 34% 38%

Source: Company, IDFC Securities Research

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Niyogin Fintech

Can we draw a parallel with Niyogin? The key essence of SQ’s business model is its platformisation that is used to drive customer engagement through multiple services such as SaaS, food ordering, lending, etc. Unlike SQ, Niyogin isn’t entering the SMB customers with payments, but we believe there exists a parallel between the two business models. And, this parallel exists in their intent to platformise and drive hyper-localised products on their own or through partnerships.

Exhibit 30: Square portfolio Exhibit 31: Niyogin portfolio

Business services

Financial Niyogin SaaS Products Channel

Credit

Source: Company, IDFC Securities Research Source: Company, IDFC Securities Research

Why is Niyogin not using payments as an entry strategy? The entry point for Niyogin is credit, as payments (which is SQ’s forte) is hotly contested in India. Moreover, India is still a cash-centric economy and payments is a likely loss leader from a product-offering perspective given price competition. While SQ makes 2.9% on their payment-processing service in the US, in India, gross revenue yields in the payments segment are 1.2%. Further, India has a fixed-fee model with certain enterprises (for example LIC pays Rs0.2/transaction).

Exhibit 32: Payment gateway spreads low in India; credit a better entry strategy Transaction Fee % 3.2% 2.9%

2.4%

1.6% 1.2%

0.8% 0.60%

0.0% UPI India Floating model Square US Source: Company, IDFC Securities Research

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Niyogin Fintech

Exhibit 33: Regulations cap MDR for small merchants Mechant Discount Rate (MDR) for debit card transactions (as a % of transaction value) Merchant Category Physical POS infrastructure QR code based card including online card acceptance infrastructure transactions

Small Merchants (with turnover Not exceeding 0.40% Not exceeding 0.30% up to Rs20 lakh during the (MDR cap of Rs200 (MDR cap of Rs200 per previous financial year) per transaction) transaction)

Other merchants (with turnover Not exceeding 0.90% Not exceeding 0.80% up to Rs20 lakh during the (MDR cap of Rs1,000 (MDR cap of Rs1,000 per previous financial year) per transaction) transaction)

Source: Niti Aayog, IDFC Securities Research

Payment spreads are low We also think payment spreads are low in India compared with the US. As in India compared with the a result, we view credit as a more profitable entry strategy. Further, the US payments space is turning hyper competitive, as multiple players are in the process of establishing payment gateway platforms. We believe Niyogin can successfully collaborate and/or partner with these platforms to access SMB customer base. We have already seen Niyogin partner with Instamojo (Payment platform) in Q1FY19, which will allow direct-to-customer channel and could be further used to acquire SME merchants for the company.

Exhibit 34: Executing on partnership (as of Q1FY19)

Banks Instamojo

Niyogin FinTech Service Platform innovators

Product innovators

Source: Company, IDFC Securities Research

Model can deliver attractive return ratios We expect Niyogin to We believe Niyogin’s business model has the potential to deliver superior deliver ROE of 20%+ by return ratios compared to a typical risk lender, given the parallel with SQ, FY2022E low cost of delivery and ability to cross-sell with the platform. We have seen SQ’s ability to deliver both scale and improve return ratios. The company has currently scaled up its non-transaction/non-hardware revenue to 11% of sales. Interestingly, gross margins on these revenues work out to 70% for SQ. We expect Niyogin to deliver ROE of 20%+ by FY2022E.

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Niyogin Fintech

Exhibit 35: SQ’s non transaction gross margins (%)

Non transaction Rev (US$ m - LHS) Gross Margin (% - RHS) 280 253 80% 75% 70% 210 67% 60% 61% 129 140 40%

58 70 20% 12 0 0% 2014 2015 2016 2017 Source: Company, IDFC Securities Research

 Strong board and team Niyogin is founded by industry veterans and run by a professional and strong management. The sound board is backed by an experienced execution team with know how across markets and Indian SMB segment.

Exhibit 36: Founders Name Designation Profile

• Amit has over 15 years of experience in the financial services industry Non-Executive • Currently he is the CEO of Marshall Wace Asia, based out of Hong Kong, Prior to Amit Rajpal Chairman & Co- this, Amit worked at Morgan Stanley for 11 years as part of the FIG research group Founder • He was one of the youngest MD in the history of Morgan Stanley

• Gaurav, the Co-Founder of Niyogin, is a private investor focused on taking an engaged ownership approach across public and private investments • Over his 18-year career, Gaurav has invested across emerging and developed markets. Most recently, he was Managing Director and Portfolio Manager at The Boston Company Asset Management (A BNY Mellon company), focused on Gaurav Patankar Co-Founder Emerging Market Conviction Investing. Prior to this, he was a portfolio manager of global absolute-return strategies, including emerging-market strategies at Lockheed Martin Investment Management Co. (LMIMCo) • He holds a Ph.D. in Social and Political Sciences, an MBA in Finance & Strategy and a Bachelor’s degree in Electronics and Telecommunications Engineering

Source: Company, IDFC Securities Research

123 | IDFC SECURITIES 7 September 2018

Niyogin Fintech

Exhibit 37: Board of Company Name Designation Profile

• Amit has over 15 years of experience in the financial services industry Non-Executive • Currently he is the CEO of Marshall Wace Asia, based out of Hong Kong, Prior to Amit Rajpal Chairman & Co- this, Amit worked at Morgan Stanley for 11 years as part of the FIG research group Founder • He was one of the youngest MD in the history of Morgan Stanley

• Makarand has over 40 years of multinational experience in Strategic and Financial Makarand Promoter roles within industry verticals of Financial Services, Pharmaceutical, Healthcare and Patankar Director Retail in organisations such as Glaxo, TATA & TNT

• Kapil started his professional career in 1987 with Nestle India Limited. He was also a part of the management team of Bausch & Lomb serving in Russia, Ukraine, East Africa and SAARC region. He re-located to Thailand on becoming the Country Independent Manager of Bausch & Lomb and subsequently got promoted as the commercial Kapil Kapoor Director director in 1998 with regional responsibility for South-East Asia • He currently serves as the Chairman and Non-Executive Director of Info Edge (India) Limited, and is also on the Board of Trustees of the International Foundation for Research and Education (Ashoka University)

• Sutapa has close to 24 years of experience in financial services across large multinational banks - ANZ Grindlays and ABN AMRO Currently, she is consulting in the wealth, investment management area and is on Independent • Sutapa Banerjee Director the board of directors (independent director) for leading companies (JSW Group, IL&FS Group) and non-profits (Oxfam India and Dignity Foundation). She also represents women’s world banking as a nominee director on the board of their investee company Ananya Finance in India

• Sucheta is one of the best known names in investigative journalism. She was awarded the Padma Shri by the Government of India in 2006 for her outstanding Independent investigative journalism spanning over two decades including exposing the Sucheta Dalal Director Harshad Mehta scam in 1992 • She currently directs socially-oriented reporting at Moneylife, the Foundation's activities and grievance redressal activities

Source: Company, IDFC Securities Research

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Niyogin Fintech

Exhibit 38: Management Team Name Designation Profile

• Arnab leads strategy, risk, finance, technology and data sciences at Niyogin He has over 19 years of experience in banking and financial services across Asia. Arnab • President His has previously worked with HSBC, Citigroup and ANZ and has also run his Bhattacharya own firm, Goalkeep Advisors • He is an MBA from FMS, Delhi University

• In his current role, his responsibility encompasses Business Development and Sales, Network Management and Operations, Product Management, Marketing and Channel Development • He brings over 24 years of experience in the banking & financial services industry Parag Chopde President • Prior to Niyogin, he served for around 6 years in the transformation journey of RBL Bank as the Head of MSME Finance, Head Risk – Agri Business, Development Banking & Financial Inclusion Group., Head Risk-Business Banking for RBL Bank, Head Credit & Risk - Exim Bank (T) Ltd., has spent over a decade across locations & positions with Citi-ABF, Program Risk Head (ABF) for Citi - ELC India & Product Head - Supply Chain Finance for Global Subsidiary Group, Citibank, India.

• He is responsible for the Go To Market for off-line and on-line business partnerships, marketing & digital strategy, channel development, consumer Chief Business acquisition & PR & communications Himanshu Rajpal Development • Himanshu brings in over 18 years of rich and varied experience, leading steady Officer state and start-up businesses in organizations such as Standard Chartered, PepsiCo, Euronet & PayPal amongst others, across FMCG, unsecured consumer credit, digital technology and payments

• Srivaths is responsible for Information Technology – Digital platforms, Srivaths Chief Information Applications, infrastructure and information security Varadharajan Officer • With 19 years of experience, he has worked across industries like BFSI , Telecom, BPO / KPO and Airline sub division in various functional streams

Source: Company, IDFC Securities Research

Exhibit 39: Governance structure Board of Directors

Amit Rajpal Makarand Patankar Kapil Kapoor Sutapa Banerjee Sucheta Dalal Non Executive Promoter Director Independent Independent Independent Chairman Director Director Director

Steering Committee

Amit Rajpal Gaurav Patankar Makarand Patankar Arnab Bhattacharya Parag Chopde Co - Founder Co - Founder Promoter Director President President

Operating Committee

Himanshu Rajpal Srivaths Vardharajan Arnab Bhattacharya Parag Chopde Chief Business Chief Business President President Development Officer Development Officer

Source: Company, IDFC Securities Research

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 Niyogin –Valuation We have used new tech Niyogin’s unique business model poses valuation challenges for investors companies in the US as and analysts alike, given the early-stage growth profile, business mix, and valuation benchmarks sub-scale profitability of the company/industry. Moreover, limited listed companies in India in the emerging technology space, compound the issue pertaining to valuing the company. We have therefore used new tech companies in the US as valuation benchmarks.

Comparison across tech-centric global players On a relative basis, we have compared Niyogin to 4 broad groups within the technology space, 1) high-growth technology, 2) disruptive internet technology, 3) disruptive enterprise software and 4) high-growth Indian NBFCs. As we think Niyogin’s business model is geared towards building a technology platform, technology-centric multiples would be a fair comparable.

Exhibit 40: Comparable sets of companies in different areas High-growth tech Disruptive Internet Ecosystem Disruptive enterprise software Indian NBFCs Facebook Etsy Workday Bajaj Finance FireEye Grubhub ServiceNow HDFC LTD SS&C Greendot Hubspot Gruh Finance Splunk Shopify Ultimate Software

Twitter Square Paycom

Source: Company, IDFC Securities Research

Exhibit 41: Valuation comparison – Global tech Company Name Ticker Mkt Cap EV/EBITDA (x) EV/Sales (x) High-Growth Tech (US$ m) CY16 CY17 CY18 CY16 CY17 CY18

High-Growth Tech Facebook FB 5,04,238 21 20 14 11 12 18 FireEye FEYE 3,192 NM NM 30 3 3 4 SS&C SSNC 13,803 16 16 17 6 6 6 Splunk SPLK 17,935 NM NM - 8 7 14 Twitter TWTR 25,979 NM NM - 4 6 8 Average 18.3 18.3 12.3 6.1 6.9 9.8

Disruptive Internet Ecosystems

GrubHub GRUB 12,524 24 43 46 6 9 12 Green Dot GDOT 4,503 26 20 14 5 4 3 Etsy ETSY 5,873 27.3 55.2 41.3 3 5 9 Shopify SHOP 14,954 NM NM 407.4 9 14 13 Square SQ 32,087 NM NM 133.1 3 6 20 Average 25.9 39.6 128.2 5.0 7.4 11.7

Disruptive Enterprise Software

HubSpot HUBS 5,445 NM NM 6 8 10

Ultimate Software ULTI 9,368 85 77 82 12 10 8 Paycom Software PAYC 8,849 48 36 47 8 11 16 Workday WDAY 32,484 NM NM 88 9 10 14 ServiceNow NOW 34,434 NM - 9 11 13

Average 66.6 37.5 72.4 8.7 10.0 12.3

Simple Average 37 32 71 7 8 11

Weighted Average 57 58 9 10 13

Source: Bloomberg, Company, IDFC Securities Research: * December year end; All valuation ratios on LTM basis

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EV/Revenues On our football field Our disruptive tech universe traded at an average of 11.7x CY18 valuation run, we have EV/Revenues, with players like GrubHub and Shopify trading at 12x and arrived at an average 13x, respectively. SQ traded at 20x EV/Revenues during the period. In valuation of Rs451/share high-growth tech, EV/Revenues were slightly lower at an average of 9.8x, for Niyogin while disruptive enterprise tech players were trading at 12.3x average.

EV/EBITDA Given that most of the comparable sets are high growth, disruptive and in the process of scaling, EV/EBITDA multiples look optically high and have a varied range, depending on where the business model is in terms of scale and/or growth. Our weighted average for the tech universe 1) high-growth tech, 2) Disruptive internet tech and 3) disruptive enterprise software sits at 73x. In our view, this isn’t a metric that we can use for valuing Niyogin, given the early stage of the business.

Exhibit 42: Volatile range for EV/EBITDA in emerging tech EV/EBITDA (CY18E) Low Average High High-Growth Tech 14 12 30 Disruptive Internet Ecosystems 14 128 407 Disruptive Enterprise Software 47 72 88

Source: Bloomberg, IDFC Securities Research, Company P/BV We compared P/BV of premium high-growth NBFCs in India with our comparable set, which currently trades at 9x trailing P/BV. We believe Niyogin’s platform-centric model is different from that of a typical NBFC, despite credit being one of the large entry products. The platform approach should allow Niyogin to scale without frequent capital raise

 Initiating an Outperformer; target price of Rs250 Our football field valuation run for Niyogin is based on the following parameters. Based on this run, we have arrived at an average valuation of Rs451/share.

• EV/Revenues Average EV/Revenues o Weighted average EV/Revenues o • Weighted average EV/EBITDA • High-growth NBFC P/BV • High-growth NBFC P/E

Exhibit 43: Niyogin’s football field valuation price range

High Growth NBFC - P/E 265 410

High Growth NBFC - P/BV 180 554

Wt Average - EV/ EBITDA 440 837

Wt Average - EV/ Sales 160 306

Average - EV Sales 160 231

0 200 400 600 800 1000

Source: Company, IDFC Securities Research, Bloomberg

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Niyogin Fintech

 Target price of Rs250 per share based on EV/Revenues We would prefer to use Niyogin is a unique technology-centric FinTech, not just a credit-centric weighted average model. In our view, its platform-centric direction of the business model is EV/Sales of our akin to a technology enterprise platform company. Hence, we would prefer technology universe to to use weighted average EV/Sales of our technology universe to value the value Niyogin company, which stood at 13x sales in CY18.

Based on 13x EV/Revenues for FY2023E, we estimate Niyogin’s future value at Rs370/share. Discounting this value at 14% yield over next three years, we arrive at FY20E future value of Rs250 per share for the company. We initiate coverage on the stock with an Outperformer rating.

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FINANCIALS

Exhibit 44: Revenue and yoy growth Exhibit 45: EBITDA & PAT Revenue (Rs m - LHS) YoY Growth (% - RHS) (Rs m) EBITDA PAT 4,200 200% 2400 175% 3,531 3,500 160% 1800 2,800 131% 2,146 120% 1200 2,100 77% 65% 80% 600 1,400 776 1,375 56% 700 336 40% 0

0 0% -600 FY19E FY20E FY21E FY22E FY23E FY19E FY20E FY21E FY22E FY23E Source: Company, IDFC Securities Research Source: Company, IDFC Securities Research

Exhibit 46: Partner network (#s) Exhibit 47: Loan book Partner Network YoY Growth (% - RHS) Loan book (Rs m - LHS) % on BS (RHS)

8,000 300% 7,500 320% 34,000 120% 100% 233% 6,000 25,740 6,000 240% 25,500 90% 75% 4,000 17,160 4,000 160% 17,000 50% 60% 100% 2,000 8,580 30% 2,000 80% 8,500 40% 30% 500 25% 1,650 50% 0 0% 0 0% FY19E FY20E FY21E FY22E FY23E FY19E FY20E FY21E FY22E FY23E Source: Company, IDFC Securities Research Source: Company, IDFC Securities Research

Exhibit 48: Platform spread and cross-sell revenues Exhibit 49: RoE (Rs m) Platform Spread Cross-sell revenue ROE 32% 1200 35% 28% 900 19% 21%

10% 600 14%

7% 1% -3% 300 0%

-7% 0 FY19E FY20E FY21E FY22E FY23E FY19E FY20E FY21E FY22E FY23E Source: Company, IDFC Securities Research Source: Company, IDFC Securities Research

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Key risks

 Credit risk and high sensitivity to interest rates The SMB is sensitive to Niyogin’s business model carries interest rate and credit risk, as credit is its changes in the economic primary product. The segment that Niyogin addresses (SMB), is sensitive environment and interest to changes in the economic environment and interest rates. rates  Access to capital Growth will need access to capital, both equity and debt. Niyogin’s ability to execute and push Indian banks to work in a co-lending model will drive its RoE expansion.

 Technological innovation FinTech is an emerging industry in India and globally and thus technological changes can lead to emergence of more efficient business models that could disrupt the market.

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Appendix

Capital raise history

US$5m promoter Raised US$35m through Use earnings from capital contribution to acquire M3 preferential allotment at raise to fund opex/capex Global Rs50 build out in year 1

Source: Company, IDFC Securities Research

Shareholding pattern

Others Vikasa India Eif I Fund 5.3% 9.2%

Carmignac Portfolio 8.0%

Alchemy India Long Term Fund 5.6%

Promoter 41.9% Wf Asian Reconnaissance Fund 15.2%

Strategic India Equity Fund Lucky 10.8% Investment Managers 1.6% Alchemy Capital Management 2.4% Source: Company, IDFC Securities Research

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Income statement Key ratios

Year to 31 Mar (Rs Year to 31 Mar FY18 FY19E FY20E FY21E FY22E FY18 FY19E FY20E FY21E FY22E m) EBITDA margin (%) (178.6) (145.4) 7.4 38.6 53.0 Net sales 52 149 715 1,368 2,141 EBIT margin (%) (188.7) (154.7) 4.7 36.8 51.7 % growth 0.0 188.1 381.5 91.3 56.5 PAT margin (%) (51.4) (28.5) 11.8 28.0 38.0 Operating expenses 144 364 662 840 1,006 RoE (%) (2.0) (1.6) 3.3 14.2 25.8 EBITDA (92) (216) 53 528 1,135 RoCE (%) (7.4) (8.8) 0.7 5.5 8.7 % change 0.0 0.0 (124.5) 899.8 114.9 Gearing (x) 0.0 (0.3) 1.8 2.8 3.1 Other income 71 187 61 7 4 Net debt/ EBITDA 1.1 3.4 86.4 15.2 9.6 Net interest cost 0 0 0 0 0 (x) FCF yield (%) (1.2) (15.0) (45.4) (29.2) (22.1) Depreciation 5 14 19 24 29 Dividend yield (%) 0.0 0.0 0.0 0.0 0.0 Pre-tax profit (27) (42) 95 511 1,111 Deferred tax 0 0 0 0 0 Current tax 0 0 10 128 297 Valuations Profit after tax (27) (42) 85 384 814 Year to 31 Mar FY18 FY19E FY20E FY21E FY22E Preference dividend 0 0 0 0 0 Reported EPS (Rs) (0.3) (0.5) 1.0 4.5 9.3 Minorities 0 0 0 0 0 Adj. EPS (Rs) (0.3) (0.5) 1.0 4.5 9.3 Adjusted net profit (27) (42) 85 384 814 PE (x) NM NM 136.2 30.1 14.6 Non-recurring items 0 0 0 0 0 Price/ Book (x) 4.4 4.5 4.5 4.1 3.4 Reported net profit (27) (42) 85 384 814 EV/ Net sales (x) 221.6 72.7 22.5 14.3 10.6 % change 0.0 0.0 (299.9) 353.3 112.1 EV/ EBITDA (x) (124.1) (50.0) 304.5 37.1 20.0 EV/ CE (x) 4.3 4.2 2.2 1.8 1.6 Balance sheet As on 31 Mar (Rs RoE to improve further FY18 FY19E FY20E FY21E FY22E m) Paid-up capital 848 848 850 874 897 Preference capital 0 0 0 0 0 Reserves & surplus 1,756 1,687 1,707 1,966 2,570 Shareholders' 2,604 2,534 2,557 2,840 3,468 equity Total current 14 21 73 110 144 liabilities Total debt 1 33 4,653 8,099 10,973 Deferred tax 0 0 0 0 0 liabilities Other non-current 22 22 22 22 22 liabilities Total liabilities 37 76 4,749 8,232 11,139 Total equity & 2,641 2,610 7,306 11,072 14,606 liabilities Net fixed assets 9 8 12 16 20 Investments 2,390 0 0 0 0

Cash 103 766 90 56 116 Other current assets 78 1,719 7,040 10,794 14,226 Deferred tax assets 0 0 0 0 0 Shareholding pattern Other non-current 61 118 164 206 244 assets Net working capital 167 2,464 7,057 10,740 14,198 Total assets 2,641 2,610 7,306 11,072 14,606

Cash flow Year to 31 Mar (Rs FY18 FY19E FY20E FY21E FY22E m) Pre-tax profit (27) (42) 95 511 1,111 Depreciation 5 14 19 24 29 Chg in Working (65) (1,634) (5,269) (3,717) (3,398) capital Total tax paid 0 0 (10) (128) (297) Net Interest 0 0 0 0 0 Others 0 0 0 0 0 Operating cash (64) (1,663) (5,165) (3,309) (2,556) flow Capital expenditure (74) (70) (70) (70) (71) Free cash flow (138) (1,733) (5,235) (3,379) (2,626) (a+b) Chg in investments (2,390) 2,390 0 0 0 As of June 18 Debt raised/(repaid) 1 32 4,620 3,446 2,873 Net interest 0 0 0 0 0 Capital 848 0 2 24 24 raised/(repaid) Dividend (incl. tax) 0 0 0 0 0 Other items 1,783 0 0 0 0 Net chg in cash 104 689 (612) 91 271

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www.idfc.com Niyogin Fintech

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