Article Systemic Risk and Insurance Regulation †
Fabiana Gómez 1,* and Jorge Ponce 2 1 Department of Accounting and Finance, University of Bristol, Bristol BS8 1TH, UK 2 Banco Central del Uruguay, Montevideo 11100, Uruguay; [email protected] * Correspondence: [email protected]; Tel.: +44-117-39-41485 † The views in this paper are those of the authors and not of the Institutions to which they are affiliated.
Received: 25 June 2018; Accepted: 25 July 2018; Published: 27 July 2018
Abstract: This paper provides a rationale for the macro-prudential regulation of insurance companies, where capital requirements increase in their contribution to systemic risk. In the absence of systemic risk, the formal model in this paper predicts that optimal regulation may be implemented by capital regulation (similar to that observed in practice, e.g., Solvency II ) and by actuarially fair technical reserve. However, these instruments are not sufficient when insurance companies are exposed to systemic risk: prudential regulation should also add a systemic component to capital requirements that is non-decreasing in the firm’s exposure to systemic risk. Implementing the optimal policy implies separating insurance firms into two categories according to their exposure to systemic risk: those with relatively low exposure should be eligible for bailouts, while those with high exposure should not benefit from public support if a systemic event occurs.
Keywords: insurance companies; systemic risk; optimal regulation
JEL Classification: G22, G28
1. Introduction Insurance firms play an important role in the economy as providers of protection against financial and economic risks. In recent years, their contribution to systemic risk has increased. 1 According to the International Monetary Fund’s reports (see IMF 2016 and IMF 2017), this increase has been due to two main reasons. First, there has been a rise in insurers’ interest rate sensitivity (i.e., a growing common exposure to aggregate risk). This affected the asset side of insurers’ balance sheet by approximately 24 billion US dollars of investment (according to IMF estimates). Second, there is a significant growing exposure to other common sources of risk through cyber-insurance. A greater reliance on technology, combined with the interconnections of the global financial system, imply that cyber-threats can become systemic. The indirect exposure of insurance companies through their cyber-insurance risk underwriting may imply an important contribution to systemic risk. Highly correlated attacks could impact a large group of clients, and trigger multiple outstanding contracts simultaneously. In turn, the occurrence of a cyber-attack may significantly affect the asset side of insurance firms’ balance sheet because, for instance, it may trigger the fire sales of assets when all others are also selling. In such a case, insurers are unlikely to fulfill their role as financial intermediaries precisely when other parts of the financial system are failing to do so as well. After the global financial crisis of 2007–2009, and with the aim of limiting systemic risk, some regulatory bodies have promoted the implementation of macro-prudential policies. Particularly, in the
1 Although the systemic risk in the insurance sector clearly remains below that in the banking sector, a number of insurance firms were subsequently among the financial institutions designated as globally and systemically important (International Association of Insurance Supervisors, IAIS 2013).
Risks 2018, 6, 74; doi:10.3390/risks6030074 www.mdpi.com/journal/risks Risks 2018, 6, 74 2 of 12 insurance sector, the Financial Stability Board (FSB) published a list of global systemically important insurers, and it intends to implement special policy measures for these institutions by January 2019.2 In the same direction, the US regulatory reform, known as the Dodd–Frank Act, imposed on non-bank holding companies (including insurance companies) a new form of regulation for those deemed to be “Systemically Important Financial Institutions”. Despite these incipient attempts at macro-prudential policies, most insurance regulation remains micro-prudential in nature. Systemic risk and reform proposals have led academics to focus on the extent to which insurance companies contribute to systemic risk (e.g., Acharya and Richardson 2014; Bobtcheff et al. 2016; Cummins and Weiss 2014). However, much less attention has been devoted to the analysis of the optimal way to regulate systemic insurers. Motivated by the observation that the insurance sector has been put on the map as a source of systemic risk, even though its regulation remains largely micro-prudential, this paper aims to fill the gap by studying the optimal regulation of the insurance sector when insurance companies are exposed to systemic risk. More precisely, we propose a formal model of the insurance sector that, in the absence of systemic risk exposure, predicts that optimal regulation may be implemented by capital regulation (similar to what is observed in practice) and by actuarially fair technical reserve regulation. In the case of the failure of the insurer, an industry-managed solution may be enough. However, capital regulation and actuarially fair technical reserves are not enough when insurance companies are exposed to systemic risk. In such a case, prudential regulation should also add a systemic component to capital requirements that is non-decreasing in the insurer’s exposure to systemic risk. Hence, there is a rationale for the macro-prudential regulation of insurance companies, where capital requirements are linked to their contribution to systemic risk. Moreover, public intervention under the form of a bailout policy may be deemed necessary if a systemic event occurs. Implementing optimal regulation implies separating insurance firms in two categories, according to their exposure to systemic risk: those with relatively low exposure should be eligible for bailouts, while those with high exposure should not benefit from public support if a systemic event occurs. This paper contributes to the growing body of literature analyzing the presence of systemic risk in the insurance industry (see Eling and Pankoke 2016 for a recent review of the literature on this topic). Despite many methodological and empirical approaches aimed at the identification and measurement of systemic risk, to the best of our knowledge there is no theory providing a rationale for its regulation in the insurance sector. Some authors argue that traditional insurance activities do not create systemic risk (e.g., Cummins and Weiss 2014; Harrington 2009 and Tyler and Hornig 2009). The argument basically rests on the fact that traditional insurance activities wash out risks by diversification, therefore not generating systemic risk. However, this conclusion may not hold for non-traditional activities (e.g., Acharya and Richardson 2014 and Bobtcheff et al. 2016). Based on descriptive statistics and a systemic risk measure, Acharya et al.(2011) argue that insurers with traditional business models pose low systemic risk in contrast to companies engaged in non-traditional insurance products. Similar to this strand of the literature, we argue that systemic risk may be generated if other activities are undertaken (e.g., cyber-insurance underwriting), or additional contractual clauses are attached to traditional insurance (e.g., minimum guarantees or early surrender options in the case of life insurance). Hence, we contribute by studying the optimal regulation for insurance companies under systemic risk. Unlike the previous literature, we do not focus on the contribution of insurance companies to systemic risk. Our starting point is that insurance companies are exposed to a non-diversifiable (systemic) risk. We have in mind a severe but infrequent shock in which only the government is able to provide liquidity to stabilize the financial system.3 In this case, government funding provision (i.e., bailout) of insurance companies responds to the very same rationale as emergency liquidity
2 The FSB is an international organization that was created by the G-20 in April 2009. Its purpose is to monitor the finance industry and to make recommendations for addressing systemic risk (see FSB 2013). 3 An example of this kind of intervention is the Troubled Asset Relief Program (TARP) implemented by the US in 2008. Risks 2018, 6, 74 3 of 12 assistance in banking: to protect the system as a whole, by limiting the frequency and the cost of systemic crises. This is often referred to as a macro-prudential perspective. Hence, our contribution to the previous literature is to find a rationale for incorporating this macro-prudential component to insurance regulation. A number of studies have addressed the issue of how to regulate insurance companies. However, the conclusions of this strand of literature are mixed and they are generally not supported by formal theory. On the one hand, Acharya et al.(2011) claim that institutions that are too interconnected to fail should pay a fee for the implicit guarantee of being bailed out in the case of a crisis. In the same direction, Bach and Nguyen(2012) offer a discussion about the need of prudential regulation in insurance. They claim that even though traditional insurance activities might not be systemically risky, macro-prudential regulation is necessary due to the economic cost of impaired insurance markets. We contribute by formalizing these results in a consistent theoretical model. On the other hand, Berry-Stolzle et al.(2014) provide an empirical study of the consequences of raising capital in the insurance sector. They found that insurers had no difficulty in raising money during the 2007–2009 crisis. Based on this observation, they conclude that additional regulation for insurers is not needed. Similarly, Grace(2010) provides empirical evidence supporting the argument that insurers do not contribute to systemic risk, and he claims that no institution should be classified as systemically important, since this would create a moral hazard. Our results, however, are opposed to this strand of the literature: we formally find a rationale for capital surcharges and other regulation that are linked to the contribution of insurers to systemic risk. To the best of our knowledge, we are the first to provide a formal theoretical model to justify the need of introducing a macro-prudential perspective to insurance regulation. We also propose concrete forms of implementing the optimal regulatory policy when systemic risk is an issue in the insurance industry, and discuss that implementing them would be feasible under realistic circumstances. Moreover, if systemic risk is not a concern, our model delivers similar results to previous work on insurance regulation (e.g., Plantin and Rochet 2007, and the references therein), which prescribe capital regulation similar to those observed in practice (e.g., Solvency II, a regulatory framework that aims to ensure that insurers hold enough capital and introduces a risk-based approach to regulation). Therefore, we complement this strand of the literature by extending the framework and showing how optimal regulation should be adapted to the consideration of systemic risk. The rest of the paper is organized as follows. Section2 presents the basic model where systemic risk is not considered, and shows that optimal regulation can be implemented by capital regulation. Section3 extends the model to capture the occurrence of a systemic event that may lead to the failure of the system. Finally, Section4 summarizes our findings and concludes.
2. A Model without Systemic Risk In this section we introduce a simple framework in order to study the optimal regulation of an insurance company when systemic risk is not an issue. The results in this section will serve as a benchmark to compare the effects of considering systemic risk exposures in the next section. More precisely, we propose a model that captures in the simplest possible way the risk and incentive trade-offs of an insurance company. In particular, we model the investment, technical reserve, and financing structure of the insurer’s balance sheet. We also restrict our attention to the interesting case where regulation is necessary because insurers and claimholders have opposite interests, and the former could take advantage of the nonexistence of sophisticated stakeholders.
2.1. Set Up We propose a formal model inspired by Rochet(2004). Consider an economy with two dates (t = 0, 1), where insurers sell insurance contracts at t = 0. These contracts will cover policyholders’ risks at t = 1. This situation is the so-called “inversion of the production cycle” described in most insurance textbooks: insurance companies sell their products—and pocket insurance premium—for a Risks 2018, 6, 74 4 of 12 very long time before settling claims. According to Plantin and Rochet(2007), this fact and the absence of a tough, sophisticated claimholder provide a rationale for the prudential regulation of insurance companies. Prudential regulation generally states that insurance companies (i) must estimate their outstanding liabilities toward policyholders in a sufficiently conservative way, and (ii) must finance an excess of investment in assets over such estimates with their own capital. In order to capture these elements in a simple way, we work with the following balance sheet constraint of an insurance company at t = 0:
A = pR˜ + E, (1) where A stands for risky assets whose return will be realized at t = 1, R stands for technical reserves representing the outstanding liabilities toward policyholders, and E stands for equity capital. At t = 1, an insurance company will be able to cover its claims only if the returns generated by its risky investment portfolio are large enough. Investment returns are equal to θA with probability p˜, and zero otherwise (θ is the gross return rate on investment). This probability depends on how much effort an insurer exerts in monitoring its investments. That is, there is a classical moral hazard problem in the relationship between managers and other stakeholders. If the insurer exerts effort, the probability of success is p˜ = p, whereas this probability decreases to p˜ = p − ∆ if the insurer shirks. The level of effort is unobserved by third parties, and exerting effort entails a private cost of B (per unit of investment) to the insurer. Prudential regulation would impose minimum requirements to R and E. The timeline of the model is summarized in Figure1.
Assets returns are θA p˜
t = 0 t = 1
Insurance contracts are signed Insurer chooses Given R and E, insurer invests A monitoring effort
Assets fail
Figure 1. Timeline without systemic risk.
In order to study the interesting case in which moral hazard is an issue, we introduce the following assumptions:
Assumption 1: (p − ∆)θ + B < 1 < pθ.
Assumption 1 implies that the investment portfolio has a positive net present value only when it is monitored by the insurer. Otherwise stated, if the insurer shirks, the return of the assets plus the private benefit from shirking is less than the invested amount. Without this assumption, the solution would be trivial since the interest of insurers and claimholders will be perfectly aligned.