1Do Insurance Companies Pose Systemic Risk? J. David Cummins2013 China International Conferenceon Insurance and Risk ManagementKunming, ChinaJuly 18, 2013Copyright J. David Cummins, 2013, all rights reserved. Not to be reproduced without author’s permission.11111
2Outline of Presentation What is Systemic Risk?Systemic Risk: Primary Indicators – Factors Used to Identify Systemically Important Financial InstitutionsSystemic Risk: Contributing Factors – Factors Exacerbating Vulnerability to CrisesConclusions: Does Insurance Pose Systemic Risk?Based on primary indicators and contributing factorsAre Insurers Instigators and/or Victims of Systemic Risk?An econometric analysis using Granger causality
3This Presentation Based on Two Papers Cummins, J. David and Mary A. Weiss, 2013, “Systemic Risk and the Insurance Industry,” forthcoming in Georges Dionne, ed., Handbook of Insurance, 2d ed. (Springer).Chen, Hua, J. David Cummins, Krupa Viswanathan, and Mary A. Weiss, 2013, “Systemic Risk and the Inter-Connectedness between Banks and Insurers: An Econometric Analysis,” forthcoming, Journal of Risk and Insurance.Other relevant papersChen, Hua, J. David Cummins, Krupa Viswanathan, and Mary A. Weiss, 2013, “Systemic Risk Measures in the Insurance Industry: A Copula Approach,” working paper, Temple University, PhiladelphiaCummins, J. David and Mary A. Weiss, 2013, “Systemic Risk and the Regulation of the U.S. Insurance Industry,” working paper, Temple University, Philadelphia.Cummins, J. David and Mary A. Weiss, 2012, “Systemic Risk and the U.S. Insurance Sector,” forthcoming, Journal of Risk and Insurance.To obtain the papers, please
5What Is Systemic Risk?The risk that an event will trigger a loss of economic value or confidence in a substantial segment of the financial system serious enough to have significant adverse effects on the real economy. Group of 10 (2001).Systemic financial risk involvesA system-wide financial crisis accompanied by a sharp decline in asset values and economic activityThe spread of instability throughout the financial system (contagion)Sufficient to affect the real economy World Economic Forum (2008).Systemic risk is exposure to extreme correlations
6Financial Crises and Systemic Risk Prices of risky assets drop sharplyPrices of safe assets increase (flight to quality)Asset price volatility increasesLiquidity dries up (rising bid-ask spread & price impact)Financial institutions become financially distressedCredit markets dry up, economic activity depressedFinancial systemic risk: Financial crisis in which many institutions become financially distressed, with a potential impact on real economic activityFinancial distress of one or a few institutions does not necessarily equal systemic risk!
7Too-Big-To-Fail Has Been With Us For a Long Time and Isn’t Confined to Financial Institutions Industry/CompanyYearType of AssistancePenn Central Railroad1970$676.3 million in loan guarantees – Gov’t spent $19.7 billion and got back about $4 billionLockheed1971Government loan which was paid offNew York City1975Loans and loan guaranteesChrysler1980Loan guarantees and warrants – Gov’t earned a profit of about $660 millionContinental Illinois1984Government took 80% ownership and phrase TBTF was coinedAirline Industry2001Government bought stock below market and provided loan guaranteesAutomobile industryGovernment takes equity stake in GM & Chrysler = $80 billionUS Government bailouts of industries in the US isn’t new.In 1970, the government took over Penn Central, injected some 19.7 billion in funds and provided $676 billion in government guarantees,In 1971 we provided a loan to LockeedAnd in 1975, NYC, who had engaged in profligate spending was provided loans and Loan guarantees.Our recent investments in Chrysler and GM aren’t new either. In 1980 we provided loan guarantees and obtained warrants for the support provided to Chrysler.In 2001 we bailed out several of the airlines, buying stock and providing loan guarantees.In terms of Banks, the first real significant venture, aside from the forbearance provided to Citicorp was when Continental Illinois bank went underWhere did it came from for banks?
9Primary Indicators and Contributing Factors The Question: How to identify systemically risky markets and institutions?Primary indicators: Factors used to identify systemic markets and institutionsContributing factors: Determine the vulnerability of an institution or market to systemic eventsAn institution may be systemic in terms of primary indicators but not vulnerable in terms of contributing factors
10Primary Indicators of Systemic Risk Size – Macroeconomic Importance of InsurersSize not limited to conventional measures such as assetsVolume of transactions, exposure to off-balance sheet positions, and derivatives also play a roleInterconnectedness – degree of correlation and potential for contagion among institutionsLack of substitutability –Are there effective substitutes for an institution’s products?Are the products critical to the functioning of the financial system
11Primary Indicators: Size Conventional measures – assets or equity, absolutely or relative to GDPOff-balance sheet exposures and volume of transactions processed“Callability” of positions taken – marginability, etc.Notional value of derivatives exposure (e.g., AIG’s credit default swaps positions)“Too Big to Fail” being replaced by “Systemically Important Financial Institution (SIFI)”Reflects inadequacy of conventional size measures
12Designating SIFIs Financial Stability Oversight Commission (FSOC) Established as part of U.S. Treasury in 2010Can designate banks and non-banks as SIFIsThresholds for SIFIs≥ $50 billion of assets, andMeets or exceeds any one of several thresholds$30 billion notional CDS for which firm is reference credit$3.5 billion of derivative liabilities$20 billion of total outstanding debt (bonds, etc.)15-to-1 leverage ratio (assets/equity)10% ratio of short-term debt to assets
13Primary Indicators: Interconnectedness Could Insurers Cause a “Run on the Bank”?Interconnectedness – extent to which financial distress at one or a few institutions increases probability of distress at other institutionsNetwork or “chain” effects on both sides of balance sheet or through derivatives exposures, off-balance sheet commitments, etc.Existence of “contagion” in the economyInterconnectedness creates conditions that trigger “runs on the bank”
14All Systemic Financial Crises Involve “Runs” In crises, investors seek cash at all costsAs prices no longer adjust supply, access to credit becomes centralMaturity mismatch compounds shock and spreads runsRapid withdrawals lead to “fire sales,” prices crashLosses induce margin calls, more fire salesRuns are both cause and consequence of extreme correlationCrises that do not spread to general credit market do not qualify (e.g., “dot-com” bubble collapse in )
15Types of “Runs”In the past (e.g., 1930s), financial crises often involved “retail runs”Many depositors try to withdraw money from banks simultaneouslyDeposit insurance has virtually eliminated retail bank runsRecent financial crisis involved “wholesale runs”Banks refused to provide liquidity to troubled institutions such as Lehman BrothersAIG counterparties demanded higher margin deposits and the unwinding of asset lending relationshipsEssentially, a “run” on the shadow banking system
16“Runs” Triggered by Exposure to Common Shocks Common shock may be exposure to agricultural depression, real estate, or oil pricesIn the Crisis of , common shock was the bursting of the housing price bubbleBursting of bubble triggered crises inInter-bank lendingCommercial paperMarket for short-term repurchase agreements (“repos”)Essentially a run on the shadow banking system
17“Too Big to Fail” & “Too Interconnected to Fail” Institutions that pose significant systemic risk are viewed as “Too Big to Fail” -- e.g., failure would cause ripple effects throughout the economy due to the sheer size of the enterprises“Too Interconnected to Fail” -- Firms with multiple counterparty relationships could trigger a cascading chain of failures – “domino effect”
18Primary Indicators: Lack of Substitutability Could Unavailability of Insurance Cause a Financial Crisis?Substitutability – extent to which other firms or segments of the financial system can provide the same services provided by the failed institutionsFor substitutability to be a problem, the services must be critical to the functioning of other institutions or the financial systemPayment system – operational arrangement that enables individuals and institutions to transfer fundsSettlement system – enables transfer of securities and cash to settle tradesLiquidity system – inter-bank lending, repos, etc.
19Contributing Factors: Enhance Vulnerability to Systemic Events LeverageMeasured conventionally as debt to equityOff-balance sheet positions, options exposure, and “marginability” of positions also creates leverageLeverage and “loss spirals”Declines in asset values erode net worth much faster than the asset declines themselves (“leverage”)E.g., at 10-to-1 assets/equity ratio, 5% decline in assets means 50% decline in equityIf many institutions are affected at same time, selling assets puts additional pressure on prices generating a loss spiral
20Contributing Factors: Liquidity Risk and Maturity Mismatches Liquidity risk – vulnerability to shocks is increased to the extent the institution holds illiquid assetsDifficulties in obtaining financing may trigger need to sell assets – problematic for illiquid assetsEspecially serious if other institutions also illiquidAsset-liability maturity mismatch raises liquidity riskIn Financial Crisis, Shadow banks used short-term commercial paper, overnight lending, and repos to finance longer-term assetsDisappearance of short-term financing triggered need to sell illiquid longer-term assets
21What Are Repos?Repos – abbreviation for “sale and repurchase agreement”Defined: Sale of securities together with an agreement for the seller to buy back the securities at a later dateRepurchase price > original sale price, the difference representing interest, the “repo rate”Seller is a borrower, using securities as collateral for a cash loan at specified interest rateThe buyer acts as a lenderDuring financial crisis, repo buyers refused to extend credit to firms such as Lehman
22Contributing Factors: Complexity Enhances Vulnerability to Shocks Dimensions of complexityComplexity of organization or group structure – firms offering banking, insurance, and investment products more complex than single industry firmsGeographical complexity – multi-national firms face variety of local and regional risk factorsProduct complexity exposes firms to risks that may not be fully understoodE.g., AIG Financial Products CDS transactionsComplexity aggravated by opacityAIG’s positions were opaque, preventing market adjustment for over-exposure
23Contributing Factors: Government Policy and Regulation Government policy and regulation can contribute to financial system fragilityDeposit insurance and guaranty funds create moral hazard that may lead to crises – buyers with government guarantees have no incentive to monitor“Too Big To Fail” policies also create moral hazardComplexity of AIG created regulatory blind spot that led to AIG’s near collapse (nominally regulated by Office of Thrift Supervision)US government policy permitted investment banks to become over-leveraged, helping to precipitate crisisLack of regulatory oversight contributed to the housing bubble and mortgage backed securities crisis
24Size Risk: The Macro-Economic Importance of Insurers 24
25Total Assets: US Banks and Insurers Assets: Banks $14.6 trillion, insurers $6.8 trillion.Source: Federal Reserve Flow of Funds accounts.
26Total US Life and P-C Premiums: % of GDP Source: A.M. Best Company, American Council of Life Insurance, St. Louis Federal Reserve Bank.
27US GDP From Financial Services (Value Added) Source: US Department of Commerce, Bureau of Economic Analysis.
28Insurance Companies: Share of Total Assets Source: Federal Reserve Flow of Funds Accounts.
29Conclusions: How Big Are Insurers? Insurers have $6.8 trillion in assetsAbout 50% as large as commercial banksOnly about 8% of total US financial assetsInsurers do not have large share of any asset marketInsurer insolvencies resolved gradually so even large insolvency would not lead to liquidity problemsInsurers not very important source of GDP (< 3%)Therefore, as a sector insurers do not pose systemic risk due to their size alone
30Interconnectedness Risk: Could Insurers Cause A “Run on the Bank”? 30
31Interconnectedness: Insurers and Other Financial Firms I Do US insurers invest heavily in other financial institutions?Investment in Banks:5.6% of insurer assets are in bank bonds1% of insurer assets and in bank equitiesInvestment in Securities firms:1.6% of insurer assets in securities firm bonds1% of insurers assets in securities firm equitiesConclusion: Insurers are not vulnerable to stock and bond declines from financial firms
32Interconnectedness: Insurers and Other Financial Firms II Are insurers a significant source of funds for other financial institutions?Life insurers supply:9.4% of outstanding bonds for banks14.1% of outstanding bonds for securities firmsHowever, bonds account for only 10% of financing for banks and securities firmsConclusion: Banks and securities firms are not dependent on insurers to finance their activities
33Interconnectedness Within Insurance Industry Reinsurance is the primary source of intra-industry interconnectednessReinsurance creates risk of counterparty defaultReinsurer failure to pay claims can trigger insurer insolvenciesInsolvent insurers then default on their reinsurance counterpartiesResult: A Reinsurance spiralReinsurance counterparty risk present for bothReinsurance transactions with affiliatesNon-affiliated reinsurance transactions
34Measures of Reinsurance Interconnectedness Reinsurance premiums cededInsurance in force ceded (life)Reinsurance receivables – funds owed by reinsurers to ceding companyWrite-down of liabilities due to reinsurance:Reserve credit taken (life)Net amount recoverable from reinsurance (P-C)If reinsurers fail:Default on receivables and ceded premiumsLiability write-downs canceled, increasing leverage
35Extent of Reinsurance Interconnectedness Reinsurance premiums ceded to affiliates & non-affiliatesP-C premiums ceded = 17.2% of surplusLife premiums ceded = 38.0% of surplusInsurance in force ceded (life) = 55.3% of surplusReinsurance recoverables –For 25% of P-C insurers, recoverables > 40% of surplusFor 25% of life insurers, recoverables > 100% of surplusWrite-down of liabilities due to reinsurance:Reserve credit taken (life) averages 149% of surplusRecoverables (P-C) average 39% of surplus
36Have Reinsurance Failures Been a Significant Source of Insurer Insolvency? 36
37P/C Impairments: Triggering Events Deficient loss reserves, inadequate pricing, and rapid growth are the leading triggers. Investment, catastrophe, and reinsurance losses play a much smaller role.Source: A.M. Best: Impairment Review, Special Report, May 2, 2011.
38L-H Impairments: Triggering Events Life insurers more susceptible to affiliate problems.Inadequate pricing, affiliate problems, rapid growth, and investments are primary causes of L/H insolvencies.Source: A.M. Best: U.S. Life/Health – Impairment Review, Special Report, May 23, 2011.
39Reinsurance Interconnectedness: Conclusions Reinsurer failure traditionally not a major source of insurer insolvencyMany insurers do have large reinsurance counterparty exposure relative to surplusTherefore, reinsurance failure could threaten solvency of individual insurers and create industry-wide crisisHowever, it is unlikely that even a major intra-industry crisis would spill over into broader financial marketsTherefore, reinsurance causes intra-industry vulnerability but not systemic risk
40Interconnectedness and Non-Core Activities Insurer non-core (“banking”) activities can create interconnectedness and systemic riskExample: AIG Financial ProductsNon-core activities that may be systemicCredit derivatives transactionsAsset lending programsFinancial guarantees and other off-balance sheet commitmentsReliance by insurers on short-term financingSubsidiaries with high exposures relative to capitalImproved regulation needed to prevent crises
41Substitutability Risk: Could Unavailability of Insurance Cause a Financial Crisis? 41
42Lack of Substitutes and Crises For lack of substitutability to cause a crisis both of the following must be true:The product must be unavailable and have no substitutes or alternative suppliersThe product must be essential for the functioning of other institutions or the financial system
43Quantitative Measures of Substitutability For lack of substitutability to cause a crisis:Concentration (market share of top firms) – highly concentrated markets more likely to trigger crisis due to lack of substitutesEase of entry into the marketIf entry barriers exist, new entrants prevented form providing vital products or financial servicesEase of entry can mitigate concerns about lack substitutability
44Concentration and Regulation in Insurance Concentration in insurance: USTop 4 (10) non-life groups have 29% (50%) of marketTop 4 (10) life groups have 24% (45%) of marketEntry of new insurers relatively easy (both on shore and off-shore, e.g., Bermuda)Nationally significant insurers reviewed quarterly by the NAIC – Financial Analysis Working GroupTherefore, widespread insolvencies causing insurance unavailability are extremely unlikelySurvivors or new entrants would provide coverage
45Do Insurance Products Have Substitutes? Life InsuranceMostly asset accumulation products rather than mortality/longevity risk bearingMany non-insurance substitutes for asset accumulation and investment productsBanks, mutual funds, securities firms, etc.Many insurers available to fill coverage gaps resulting from insolvency of one or a few firmsTherefore, lack of substitutes not a problem for life insurance
46Do Insurance Products Have Substitutes? Property-Casualty (PC) InsuranceMainly provide risk management and risk-bearingNo real substitutes for individual buyers (auto insurance) and small commercial customersBut many insurers are available to fill coverage gaps resulting from one or a few insolvenciesLarge corporate buyers have substitutes – self insurance, captives, securitizationTherefore, lack of substitutes not a problem for P-C insurance
47Is Insurance Critical to Functioning of Economy? Insurance clearly enables the economy to function more smoothly by enabling individuals and businesses to take more riskHowever, it is difficult to argue that insurance is as important as banking, the payments system, or the settlement systemVarious insurance markets regularly experience availability crises without significantly affecting real economic activityTherefore, unavailability of insurance unlikely to create a systemic crisis
48Contributing Factors: How Risky Are Insurers? 48
49Contributing Factors: Leverage and Insolvency Rates 49
50Equity Capital-to-Assets Ratios Source: Federal Reserve Flow of Funds accounts, American Council of Life Insurance, FDIC.
51Premiums-to-Surplus Ratios: US Insurers Insurance leverage ratios have been improving over time.
52Failure Rates: US Banks & Insurers Bank failure rate was more strongly affected by the crisis.
53P/C Insurer Impairments: 1969-2011 Financial Crisis Did Not Trigger Many Impairments.Source: A.M. Best; Insurance Information Institute
54Why Did PC Impairments Increase in 2011? Lingering effects of financial crisisCrisis appears to have had delayed effect on P-C insurersNear record catastrophe lossesInsured losses of $116 billion2nd largest year for catastrophes in recorded history (largest was 2005 when Hurricanes Katrina, Rita, and Wilma and other events caused losses of $123 billion)“Soft market” phase of underwriting cyclePC insurance supply increases and prices decrease
55PC Insurer Impairments & Combined Ratio Impairment rates highly correlated with underwriting performance.Correlation with combined ratio = 64%Source: A.M. Best; Insurance Information Institute
56Life/Health Insurer Impairments:1976-2011 Life/health impairments less cyclical than P/CSource: A.M. Best.
57LH Impairment Frequency & Profits LH less correlated with profits than PC, Corr = -20%Source: A.M. Best.
58PC Guaranty Fund Assessments: 1978-2010 Correlation = 81%.Source: A.M. Best Company, National Conference of Insurance Guaranty Funds.
59LH Guaranty Fund Assessments: 1988-2010 Source: A.M. Best, National Organization of Life and Health Insurance Guaranty Associations.
60PC insurers beat the S&P during crisis, life insurers did not. US Insurance Stock Indices vs. S&P 500PC insurers beat the S&P during crisis, life insurers did not.
61Insurer Leverage & Solvency: Conclusions US regulated insurance companies are highly solventInsolvency rates are lowGuaranty fund costs are lowFinancial crisis had little impact on insurer insolvenciesLife insurers give some cause for concernMore highly leveraged than PC but about same as banksMore interconnected than PC insurers (susceptibility to affiliates)LH stocks harder hit by crisis than PC stocksInter-connectedness does not pose serious solvency threat for PC insurers based on past experienceMonolines (insurers of bonds) are a different storyNot traditional insurance
62Contributing Factors: Liquidity Risk and Asset-Liability Mismatches 62
63Liquidity Risk Danger signals for life insurance industry ABS/MBS = 194% of surplus (only 27% of surplus for PC insurers)Privately placed bonds = 204% of surplus (only 10% of surplus for PC insurers)But, life insurers have significant cash from operations43.8% of surplus28.1% of benefit paymentsConclusion: Liquidity risk exists from mortgage-backed securities and private placements for life but not PC insurers – partly offset by cash flow
64Maturity MismatchesAsset and liability maturities tend to be long-term for insurers (in absolute terms and relative to banks)Property-casualty liabilities not “putable”Must experience a loss and file a claim to collectMost life insurance long-term and not putableExceptions: cash value life insurance, variable life, and variable annuitiesHowever, usually a penalty for early surrenderConclusion: Maturity mismatch not a problem but some putability risk for life insurance
66Complexity AIG prime example of complexity Complicated group structureGeographically dispersedComplex, new financial productsLarge multi-national insurers common in insurance industryLife insurance more complex than PCMost life products have embedded derivativesConclusion: Complexity is a problem for the large, multi-product, multi-national insurers
67Contributing Factors: Government Policy and Regulation 67
68Do Guaranty Funds Create Moral Hazard? In theory, mis-priced guaranty fund coverage provides incentives for excessive risk-takingIn practice, guaranty funds do not seem to be a problemNo solvency crisis for US regulated insurance companies – now or during Financial CrisisGuaranty fund assessments have been very lowPossible rationale:Risk-based capital (introduced in 1994) blunts insurer incentives for excessive risk-takingGF protection is incomplete (low maximums, etc.)
69Regulation of Complex Multi-Nationals Generally, complex multi-national financial service firms lead to gaps in regulationNo one regulator has responsibility for entire firmDifferent national regulators have responsibility for nationally domiciled subsidiariesBanking and insurance subs may be regulated by different organizationsAt least in US, regulation of insurers mostly at the individual insurer rather than the group levelConclusion: Better supervision needed for insurance groups and multi-national financial services firms
70Conclusions: Does Insurance Pose Systemic Risk? 70
71P-C Insurance May Not Create Systemic Risk “Runs” are not possibleTo obtain funds, it is necessary to have a claimUnlike bank deposits, which are instantaneously “putable”Insurance not involved in liquidity creation, payments system, or business/consumer lendingInsurers hold only small proportion of total invested assets in the economyInsurance claim payments are not a major financial asset for any economic sectorHowever, intra-sector reinsurance exposure could cause “reinsurance spiral” spreading across the P-C industryNot clear if this would be a true systemic event, i.e., not likely to affect other financial institutions or the real economy
72Does Life Insurance Pose Systemic Risk? Why LI may be systemically riskyLife insurance investment products are susceptible to “runs” (withdrawals and/or suspension of premium payments/annuity considerations)Life insurers are thinly capitalized in comparison with P-C insurers, but similar to banksLife insurers hold large amounts of ABS/MBS and private placements relative to surplusInsurance guaranty fund system probably not adequate for a major run or liquidity crisisLife insurers owned by banks (and vice versa) could add to fragility of banking system
73Does Life Insurance Pose Systemic Risk? Why LI may NOT be systemically riskyLife insurance sector not involved in payments system, liquidity creation, credit creation, etc.Life insurers own only small proportion of stocks and bonds in the economy (about 6%)Life insurance is a small proportion of household financial assets (about 3%)Many substitutes exist for life insurance policiesLife insurers not major employers (< 2% of non-farm civilian labor force)Disappearance of the entire sector would be tragic but sustainable
74Systemic Risk In Insurance: Non-Core Activities As AIG debacle shows, the main systemic risk posed by the insurance industry comes from insurer participation in “banking” activities, e.g., credit default swaps (CDS) and other derivativesSwiss Re data shows that insurers and reinsurers accounted for 33% of CDS market in early 2000sAs with AIG, most insurers are not adequately capitalized to sustain large CDS meltdownInsurance groups should required to increase transparency of CDS operationsTighter regulation of leverage at non-insurance subs
75Overall Regulatory Implications Regulators need to improve capabilities in group supervisionRegulation of non-insurance subsidiaries to head off future AIG-type crisesImproved measures of group level solvency riskRegulators need to improve international coordination of insurance supervision for multi-national insurersCoordinate national regulators & the International Association of Insurance Supervisors
76Hua Chen, J. David Cummins, Krupa Viswanathan, and Mary A. Weiss Systemic Risk and the Interconnectedness Between Banks and Insurers: An Econometric AnalysisHua Chen, J. David Cummins, Krupa Viswanathan, and Mary A. WeissPresented at: 2013 CICIRMKunming, ChinaJuly 18, 2013Copyright J. David Cummins, 2013, all rights reserved. Not to be reproduced without author’s permission.117611
77Prior Literature: Insurers & Banks Two Prior Papers measure systemic risk in banking and insurance using market dataBillio et al. (2012) – monthly stock returnsHedge funds, brokers, banks, and insurance companiesPrincipal components and linear Granger causality testConclusion: All four sectors have become highly interrelated in the past decade, increasing the level of systemic risk in the banking and insurance industriesAcharya et al. (2010) – daily stock dataSystemic expected shortfall (SES) – propensity to be undercapitalized when the system as a whole is undercapitalizedConclusion: 9 insurers among the top 50 systemic financial institutions
78“Are insurers instigators or victims of systemic risk?” Purpose of Our PaperDevelop and implement a robust systemic risk measure for insuranceInvestigate interconnectedness between banking and insurance during financial crisisWe use CDS quotes and intra-day equity returns to estimate systemic risk in the insurance and banking industries“Are insurers instigators or victims of systemic risk?”
79Purpose II Our systemic risk measure relies on Daily-frequency market price data for CDS (Markit)Intra-day trading data on stock prices (TAQ)Systemic risk measure is risk-neutral, forward-looking and economically intuitiveDirection of interconnectedness investigatedLinear and non-linear Granger causalityCorrecting for heteroskedasticity
80Contribution to Literature First paper to use data on CDS spreads and intra-day stock prices to study systemic risk for the insurance industryDifferent econometric methodology than Billio et al. (2012) and Acharya et al. (2010)New evidence on whether insurers are victims or sources of systemic risk
81Measuring Systemic Risk Two major components that determine risk profile of sample firms:Probability of default of each insurer (based on CDS premiums – Markit.com)Default correlation (estimated indirectly from underlying equity return correlation -- TAQ)Measure of systemic risk uses portfolio credit risk methodology (developed by Huang et al., 2009)
83A Measure of Systemic Risk Estimate forward-looking, risk-neutral indicator of systemic risk of insurance industry:“price of insurance against financial distress (DIP)”Define financial distress by choosing a threshold (e.g., 15%) such that the ratio of portfolio credit losses to total liabilities of the insurance sector is equal to or above threshold
84A Measure of Systemic Risk II Construct a hypothetical portfolioConsists of debt instruments issued by the sample banks/insurers, weighted by the liability size of each firm.Conduct Monte Carlo simulation (Tarashev and Zhu 2008)Probability of joint default (PD)Loss given default (LGD)Systemic risk measure: the price of insurance against financial distress
85A Measure of Systemic Risk III Systemic risk measure is calculated as risk-neutral expectation of portfolio credit losses that reach at least a minimum share (15%) of sector’s total liability= systemic risk measure for insurance industryLt = portfolio credit lossesTLt = total liability of insurance sector at time t
86A Measure of Systemic Risk IV Similar estimation procedure is performed for firms in banking sector to obtainused to analyze degree of interconnectedness between insurance and banking industries.
87A Measure of Systemic Risk V Advantage of method is that does not require large sample of firmsHuang et al. (2009) – 12 banksConclusions apply to relatively large firms since they have traded CDSLarge insurers have lower default probabilities than smaller insurers so results apply more strongly to small insurers
88Granger Causality Tests Testing Granger causality involves using F-tests to determine whether lagged information on a variable X provides any significant information about a variable Y in the presence of lagged Y.If not, then X does not Granger-cause YLinear Granger causality tests conducted firstThen do nonlinear Granger causality testsNonlinear Granger causality test uses the residuals from the linear causality testThen do Hiemstra-Jones (HJ) Test on residuals
89Data and Systemic Risk Measures Sample SelectionSample of banks and insurers (Markit, SIC code)Check whether the firm is publicly traded on a US exchange (TAQ)Focus on 5-year, Senior, No Restructuring CDS Quotes on FridayFill in missing valuesUse other quotes on the same day for conversionTrace back one (two,…, five) day(s) beforeInterpolationDetermine a common time periodOur sample: 11 insurers and 22 banks with CDS quotes over the period Feb 2002 to May 2008
91Average Probability of Default Default probability begins to spike in 3rd quarter of 2007.
92Systemic Risk MeasureAfter measuring probabilities of default and asset return correlations, the systemic risk measure can be computed for each weekSystemic risk measure represents a weekly price of insurance against distressed losses over the following three months.To make comparisons, unit price of insurance = ratio of nominal price to total liabilities of sample firms in each sector
93Linear Granger Causality Tests Distress Insurance Premiumsare not stationaryDifferenced time series are stationaryLinear causality tests are performed on the differenced series
94Linear Granger Causality Tests The results imply that systemic risk of insurers Granger-causes systemic risk of banksAlso, systemic risk of banks Granger-causes systemic risk of insurersHowever, results of BDS tests indicate that nonlinearities are present in the univariate systemic risk measures for both banks and insurersTherefore, we must conduct nonlinear Granger causality testsBDS = Brock-Dechert-Scheinkman.
95Control for Conditional Heteroscedasticity If conditional heteroskedasticity exists, causality test results can be biasedResiduals from Granger-causality tests revealLittle autocorrelationConditional heteroskedasticity existsTherefore, use GARCH (1,1) model to assess whether the bi-directional causality changesRe-do linear and nonlinear Granger tests using GARCH
96Non-Linear GARCH Models: Main Results Nonlinear effect of insurers on banks is highly significant at 1 lagSignificance fades after 3 lagsBanks in contrast have persistent predictive power on insurers up to 5 lagsSystemic risk of banks has longer duration of impact on insurersImpact is also stronger than insurer effect on banks
97Interconnectedness: Stress Testing Stress testing conducted to study the impact of systemic risk movements in the banking sector on the insurance sector and then vice versaA hypothetical shock in systemic risk of banking sector is fed into GARCH regression to generate future dynamic movements of systemic risk in the banking and insurance sectorsShocks of 5%, 10%, 15% and 20% are appliedSystemic risk of insurance sector fed into GARCH model as well to generate future dynamic movements of systemic risk
99Non-Linear Tests: Conclusions Banks create economically significant systemic risk for insurers but not vice versaBased on linear and non-linear Granger causality tests correcting for heteroskedasticityTherefore, insurers seem to be victims of systemic risk rather than instigatorsBanks are instigators of systemic risk
100Systemic Risk: Policy Implications Regulators should focus on banks to prevent/ameliorate systemic shocks from banksRegulators should focus on non-core rather than insurance activities of large insurersInsurance regulators should focus on mitigating effect of shocks from banks (e.g., investment restrictions and tighter capital requirements for life insurers)
102Further InformationAmerican International Group, 2009, AIG: Is the Risk Systemic? Powerpoint presentation (New York).De Bandt, Olivier and Philipp Hartmann, 2000, Systemic Risk: A Survey (Frankfurt, Germany: European Central Bank).Geneva Association, 2010, Systemic Risk in Insurance: An Analysis of Insurance and Financial Stability (Geneva, Switzerland).Group of 10, 2001, Report on Consolidation in the Financial SectorHarrington, Scott E., 2009, “The Financial Crisis, Systemic Risk, and the Future of Insurance Regulation,” Journal of Risk and Insurance 76:Kaufman, George G., 1996, “Bank Failures, Systemic Risk, and Bank Regulation,” The CATO Journal 16:Kaufman, George G., 2000, “Banking and Currency Crises and Systemic Risk: Lessons from Recent Events,” Federal Reserve Bank of Chicago Economic Perspectives 24: 9-28.Swiss Re, 2003, Reinsurance – A Systemic Risk, Sigma No. 5/2003 (Zurich, Switzerland).World Economic Forum, 2009, Global Risks 2009 (Geneva, Switzerland).Cummins, J. David and Mary A. Weiss, 2012, “Systemic Risk and the U.S. Insurance Sector,” working paper, Temple University, Philadelphia.
103My Research on Systemic Risk Cummins, J. David and Mary A. Weiss, 2013, “Systemic Risk and the Insurance Industry,” forthcoming in Georges Dionne, ed., Handbook of Insurance, 2d ed. (Springer).Chen, Hua, J. David Cummins, Krupa Viswanathan, and Mary A. Weiss, 2013, “Systemic Risk and the Inter-Connectedness between Banks and Insurers: An Econometric Analysis,” forthcoming, Journal of Risk and Insurance.Chen, Hua, J. David Cummins, Krupa Viswanathan, and Mary A. Weiss, 2013, “Systemic Risk Measures in the Insurance Industry: A Copula Approach,” working paper, Temple University, PhiladelphiaCummins, J. David and Mary A. Weiss, 2013, “Systemic Risk and the Regulation of the U.S. Insurance Industry,” working paper, Temple University, Philadelphia.Cummins, J. David and Mary A. Weiss, 2012, “Systemic Risk and the U.S. Insurance Sector,” working paper, Temple University, Philadelphia.To obtain the papers, please
105Reinsurance Exposure: Recoverables from Non-Affiliates, P-C Insurers Reinsurance Recoverables/Policyholders Surplus From Non-affiliated ReinsurersCeded paid lossesCeded unpaid lossesCeded IBNRCeded unearned premiumsCeded commissionsMinus funds held from reinsurersNormal range: 50% to 150%Un-weighted average for groups = 43% (2008)
106Reinsurance Exposure: Ceded Reinsurance Leverage from Non-Affiliates Ceded Reinsurance Leverage From Non-Affiliated Reinsurers/Policyholders SurplusReinsurance recoverablesCeded balances payableCeded premiums writtenMinus funds held from reinsurersNormal range: Component of gross leverage. Gross leverage range is 5 to 7Un-weighted average for groups = 70% (2008)
107Reinsurance Recoverables/Surplus: Groups For 26% of groups, non-affiliate recoverables > 50% of surplusReinsurance recoverables from non-affiliated reinsurers, including ceded paid losses, unpaid losses, IBNR losses, unearned premiums and commissions less funds held from reinsurers. Source: Best’s Key Rating Guide, Data are for 2008.
108Reinsurance Receivables/Surplus: Industry Non-affiliate receivables = 28% of industry surplus in 2008.Reinsurance recoverables from non-affiliated reinsurers, including ceded paid losses, unpaid losses, IBNR losses, unearned premiums and commissions less funds held from reinsurers. Source: Best’s Key Rating Guide, Data are for 2008.
109Reinsurance Leverage/Surplus: Groups For 30% of groups non-affiliate leverage > 75% of surplus.Reinsurance recoverables, ceded balances payable, and ceded premiums written less funds held divided by policyholders surplus. Source: Best’s Key Rating Guide, Data are for 2008.
110Reinsurance Leverage/Surplus: Industry Non-affiliate leverage = 40% of industry surplus in 2008.Reinsurance recoverables, ceded balances payable, and ceded premiums written less funds held divided by policyholders surplus. Source: Best’s Key Rating Guide, 2009.
112US Life Insurers: 12 Month Change in Premiums (as of June 30, 2009) Source: A.M. Best Company.
113AIG: What Went Wrong?AIG’s traditional insurance operations did not cause its meltdownAIG’s problems came from:Credit default swaps out of AIG Financial Products(Supposedly) regulated by Office of Thrift SupervisionUS insurance regulators had no jurisdictionSecurities lending program of life subsidiariesIndicates need for more regulatory scrutiny in the futureUS regulators do have jurisdiction if lending is out of regulated life insurance subsidiaries
114AIG Revenues Before the Crash 12 months ending 12/31/2006.
115AIG’s Credit Default Swaps AIG sold CDS contracts, mostly to European banks (i.e., writing bond default insurance)Banks were using the swaps to reduce regulatory capital, relying on AIGs overall credit rating (regulatory arbitrage)AIG Financial Products had about $500 billion in CDS outstanding but virtually no capitalAIG’s models supposedly showed that losses on the CDS portfolio were virtually impossibleLosses due to model risk and managerial moral hazard
116AIG’s Securities Lending Operation AIG loans securities to broker dealer or bank (e.g., to cover short selling or for diversification)Borrower posts collateral in form of cash or high quality securitiesAIG reinvests the collateral and earns spread between yield on invested assets and yield on underlying securitiesAIG had $82 billion in liabilities for securities lending as of year-end 2007, $69 billion in August 2008
117AIG Securities Lending: What Went Wrong Declines in value of mortgages and other assets in reduced value of reinvested collateral in securities lending programsMany of the counterparties in the securities lending operation were the same institutions holding AIG CDSAs asset values declined, borrowers terminated the securities lending arrangement toImprove liquidityReduce exposure to AIG’s credit riskAt the same time, AIG had to post additional collateral for the CDS transactions as underlying “insured” asset values declinedEssentially, a “run on the bank” by AIG’s counterparties
118The Bailout: Payments to AIG Counterparties CounterpartyCDS Trans.Asset LendingTotalGoldman Sachs8.104.8012.90Societe Gen.11.000.9011.90Deutsche Bank5.406.4011.80Barclays1.507.008.50Merrill Lynch4.901.906.80Bank of Amer0.704.505.20UBS3.301.705.00BNP ParibusOthers14.7011.6026.3049.6043.7093.30
119US Insurer Assessments vs. AIG Total US life and P-C assessments: $18.8 billionFederal assistance to AIG (as of June 30, 2009): $136 billionNot necessarily a net lossButTotal assets of largest insurers: 2011Met Life: $612.8 billionState Farm: $135.2 billionSource: A.M. Best Company, Harrington (2009).
120Failure Costs: Met Life and State Farm (% of Life & PC Industry Assets, resp.) Source: A.M. Best Company, author’s calculations.
121What Is Systemic Risk Policy Trying to Prevent? Runs on banks – traditional problemContagion – information asymmetriesBanking system collapse –Continental bankCorrespondent bank collapse – counterpartiesJobs would be lostThreat to settlement systemThreat to payments systemFear that Infrastructure of short-term money market and OTC derivatives would not handle failure of significant counterpartyCast doubt on soundness of other counter parties (e.g., case of Bear Stearns)As time has gone on, it seems that we have evolved from specific concerns such asTraditional concerns about runs on banks andContagion –due to information asymmetriesTo some broader concerns about banking system collapseIn the case of Continental bank Correspondent bank collapse – counterpartiesJobs would be lost – (St Germain)But some like Conover talked about unthinkable financial system collapse and Congressman St. Germain was concerned at that time about job lossThreat to large dollar settlement system and network effectsFear that Infra structure of short term money market and OTC derivatives would not handle failure of significant counter party and might cast doubts on the soundness of other counter parties (Bernanke on Bear Stearns)Panic due to loss of confidence (Warsh)Risks to system due to failure of “highly interconnected” firm“Unpredictable consequences of a failure for broader financial system” (Geithner)Reaction of counterparties of other firms that might come under future government control (Kohn on AIG). – only a psychologist and not an economist is qlualified to assess the risks
122Systemic Risk Policy Is Trying to Prevent II Panic due to loss of confidenceRisks to system due to failure of “highly interconnected” firms“Unpredictable consequences of a failure for broader financial system”Reaction of counterparties of other firms that might come under future government controlAIG was large, complex and interconnected whose failure would impose losses on counterparties and also endanger the entire world’s financial sector (Bernanke-Morehouse University)As time has gone on, it seems that we have evolved from specific concerns such asTraditional concerns about runs on banks andContagion –due to information asymmetriesTo some broader concerns about banking system collapseIn the case of Continental bank Correspondent bank collapse – counterpartiesJobs would be lost – (St Germain)But some like Conover talked about unthinkable financial system collapse and Congressman St. Germain was concerned at that time about job lossThreat to large dollar settlement system and network effectsFear that Infra structure of short term money market and OTC derivatives would not handle failure of significant counter party and might cast doubts on the soundness of other counter parties (Bernanke on Bear Stearns)Panic due to loss of confidence (Warsh)Risks to system due to failure of “highly interconnected” firm“Unpredictable consequences of a failure for broader financial system” (Geithner)Reaction of counterparties of other firms that might come under future government control (Kohn on AIG). – only a psychologist and not an economist is qlualified to assess the risks
123Preview of ResultsAfter adjustment for heteroscedasticity, impact of banks on insurers found to be stronger and of longer duration than impact of insurers on banksStress tests indicate that banks create significant systemic risk for insurers & not vice versaInsurers are primarily victims rather than instigators of systemic risk
124Measuring Systemic Risk: Methodologies Huang et al. (2009): Distress Insurance PremiumAcharya et al (2010): Systemic Expected ShortfallAdrian and Brunnermeier (2010): CoVARZhou (2010): Multivariate extreme value theoryBillio et al (2012): Principal Components, Causality testsInsurers can be a source of systemic risk to some extent.
125Nonlinear Granger Causality Tests II Diks and Panchenko (2005, 2006)HJ test could produce spurious results in the presence of conditional heteroskedasticityRoss (1989), Andersen (1996)Volatility of a time series can measure the rate of information flow.Use the GARCH model to assess whether the bi-directional causality changes.
126Sample Firms IIOf 11 insurers, 8 are classified as property-liability insurersOf remaining three,Lincoln National had only life-health operationsMetLife group has property-liability operationsPrudential divested property-liability operations, but owned these operations at the beginning of sample.