Filename Integrated Risk Management in a Financial Conglomerate Til Schuermann* Federal Reserve Bank of New York World Bank Risk Management Workshop Cartagena,

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Filename Integrated Risk Management in a Financial Conglomerate Til Schuermann* Federal Reserve Bank of New York World Bank Risk Management Workshop Cartagena, Colombia February 17, 2004 * Any views expressed represent those of the author only and not necessarily those of the Federal Reserve Bank of New York or the Federal Reserve System.

Filename 1 What Is a Financial Conglomerate?  Joint Forum definition (2001) “Any group of companies under common control whose exclusive or predominant activities consists of providing significant services in at least two different financial sectors (banking, securities, insurance)”  Virtually all of the large, internationally active multinational financial institutions are, to some degree, financial conglomerates –Strict “3 of 3” or weaker “2 of 3” definitions

Filename 2 Market Context  Rapid growth in scope of large, multi-line financial institutions –Consolidation –Financial deregulation –Globalization  Not just bigger, also (much) more complex  Major advances in risk measurement and capital management practices across the industry  Capital regulation still largely based around single business lines or ‘silo’ approach

Filename 3 What Is the Regulatory Issue?  Banks, securities firms and insurance companies all conduct trading business with –Many of the same instruments and –Many of the same counterparties, but... ... subject to very different regulatory capital charges  Differences are profound and pervasive –Differences in regulatory objectives –Differences in definition of regulatory capital –Differences in regulatory capital charges

Filename 4 Philosophical Differences About What Should Count as Capital  Differing assumptions about how to deal with a faltering firm –Securities regulators: liquidate without loss to customers or recourse to bankruptcy proceedings, emphasis on subordinated claims –Bank regulators: want time to detect and remediate, emphasis on patient money –Insurance regulators: ring-fence for protection of customers, emphasis on adequacy of technical reserves  Evident in capital ratios –Securities firms: ~5% –Banks: ~ 10% –Insurers Life: ~8% P&C: ~25%

Filename 5 Differing Definitions of Capital Net Worth: similarities more apparent than real –Mark to market accounting in securities firm –Mix of mark to market & book value in banks –Statutory accounting in insurance companies

Filename 6 Example of Different Treatments Banking Regulation Treat as commercial loan BIS 1: 8% Capital BIS 2: 2% Capital EU Credit Insurance Treat as credit insurance paying credit insurance premium of 1% pa. Solvency capital = 15% of premiums  0.16% of outstandings EU Life Insurance Treat as investment Implicit asset charge = 3% of outstandings  Consider a credit exposure to an ‘A’ rated counterparty

Filename 7 Key Questions and Approach 1.How should assessments of capital adequacy take into account diversification or concentration of activities within a conglomerate? 2.What are the implications for regulating the solvency of a multi-line financial conglomerate?  Our Approach –Adopt a top-down economic perspective –Focus on unique problems of risk aggregation within a conglomerate –Initially, make simplistic assumption that all risk types have multivariate normal distribution –Risk is taken to be 99% VaR

Filename 8 Risk Types and Distributions CreditMarketP&C CATP&C ExperienceBusinessEvent Operating RiskAsset RiskLiability Risk RISK Life AA- How to Aggregate?

Filename 9 Risk Types and Modeling Approaches  There is a large variety of measurement and modeling approaches

Filename 10 Risk Management in a Financial Conglomerate Financial Holding Company Financial Holding Company Correlation Very High Very Low ALM Non-Licensed Subsidiary Market Credit Insurance Operating P&C Insurance Company Life Insurance Company Insurance Universal Bank Market Credit ALM Operating ALM Market Credit Insurance Operating Credit Market Insurance ALM Operating

Filename 11 Levels of Risk Aggregation in a Financial Institution LEVEL 1 Within a Risk Type Commercial Credit ConsumerInternational LEVEL 2 Within a Subsidiary + Market + Operating LEVEL 3 Across Subsidiaries + BankInsurance

Filename 12 Diversification: Size of “Portfolio” and Degree of Correlation Typical Market vs. Credit Risk Correlation Geographic Diversification Level 1

Filename 13 Diversification Across Risk Types Within Universal Bank Level 2 Across Bank & Insurance Level 3

Filename 14 Diversification Across Risk Types: Financial Conglomerate

Filename 15 Summary of Results so Far  Diversification effects typically decrease at successive levels in an organization: Level 1 > Level 2 > Level 3  Provided standalone risks are correctly measured, incremental diversification benefits across banking and insurance fall into an expected range of 5-10%  Diversification effects are greatest when businesses are of similar size  Combining a bank with a P&C company produces the greatest diversification benefit because P&C and credit risks predominate and are uncorrelated

Filename 16 Alternative Interpretations Naive View HC CAP  Univ-Bank CAP + Ins CAP Level 3 diversification unimportant BIS 2 approach (deconsolidation) is right Counter View Result only valid if regulatory measures at Levels 1 and 2 fully reflect diversification Existing measures are inherently limited: –‘Lowest common denominator’ –Assume ‘average’ correlation for many risk types at Level 1 –Ignore cross-factor diversification at Level 2 BUT Risk Aggregation at Level 3 Can Only Be as Good as the Standalone Measures on Which It Is Based

Filename 17 Level 2: A More Sophisticated Approach  Goal was to model market, credit and operational risk of a typical large, internationally active bank  Market and credit risk distributions from market data  Operational risk distribution from industry (proprietary) database of operational risk events  Compare different ways of computing total risk distribution –Add-VaR: add-up marginal VaR to arrive at total Effectively BIS 2 –Normal-VaR: assume joint normality –Copula-VaR: use copulas to arrive at total risk distribution –Hybrid approach: assume elliptical distribution (not as strict as joint normal but almost as easy)  Risk is taken to be 99.9% VaR

Filename 18 Marginal Risk Distributions Market Credit Operational Total

Filename 19 Characteristics of Risk Distributions  Market  Credit  Operational Highest volatility Lowest skewness Slightly fat tails Moderate to high volatility Skewed Moderately fat-tailed Low volatility Very skewed Very fat-tailed

Filename 20 Impact of Correlation at 99.9% VaR   (market,credit) = 50%  vary  to operational risk

Filename 21 Bottom Line  Consistent ordering of approaches –Add-VaR > Hybrid-VaR > Copula-VaR > Normal-VaR –Add-VaR biggest: imposes perfect inter-risk correlation –Normal-VaR smallest since it imposes thinnest tails –The Hybrid approach is strikingly close to copula-VaR Use volatility multiples from marginals Incorporates correlation  Diversification benefits at 99.9% VaR can be substantial –Depending on correlations, 10% to 35%  As business mix or correlation shifts towards operational risk (very fat-tailed and skewed), 99.9% VaR increases dramatically –Normal-VaR fails especially here –Hybrid approach can handle this well (sensitive to tail shape of marginals)

Filename 22 What Has Been the Market Response? Risk Measurement Economic capital increasingly being adopted as “common currency” for risk across financial businesses Migration of methodologies from banking to insurance Diversification effects captured at successive levels Customized models sensitive to business mix Risk Management Conglomerates building up centralized risk and capital management units Dominant approach “hub and spoke” system Hub responsible for overseeing Group risk and capital planning (Level 3) Spokes responsible for risk management and transaction decisions within businesses (Levels 1 and 2)

Filename 23

Filename 24 Thank You!

Filename 25 Limitations of ‘Silo’ Regulation Inconsistency Capital requirements dependent on where risk is booked Boundaries breaking down due to product innovation Increasing demand/ potential for regulatory arbitrage Aggregation Concentration of risks across legal boundaries Diversification across risk classes within a legal entity Diversification of risks across business activities and operating companies Incompleteness Capital requirements of unlicensed operating companies Capital requirements/ funding structure of holding company ‘Strategic’ investments in non- financial companies