Capital Management for Conglomerates. Jennifer Lang BEc, FIA, FIAA Mark Young BSc, MAppStat

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Transcription:

Capital Management for Conglomerates Jennifer Lang BEc, FIA, FIAA Mark Young BSc, MAppStat

Agenda Managing capital in conglomerates Measures for individual types of company Banks Life insurers General insurers Funds managers Using risk based capital across conglomerates

Managing capital in conglomerates Financial Services companies have allocated capital using various methods: Banks have used value at risk (VaR) approaches Insurance companies have historically focused on asset liability modelling (ALM), or more generally, Dynamic Financial Analysis (DFA) Funds Managers have generally used regulatory requirements In essence these are approximating Risk Based Capital (RBC), concentrating on the key risks for each entity To manage capital in conglomerates, these methods need to be made consistent, and combined

Key questions for all entities Key questions to be answered for all entities: Why is capital being allocated? To determine total capital required OR To determine relative performance between products and companies What is the time horizon for reviewing risks? What capital is being allocated? Including or excluding goodwill The rest of this presentation assumes: Capital allocation for relative performance A one year time horizon Capital allocated excludes all goodwill generated

Banks Building Risk Based Capital Business Inputs Risk Building Blocks Model Risk Capital Attribute Capital By By Business Products Transactions Customers Activities Interest Rate Foreign Exchange Equity Commodity Default Risk Collateral Severity of Loss Operational Errors P/L Restatements Technology Investment Audit Results Regulatory Flags Market Risk Credit Risk Operating Risk Risk Capital Business Line market credit operating All three risks defined above are modelled separately, correlated within risks and then combined

Market Risk Portfolio Analysis Identify sources of market risk in portfolio (eg. treasury equities, options, pipeline) and A/L mismatch Calculate Value at Risk, using appropriate models Duration gap report on bank A/L Mismatch Calculate value at risk for present value charge in bank Bank market risk VAR Translate VAR into market risk capital Market risk frameworks within banks are generally very sophisticated, with allowances for interactions between complex positions on different instruments

Credit Risk Segment credit portfolio data (e.g., unrated, rated) Gather historical data (e.g., expected loss, default frequency, severity (loss given default)) Normalize and model data Conduct analysis Option 1 Option 2 Utilize UBOC portfolio data Combination Utilize external data (e.g., loan pricing, corporation, etc.) Unexpected loss Output Capital Credit risk is also reviewed using a value at risk framework, but the time horizon is generally longer than for market risk, as holding periods are longer for these risks

INTE RN AL FR AU D EX TER NAL FR AU D EMPLOYMENT PRACTICES & W ORKPLACE SAFETY CLIENTS, PRODUCTS & BUSINESS PRACT ICES DAMAGE TO PHYSICAL ASSETS EX EC UTI ON, DELIVERY & PROCESS MANAGEMENT BUSINESS DISRUPTION AND SYSTEM FAILURES TOTAL Corporate Finance Number 36 3 25 36 33 150 2 315 Mean 35,459 52,056 3,456 56,890 56,734 1,246 89,678 44,215 Standard Deviation 5,694 8,975 3,845 7,890 3,456 245 23,543 6,976 Tradi ng & Sales Number 50 4 35 50 46 210 3 441 Mean 53,189 78,084 5,184 85,335 85,101 1,869 134,517 66, 322 Standard Deviation 8, 541 13,463 5,768 11,835 5,184 368 35,315 10, 464 Re tail Banking Number 45 4 32 45 42 189 3 397 Mean 47,870 70,276 4,666 76,802 76,591 1,682 121,065 59,690 Standard Deviation 7,687 12,116 5,191 10,652 4,666 331 31,783 9,417 Commercial Banking Number 41 3 28 41 37 170 2 357 Mean 43,083 63,248 4,199 69,121 68,932 1,514 108,959 53, 721 Standard Deviation 6, 918 10,905 4,672 9,586 4,199 298 28,605 8,476 Payment & Settlements Number 37 3 26 37 34 153 2 321 Mean 38,774 56,923 3,779 62,209 62,039 1,363 98,063 48,349 Standard Deviation 6,226 9,814 4,205 8,628 3,779 268 25,744 7,628 Agency S ervices Number 44 4 31 44 40 184 2 386 Mean 46,529 68,308 4,535 74,651 74,446 1,635 117,675 58, 018 Standard Deviation 7, 472 11,777 5,045 10,353 4,535 321 30,893 9,154 Asset Management Number 40 3 28 40 36 165 2 347 Mean 41,876 61,477 4,081 67,186 67,002 1,472 105,908 52,217 Standard Deviation 6,725 10,599 4,541 9,318 4,081 289 27,804 8,238 Re tail Brokerage Number 48 4 33 48 44 198 3 417 Mean 50,252 73,773 4,898 80,623 80,402 1,766 127,090 62, 660 Standard Deviation 8069 12 71 9 5449 11182 4898 347 33365 9886 Insurance Number 43 4 30 43 39 179 2 375 Mean 45,226 66,395 4,408 72,561 72,362 1,589 114,381 56,394 Standard Deviation 7,262 11,447 4,904 10,063 4,408 312 30,028 8,897 Total Number 435 36 30 2 435 399 1,812 24 3,806 Mean 45,653 67,021 4,450 73,245 73,044 1,604 115,459 56, 926 Standard Deviation 7, 331 11,555 4,950 10,158 4,450 315 30,311 8,981 Operational Risk INDIVIDUAL LOSS EVENTS LOSS EVENT MATRIX LOSS DISTRIBUTIONS VAR CALCULATION TOTAL LOSS DISTRIBUTION 74,712,345 74,603,709 74,457,745 74,345,957 74,344,576 167,245 142,456 123,345 113,342 94,458 0 Frequency of events 1 2 3 Severity of loss 4 VaR Calculator e.g., Monte Carlo Simulation Engine Mean 99th Percentile Annual Aggregate Loss ($) 0-10 10-20 20-30 30-40 40-50 Operational risk modelling is much newer than the other two risks, as data is hard to find

Combining risks into capital VaR Approach Test Model Model Model Aggregate Outcomes Market Credit Operational Capital with Key Risk* Risk* Risk* Requirements Stakeholders * Activities will be performed concurrently Combining the main risk types into capital involves: Determining a holding period Understanding correlations between risks and products Determining risk levels

Insurers Dynamic Financial Analysis Inputs Economic scenarios Liability data Asset data Business Plans Cashflow Scenario Generator Models Product class level output Profit & loss accounts and Balance Sheets Company Structure / Consolidation Rules Aggregator and Analyser Strategies Outputs Capital Definitions Profitability by Product Class Comparison of different scenarios Other as defined

Risk based capital Both banks and insurers are aiming for risk based capital Risk Based capital allocates capital based on the relative risks borne by different businesses The superficial differences in approaches are mainly due to the major risks being different between insurance companies and banks To allocate capital for conglomerates, we need to go back to basics

Risk Based capital framework Choose the products for allocation of capital (eg mortgages, risk insurance) Determine a time frame for review of risks Develop a model to capture all sources of volatility of profits Allocate capital based on total levels of volatility of each product set Allow for risk sharing between products (using correlations between product sets Scale capital allocated to the total level being allocated

Capital Management feeds Performance Measurement Capabilities Performance Measurement Framework Economic Capital Framework Organisational and Business Unit Profitability Strategic Planning and Portfolio Management ALM / Provisioning Funds Transfer Pricing Framework Cost and Revenue Allocation Framework (ABC) Customer and Product Profitability Pricing Modules and Profitability Templates Operational Management Improved Risk / Return Positioning Feedback and Refinement

Discussion Is Risk based capital the best measure? What is the right duration of the risk? What are the key areas of volatility? How do you take into account correlations? How should goodwill be taken into account?

References Managing Bank Capital Chris Matten A Global Framework for Insurer Solvency IAA Insurer Solvency Assessment Party Assessment Working Target Surplus Developing an Industry Kent Griffin & Robert Baillie Approach