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Financial Condition Reporting Practical Aspects GIRO / CAS Convention 2001 John P Ryan Wednesday 3 October 2001 Financial Condition Reporting - Practical Aspects The FSA’s view Assessment of individual risk Modelling operational risk Importance of tail dependency Relevance of risk measures Overlaying hard to quantify risks with a DFA model Use of insurance to reduce capital requirements Q:\client\ryanjp\2001\jr0460sh.ppt 2 Institute of Actuaries paper on FCA Provides a framework for evaluating a company’s financial position in relation to the risk it covers. Concentrates on non-life insurance but covers the principles for all companies. It covers both readily quantifiable risks and those not so readily quantifiable e.g. management succession risks. The Profession’s response to the FSA proposal. FSA will apply to all financial Institutions. Corley Report also calls for FCR reports for Life Co’s Q:\client\ryanjp\2001\jr0460sh.ppt 3 Risk Management Circle Identify Administer Control Finance Effective control requires quantification Q:\client\ryanjp\2001\jr0460sh.ppt 4 Individual Risk Assessment. Q:\client\ryanjp\2001\jr0460sh.ppt 5 Methods of Modelling Risk Financial Risk - investment models Financial Liabilities - actuarial models All Other - as operational risk Q:\client\ryanjp\2001\jr0460sh.ppt 6 Insurance Company Risks Risks Financial Retrospective Balance sheet Risks Prospective Business Risks Non Financial Operational External Q:\client\ryanjp\2001\jr0460sh.ppt 7 Financial Risks Financial Retrospective Balance sheet Risks Asset Risks Liability Risks Q:\client\ryanjp\2001\jr0460sh.ppt 8 Asset Risks RISK ACTUARIAL ASSESSMENT Concentration Valuation ? Market Modelling volatility Reinsurance Value, Bad debt Market value Q:\client\ryanjp\2001\jr0460sh.ppt 9 Liability Risks RISK ACTUARIAL ASSESSMENT Outstanding claims / IBNR Unearned Premiums Unexpired Risks Discounting Q:\client\ryanjp\2001\jr0460sh.ppt 10 Liability Risks RISK Mismatch ACTUARIAL ASSESSMENT Q:\client\ryanjp\2001\jr0460sh.ppt 11 Financial Risks Financial Propective Business Risks Underwriting Risks Exposure Risks Business Risks Financing Risks Capital / Debt Q:\client\ryanjp\2001\jr0460sh.ppt 12 Underwriting Risks RISK ACTUARIAL ASSESSMENT Pricing But varies by class Growth / new classes Impact on pricing ? assumptions Acceptance ? Concentration Q:\client\ryanjp\2001\jr0460sh.ppt 13 Exposure Risks RISK ACTUARIAL ASSESSMENT PMLs Reinsurance Claims frequency / severity Policyholders’ Reasonable Expectations ? Q:\client\ryanjp\2001\jr0460sh.ppt 14 Business Risks RISK ACTUARIAL ASSESSMENT Expenses Mergers & Acquisitions ? Investment Strategy Q:\client\ryanjp\2001\jr0460sh.ppt 15 Financing Risks RISK ACTUARIAL ASSESSMENT Dividend commitments Debt interest / repayment Gearing Q:\client\ryanjp\2001\jr0460sh.ppt 16 Insurance Company Risks Risks Financial Retrospective Balance sheet Risks Prospective Business Risks Non Financial Operational External Q:\client\ryanjp\2001\jr0460sh.ppt 17 Operational Risks RISK ACTUARIAL ASSESSMENT Fraud X But might come across evidence Administrative ? Could help assess some procedures Technology X But might help with system requirements Management X But might come across evidence Q:\client\ryanjp\2001\jr0460sh.ppt 18 Operational Risks RISK ACTUARIAL ASSESSMENT Planning DFA / Market Analysis Data quality / availability ? Reputation X Q:\client\ryanjp\2001\jr0460sh.ppt 19 External Risks RISK ACTUARIAL ASSESSMENT Legal / Legislative ? Possible future. Some known changes Social ? Political X Taxation Confiscation / Nationalisation X Q:\client\ryanjp\2001\jr0460sh.ppt 20 External Risks RISK ACTUARIAL ASSESSMENT Dependency ? Group structure Regulatory X Q:\client\ryanjp\2001\jr0460sh.ppt 21 Operational Risk ASSESSMENT OF OPERATIONAL RISK Q:\client\ryanjp\2001\jr0460sh.ppt 22 Management and Business Risk Some can be modelled using econometric or causal modelling techniques Some are really risks for shareholders rather than capital issues Stress testing can be a useful quantification technique Insurance often cannot be used for this type of risk Q:\client\ryanjp\2001\jr0460sh.ppt 23 Quantification of Operational Risk Operational Risk Collect Data Delphi Techniques Industry Produce a Model Specific Model Quantify Risk Quantify Corroborate Results Q:\client\ryanjp\2001\jr0460sh.ppt 24 Development of loss curves Probability of Loss Expected Level of Loss Budgeted Loss Amount of Loss Based on data Q:\client\ryanjp\2001\jr0460sh.ppt 25 Quantification of Operational Risk It is more complex than pricing conventional insurance risk The risks are more under control of the institution than many insured perils Changes in practice can have a material impact Organisations do not like to admit to Operational Risk losses Some are not readily amenable to statistical analysis e.g. management succession risk Q:\client\ryanjp\2001\jr0460sh.ppt 26 Scenarios Distributions may not be the best approach to evaluating certain types of operational risk Test the survival of the organisation to adverse scenarios Especially suitable for “people risks” e.g. succession planning Q:\client\ryanjp\2001\jr0460sh.ppt 27 Data based approach Not many databases around Not all losses are disclosed Controls and mode of operation may render some data to be inappropriate Low frequency / high severity risk requires a different approach Some “operational risks” are budgeting items Q:\client\ryanjp\2001\jr0460sh.ppt 28 Example Output from a Large Loss Study Reliability of Loss Estimates 1 Own Claims 0.9 Claims Size (US$ billions) 0.8 External Research Internal Interviews External Interviews 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 50% 60% 70% 80% 90% Q:\client\ryanjp\2001\jr0460sh.ppt 29 Development of loss curves Probability of Loss Expected Level of Loss Budgeted Loss Amount of Loss Based on data Including interviews Q:\client\ryanjp\2001\jr0460sh.ppt 30 Data for loss curve Loss Limit Amount of Loss in Data Amount of Losses in Data & Interviews 100 80 105 80 80 100 60 80 90 40 70 75 20 50 50 Q:\client\ryanjp\2001\jr0460sh.ppt 31 Questions The difficulty is the need to estimate the right tail in a skew distribution How good is the left of the curve at predicting the right tail Use of Bayesian statistics or credibility theory What distributions fit the data What techniques are best at supplementing the data for “missing large claims” Q:\client\ryanjp\2001\jr0460sh.ppt 32 Conclusions - Data based methods Data based methods are the traditional actuarial technique for insurance claims, they are intuitively acceptable There are major deficiencies in using data based methods for operational risk not present in insurance data The major problem is non-reporting of large claims Useful check on the reality of other methods Q:\client\ryanjp\2001\jr0460sh.ppt 33 What are the other methods? Delphi techniques Decision trees and casual modelling ? Fuzzy Logic ? Others ? Use data bases for left side and other techniques for right side Q:\client\ryanjp\2001\jr0460sh.ppt 34 Delphi Technique Key Drivers of Business Unit What are the risks to each Business Unit What are the likely frequency If loss occurs what is the likely cost Fit curves following interview technique Model uncertainty Combine all results Q:\client\ryanjp\2001\jr0460sh.ppt 35 Core Operational Risk Analysis Framework involves Business Process and Resource / Risk Classes Physical Assets Technology People Relationship (Liability) Other External Resource Classes Business Process Transactional Process Business Management Reputation Q:\client\ryanjp\2001\jr0460sh.ppt 36 Risk profiles are linked to financial measures using a financial value tree approach Free Cash Flow Investment Op. Cash Flow Gross Margin Revenues Distribution Taxes Working Capital Costs Volume Price Event Risk Financial Risk Distribution Channel Business Risk Probability Distribution of Economic Loss Due to Fire Risk Probability Distribution of Market Share Lost Due to New Entrant 0.515 0.481 0.447 0.413 0.379 0.345 0.311 0.277 0.243 10% 8% 6% 4% 2% 0% 0.209 250.86 224.86 198.85 172.85 146.84 94.84 120.84 68.83 42.83 Probability 10% 8% 6% 4% 2% 0% 16.82 Probability Fixed Assets Q:\client\ryanjp\2001\jr0460sh.ppt 37 Importance of the risk measure Var implicitly assumes “elliptic risks” Operational risk does not satisfy this condition Market Risk needs to be frequently updated hence the importance of Var Operational Risk does not change rapidly Hence “equivalent Var” will not change rapidly Q:\client\ryanjp\2001\jr0460sh.ppt 38 Evaluating risks altogether Adding Each Separately Risk Consolidated with many tail dependent risks Consolidated largely independent risks Cost Adding the efficient frontiers will overstate the costs for a given risk as no adjustment is made for diversification credits This at a minimum changes the choices or risk loadings even if all strategies are ranked in the same way Q:\client\ryanjp\2001\jr0460sh.ppt 39 Risk Measures Var works well for symmetrical risks ECOR is better for skew risks such as most insurance risks A coherent measure needs to be used across the group as a whole Beware of tail dependency Other constraints are also needed such as a requirement to maintain a credit rating Q:\client\ryanjp\2001\jr0460sh.ppt 40 ECOR reflects both the probability and the severity of ruin ECOR is the present value of expected deficits in excess of economic capital ECOR is derived as the probability of a loss times the severity of the loss In today’s dollars Sum of all loss events Reflects solvency risk tolerance measure and assigned capital The “ECOR ratio” is the ECOR divided by the present value of expected customer payments ECOR is a better solvency risk measure than probability of ruin because it reflects the cost of ruin, not simply the likelihood of event Q:\client\ryanjp\2001\jr0460sh.ppt 41 Why Does This Matter? The RBC’s are very different for different approaches Var ECOR Combined Operational Risk Investment Risk Q:\client\ryanjp\2001\jr0460sh.ppt 42 Coherent Risk Measures To be coherent a risk measure (p) must satisfy four conditions: (i) Translation Invariance p(x + .r) = p(x) - (ii)Sub additivity p(x1+ x2) p(x1) + p(x2) (iii) Positive homogeneity for o p(x)= p(x) (iv) Monotoniaty If x y p(Y) p(x) Var fails the sub additivity property Q:\client\ryanjp\2001\jr0460sh.ppt 43 Insurance to cover Operational Risk This is a non-trivial subject. Basel has many doubts. Q:\client\ryanjp\2001\jr0460sh.ppt 44 Coverage Gaps If complete cover is not available then capital will need to be held against remaining risk Insurance should mitigate operational risk cost and so should be allowable Operational Risk models would need to be run with and without insurance Contracts with material exclusions may not mitigate overall capital requirements much All Risks Cover is preferable Much operational risk violates an underwriting rule that the insured should not be able to manipulate his loss experience Some risks may not be insurable e.g. management succession risk Q:\client\ryanjp\2001\jr0460sh.ppt 45 Claims Disputes Some financial impact as a dispute creates coverage gap Change insurance practice of conducting investigations at point of claim to investigating at point of sale Financial Enhancement Ratings (FER) Different in conditions (DIC) coverage Q:\client\ryanjp\2001\jr0460sh.ppt 46