Financial Condition Reporting Practical Aspects

1. Financial Condition Reporting Practical Aspects GIRO / CAS Convention 2001 John P Ryan

2. 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

3. 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

4. Risk Management Circle Effective control requires quantification

5. Individual Risk Assessment.

6. Methods of Modelling Risk Financial Risk - investment models Financial Liabilities - actuarial models All Other - as operational risk

7. Insurance Company Risks

8. Financial Risks

9. RISK ACTUARIAL ASSESSMENT Concentration  Valuation ? Market value Market  Modelling volatility Reinsurance  Value, Bad debt Asset Risks

10. RISK ACTUARIAL ASSESSMENT Outstanding claims / IBNR  Unearned Premiums  Unexpired Risks  Discounting  Liability Risks

11. RISK ACTUARIAL ASSESSMENT Mismatch  Liability Risks

12. Financial Risks

13. RISK ACTUARIAL ASSESSMENT Pricing  But varies by class Growth / new classes  ? Impact on pricing assumptions Acceptance ? Concentration  Underwriting Risks

14. RISK ACTUARIAL ASSESSMENT PMLs  Reinsurance  Claims frequency / severity  Policyholders’ Reasonable Expectations ? Exposure Risks

15. RISK ACTUARIAL ASSESSMENT Expenses  Mergers & Acquisitions ? Investment Strategy  Business Risks

16. RISK ACTUARIAL ASSESSMENT Dividend commitments  Debt interest / repayment  Gearing  Financing Risks

17. Insurance Company Risks

18. 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 Operational Risks

19. RISK ACTUARIAL ASSESSMENT Planning  DFA / Market Analysis Data quality / availability ? Reputation X Operational Risks

20. RISK ACTUARIAL ASSESSMENT Legal / Legislative ?  Possible future. Some known changes Social ? Political Taxation X Confiscation / Nationalisation X External Risks

21. RISK ACTUARIAL ASSESSMENT Dependency ? Group structure  Regulatory X External Risks

22. Operational Risk • ASSESSMENT OF OPERATIONAL RISK

23. 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

24. Quantification of Operational Risk Operational Risk Collect Data Delphi Techniques Industry Specific Produce a Model Model Quantify Risk Quantify Corroborate Results

25. Development of loss curves Probability of Loss Expected Level of Loss Budgeted Loss Amount of Loss Based on data

26. 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

27. 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

28. 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

29.  Reliability of Loss Estimates 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 Own Claims Internal Interviews External Research External Interviews      Claims Size (US$ billions)                 50% 60% 70% 80% 90% Example Output from a Large Loss Study

30. Probability of Loss Expected Level of Loss Budgeted Loss Amount of Loss Based on data Including interviews Development of loss curves

31. Loss Limit 100 80 60 40 20 Amount of Loss in Data 80 80 80 70 50 Data for loss curve Amount of Losses in Data & Interviews 105 100 90 75 50

32. 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”

33. 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

34. 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

35. 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

36. Core Operational Risk Analysis Framework involves Business Process and Resource / Risk Classes Physical Assets Relationship (Liability) Other External Technology People Resource Classes Business Process Business Management Reputation Transactional Process

37. Free Cash Flow Investment Op. Cash Flow Working Capital Distribution Fixed Assets Taxes Gross Margin Costs Revenues Volume Price Event Risk Financial Risk Distribution Channel Business Risk Risk profiles are linked to financial measures using a financial value tree approach

38. 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

39. Adding Each Separately • 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 Consolidated with many tail dependent risks Risk Consolidated largely independent risks Cost Evaluating risks altogether

40. 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

41. 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

42. Why Does This Matter? The RBC’s are very different for different approaches Var ECOR Operational Risk Investment Risk Combined

43. 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

44. Insurance to cover Operational Risk • This is a non-trivial subject. • Basel has many doubts.

45. 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

46. 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