1. D S T Dynamic Solvency Testing Some Technical Factors Presentation to One-Day Seminar Held by PAI and AAJI Jakarta, December 8, 2005

2. Introduction Current economic and investment environments fluctuates a lot –Posing greater uncertainty to financial condition Solvency testing on future conditions needs to be done –To foresee the financial difficulties at earlier stages –To prepare constructive solutions Static vs. Dynamic Testing

3. Introduction Static Testing –Liabilities are projected separately from the assets Many deficiencies as the liability position at one point will affect the assets Dynamic Testing –Liabilities and assets are combined in projection –Incorporate one or more economic or business scenarios where the assumptions can vary by year of projections –Not meant to give exact results as no absolute correlation among assumptions used –External factors sometime have more significant impact than model assumptions –Projections can be deterministic, dynamic, or stochastic

4. DST – What is it?? A tool to identify: –Possible treats to satisfactory financial condition –Actions which lessens the likelihood of the threats –Actions which negate any of those threats if it is materialized DST is defensive –addresses threats to financial conditions rather than exploitation of opportunity

5. DST – Scenarios DST standard requires scenarios testing consisting of: –Base scenario –Adverse scenarios –certain forecast period, usually 5 years Each scenario takes into account: –Not only in-force policies but also policies assumed to be sold during the forecast period –Both insurance and non-insurance operations e.g. Operations of insurer’s trust company subsidiary

6. DST – Base Scenario Insurer’s business plan Its assumptions are expected assumptions consistent with assumptions of policy liability valuation before margins for adverse deviations Award if base scenario differs from business plan, because: –implies difference in outlook between insurer and actuary –Actuary would accept business plan as base scenario unless business plan’s assumptions are so inconsistent or unrealistic that resulting report would be misleading.

7. DST – Adverse Scenarios Adverse scenario is plausible, assumptions about matters to which financial condition is sensitive –Adverse scenarios vary among insurers and may vary over time for a particular insurer –Selection of appropriate adverse scenarios may require extensive analysis Main criteria for an appropriate adverse scenario are pertinence to insurer and plausibility of occurrence

8. DST – Adverse Scenarios Adverse scenario is plausible, assumptions about matters to which financial condition is sensitive Adverse scenarios vary among insurers and may vary over time for a particular insurer Selection of appropriate adverse scenarios may require extensive analysis Main criteria for an appropriate adverse scenario are pertinence to insurer and plausibility of occurrence –Example of a pertinent adverse scenario would be an economic downturn for insurer whose investments involve asset deterioration risk or whose marketing is sensitive to economic cycle

9. DST – Adverse Scenarios Death Rate –Medical breakthrough which permanent lowers death rates –Regulations which limit insurer’s freedom to underwrite –Epidemic increasing death rates Sickness and accident rates –Increase in disability rates –Decrease in recovery from disability rates –Retrenchment of government of security programs Withdrawal rates –Decrease in withdrawal rates for lapse supported policies –Increase in withdrawal rates for other individual policies –Loss of a distribution system

10. DST – Sample of Adverse Scenarios Interest rate swing –Parallel swing in interest rate curve –Non-parallel swing –Widening (or narrowing) of interest crediting spreads –Change in value of derivatives Asset deterioration –Increase in default rates –Poor return on equity securities –Prolonged deterioration in real estate returns Sales –Loss of distribution system –Capital strains from high sales volume –Expense strain from low sales volume –Increased competition

11. DST – Sample of Adverse Scenarios flexible premium policies –adverse variation in premium patterns for UL type products Expenses: –Inflation –Low sales Government action –New taxation –New unfavorable regulation Reinsurance –Failure of a re-insurer –Increase reinsurance cost Adverse currency fluctuation

12. DST – How to Make It Works We need to build models –Liability’s model –Asset’s model Liability’s model should model all or majority of the products sold and to be sold in the future Asset’s model should model current assets as well as the expected assets to be purchased in the future Liability and Asset models should be incorporated

13. Liability Model Generally be based on majority of the product portfolio –Limited time and resources –Insignificant impact of certain group of portfolio Determining the sample space –Short-term vs. long term business Depending on the pricing assumptions and nature of the benefit provided YRT may not be significant issue as we can revise the premium structure Certain benefits might pose long-term liability to the company

14. Liability Model Determining the sample space –UL business Depending on whether there is any investment guaranteed Investment guaranteed portion should be modeled –Group business Depending on the pricing assumptions and nature of the benefit provided YRT may not be significant issue as we can revise the premium structure Certain benefits might pose long-term liability to the company

15. Liability Model In-force portfolio –Should be based on the actual portfolio at the valuation date –Assumptions used usually consist of: Mortality and morbidity Lapse or persistency Other related assumptions

16. Liability Model New Business –Should include existing products still selling –Should also include new products to be sold in the near future May include new pricing assumptions if differ from the existing products –Should make assumptions on: Growth rates Products mix Sales weight Seasonal adjustment, if any

17. Liability Model Model Validity –The projected results should be compared to the budget figures –The current production might be taken into account E.g. Projection made in April 05 should take into account production up to March 05 Production mix Sales weight –Both by product and by currency

18. Asset Model In-force portfolio –Should reflect the current figures as of validation date Source from investment department –Should include information on: Coupon/income Coupon frequency Redemption dates MV, BV, and PV of the assets Assets’ currency –Should exclude assets regarded as cash May include bank deposit < 1 year –Might need to scale up the assets to reflect the sample space taken in liability model

19. Asset Model New Purchases / Sales –Should reflect the future re-investment strategy Separate by types of assets and by currency –Should reflect future yields on the chosen assets Taking into account current trends, assumed spread to be maintained, term to maturity, and default risks Model validity –Assumptions should be verified by investment dept –Re-investment strategy should be in line with the overall company’s strategy

20. Asset Model Sample of Re-investment Strategy IDR Asset type% Reinvest Bank Deposit10% Gov ’ t Bond 50% Corp. Bond30% Stocks10% USD Asset type% Reinvest Bank Deposit25% Gov ’ t Bond 45% Corp. Bond40%

21. Asset Model Sample of Yield for Government Bonds YTMYield (before default) <17.29 18.03 28.71 3N/A 49.84 YTMYield (before default) 23.71 106.67 YTMYield (before default) 510.06 610.31 710.28 810.38 910.49 1010.44

22. Combining the Models Deterministic Projection –Assumptions are pre-determined at the valuation date –Usually no changes during the projection period –Not suitable for fluctuate economic conditions Dynamic Projection –Used to project the effect of one or more economic or business scenarios simultaneously; –Scenarios are usually vary by year of projection;

23. Combining the Models Stochastic Projection –Much more advance approach, but might not be fully applicable –Calculations on stochastic variables are repeated for as many simulation as required Example of stochastic variables: investment return vs. expense inflation –Stochastic models: the Wilkie (1995) model, the Jump Equilibrium by Andrew Smith of Bacon & Woodrow, a simple Random Walk model.

24. Combining the Models Dynamic Projection General ideas: –Liability and asset projections need to be combined –The projections are run one period at a time; The projections are run parallel; The projected results are combined usually at the end of each projection period –Impact from liabilities projection to the assets –Need to determine a set of assumptions when combining the projections: Bonus rate to be declared; Valuation interest rates; Investment strategy; etc.

25. Combining the Models Dynamic Projection –In the first run: In-force and assumed 1 st year new business is incorporated; Net cash flow at the end of projection period should incorporate assumptions set up specifically for the projection period-end –Such as assumptions on bonus to be declared, re-investment strategy, production volume, pricing, and mix of future new business Net cash flow after adjustments will be used to buy investment vehicles based on re-investment strategy; Figures at the end of 1 st year projection will then be set up as the initial figures for the 2 nd year projection;

26. Combining the Models Dynamic Projection –In the next run: In-force and assumed new business is incorporated; Assets projected included assumed new assets purchased at the end of last period; Figures at the end of 2 nd year projection will then be set up as the initial figures for the 3 rd year projection and so on;

27. Combining the Models Dynamic Projection –Verifying the models and assumptions: Projected results at the end of 1 st projection year should be in line with the company budget; Might need to re-adjust the assumptions to be in line with the budget

28. Interpreting the Results The projected results should be interpreted based on the assumptions used; –Best estimate assumptions Should analyze the impact on total assets, premium income, profit, premium reserve, solvency ratio, and surplus; Need to explain the reasons of significant deviation, if any; Need to incorporate the major products characteristics; –Lapse supported products; –Investment-type products; –Savings products;

29. Interpreting the Results –Assumptions for Adverse Scenarios Should analyze the impact on total assets, premium income, profit, premium reserve, solvency ratio, and surplus; Need to explain the trend changes as compared to base scenario; Need to incorporate all adverse assumptions;

30. Interpreting the Results –Assumptions for Adverse Scenarios examples; –Increase in new business will have effect on the products with heavy first year strains; –Decrease in lapse will have negative impact on surplus if major products sold are lapse-supported products –Decrease in investment return usually has negative impact on surplus. However, the impact could be significant if the majority of products are investment-guaranteed;

31. Interpreting the Results –Recommendations to Board of Directors Should clearly state the main concerns and their primary causes; –Investment issues; –Operation issues; –Strategic marketing issues; –Product issues; Proposed remedies should be general; –Broad enough for management to expand the idea; –Actuaries are not supermen – know everything exactly; –Sometime only needs the shareholders’ commitment; –What matters at the end is to control the expenses as budgeted;

32. Thank You