D S T Dynamic Solvency Testing Some Technical Factors

1. D S TDynamic Solvency TestingSome 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. Sample of Re-investment Strategy Asset Model

21. Sample of Yield for Government Bonds Asset Model

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 ModelsDynamic 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 ModelsDynamic Projection • In the first run: • In-force and assumed 1st 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 1st year projection will then be set up as the initial figures for the 2nd year projection;

26. Combining the ModelsDynamic 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 2nd year projection will then be set up as the initial figures for the 3rd year projection and so on;

27. Combining the ModelsDynamic Projection • Verifying the models and assumptions: • Projected results at the end of 1st 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