Annuity capital risk managment ne act nov 2012
- 1. Annuity Capital Risk Management Actuaries’ Clubs of Boston and Hartford & Springfield Kendrick Lombardo FSA, MAAA November 15, 2012 © 2012 Towers Watson. All rights reserved.
- 2. AGENDA Agenda Economic environment FIA capital risk management issues VA capital risk management issues Summary 2 © 2012 Towers Watson. All rights reserved.
- 3. Economic Environment © 2012 Towers Watson. All rights reserved.
- 4. ECONOMIC ENVIRONMENT Very low interest rates are the most significant capital risk management challenge facing the industry Pressure on new products (all annuities) Risk increase on lapse supported products (e.g., GLWB) Increased cost of VA hedging and general account ALM challenges for FIA 4 © 2012 Towers Watson. All rights reserved.
- 5. FIA Capital Risk Management © 2012 Towers Watson. All rights reserved.
- 6. FIA CAPITAL RISK MANAGEMENT The risk management of FIAs is subject to multiple inputs and constraints Base Contract Riders Cap management ALM ALM Hedging? Hedging Fixed Indexed Annuities U.S. GAAP U.S. Statutory FAS 133 / 157 AG 33 / 35 SOP 03-1 State specific? GLWB statutory reserving in a low rate environment is a critical FIA capital management issue 6 © 2012 Towers Watson. All rights reserved.
- 7. FIA CAPITAL RISK MANAGEMENT Guaranteed FIA GLWB income rates Average of effective withdrawal rates (includes impact of bonuses and rollups) for 1) issue age 55, wait 5 years, 2) issue age 65, immediate 3) Issue age 60, wait 5 years and 4) Issue age 60, wait 10 years 7 © 2012 Towers Watson. All rights reserved.
- 8. FIA CAPITAL RISK MANAGEMENT Guaranteed FIA GLWB income rates reduced Average of effective withdrawal rates (includes impact of bonuses and rollups) for 1) issue age 55, wait 5 years, 2) issue age 65, immediate 3) Issue age 60, wait 5 years and 4) Issue age 60, wait 10 years 8 © 2012 Towers Watson. All rights reserved.
- 9. FIA CAPITAL RISK MANAGEMENT Capital management actions taken by FIA carriers Product changes Commission decreases Premium bonus decreases Income rate decreases Rollup rate decreases / making rollup simple interest Pursuing new statutory reserving regimes AG 43 (standard scenario & stochastic) Modified AG 33 (e.g., add low lapses) Enhancing ALM capabilities Improving GLWB assumptions Refinement of dynamic lapses, withdrawals, waiting periods and mortality Modifying hedging programs Account for GLWB at a macro level Refinement of index hedge programs Merger & Acquisition (M&A) activity 9 © 2012 Towers Watson. All rights reserved.
- 10. VA Capital Risk Management © 2012 Towers Watson. All rights reserved.
- 11. VA CAPITAL RISK MANAGEMENT Capital risk management issues in VA market Low interest rates Impact on equity sensitivity of AG 43 reserves and C3P2 capital Rho hedges can create exposure to rising interest rates on a statutory basis Make impact of policyholder behavior more significant Companies are working on a number of fronts to improve their capital risk management Reflection of hedging in financial projections Reflection of statutory reserves / capital projections Refining policyholder assumptions Product designs changes Other developments Benefit buyouts Renewal premium limits M&A 11 © 2012 Towers Watson. All rights reserved.
- 12. VA CAPITAL RISK MANAGEMENT Reflection of hedging in financial projection models Hedging approach generally impacted by a number of factors, including: Accuracy of results Complexity of implementation, validation, inputs and analysis Computational demands (software and hardware) Range of industry practice is shown below We believe the industry has Explicit Projection of shifted towards using more Hedging Transactions explicit projections of hedging transactions Accuracy Proxy for Hedging Transactions Simpler methods still remains popular, given the complexity Change in Liabilities of projecting hedging Approach transactions, but they have their limitations Reinsurance Approach Sophistication 12 © 2012 Towers Watson. All rights reserved.
- 13. VA CAPITAL RISK MANAGEMENT Reflection of reserves and capital in projection models Factor Based Approaches Stochastic-on-Stochastic Less refined More refined Develop set of factors Real-world scenarios May vary based on Considerations Product feature Number of scenarios Duration Time steps ITM Other possibilities: Final analyses only? Standard scenario only Focus on TAR only Advanced techniques 13 © 2012 Towers Watson. All rights reserved.
- 14. VA CAPITAL RISK MANAGEMENT Policyholder Behavior Policyholder behavior has caused large surprises Many companies are working on enhancing their capabilities Data – Inforce extracts – Transaction/exposure data for experience analysis Techniques – Predictive modeling Granularity of financial models There is still significant variation in the industry A significant issues are Interest rate related behavior for GLWBs Dynamic lapse rate slopes Floor lapse rates Non-user withdrawal cohorts and their other behavior 14 © 2012 Towers Watson. All rights reserved.
- 15. Summary © 2012 Towers Watson. All rights reserved.
- 16. SUMMARY Summary Low interest rates pose significant challenges on all fronts for both variable and fixed annuities Profitability is becoming more dependent on policyholder behavior Enhancement of methods for measuring and monitoring experience is becoming critical for many Better financial modeling is required More granularity for policyholder behavior assumptions Projection of management actions (investments, hedging, credited rate setting) and their limits Accurate refresh of balance sheet to understand capital risk exposures Ability to refine attributions of actual results 16 © 2012 Towers Watson. All rights reserved.
- 17. SUMMARY Questions 17 © 2012 Towers Watson. All rights reserved.