1. Annuity Capital Risk Management
Actuaries’ Clubs of Boston and Hartford & Springfield
Kendrick Lombardo FSA, MAAA
November 15, 2012
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2. AGENDA
Agenda
 Economic environment
 FIA capital risk management issues
 VA capital risk management issues
 Summary
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3. Economic Environment
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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
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5. FIA Capital Risk Management
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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
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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
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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
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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
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10. VA Capital Risk Management
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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
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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
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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
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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
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15. Summary
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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
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17. SUMMARY
Questions
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