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Practical aspects of realistic valuations using a market consistent asset modelRichard Waller & Michel Abbink
Agenda
Regulatory background
The realistic balance sheet
Modelling approach
Modelling issues
Practical issues
Regulatory background
CP143 (July 2002)
Dear CEO letter (August 2002)
FSA progress report (October 2002)
Dear CEO letter (December 2002)
Tiner speech (February 2003)
Dear CEO letter (March 2003)
CP??? (July 2003)
How it all fits together
Realistic balanceSheets
InternationalAccountingStandards
Pillar oneCapital
requirements
InternalCapital
Assessment
Principles and Practices of Financial Management
How it all fits together
Admissibleassets
Realisticassets
Realisticassets
Pillar one basis(twin peaks approach)
Pillar two basis
Free Capital
RMM
Resilience Reserve
WP liabilitiesEU directive
Free capital
SCA
ICA
Realisticliability
Free capital
Market andcredit risk
capital
Realisticliability
Agenda
Regulatory background
The realistic balance sheet
Modelling approach
Modelling issues
Practical issues
The realistic balance sheet
Total realistic assets
- Non-profit statutory liabilities
- Non-profit RMM
Net with-profit assets
Base asset shares / reserves
+/- Misc surplus allocated to asset shares
+/- Planned enhancements to/retentions from asset shares
+/- Smoothing costs/benefits
+ Future guarantee costs
- Future guarantee charges
+/- Value of non-profit business
+/- Future surrender profits
+/- Other realistic liabilities/assets
+ Current liabilities
Net with-profit liabilities
The realistic balance sheet
Total realistic assets
- Non-profit statutory liabilities
- Non-profit RMM
Net with-profit assets
Base asset shares / reserves
+/- Misc surplus allocated to asset shares
+/- Planned enhancements to/retentions from asset shares
+/- Smoothing costs/benefits
+ Future guarantee costs
- Future guarantee charges
+/- Value of non-profit business
+/- Future surrender profits
+/- Other realistic liabilities/assets
+ Current liabilities
Net with-profit liabilities
The realistic balance sheet
Total realistic assets
- Non-profit statutory liabilities
- Non-profit RMM
Net with-profit assets
Base asset shares / reserves
+/- Misc surplus allocated to asset shares
+/- Planned enhancements to/retentions from asset shares
+/- Smoothing costs/benefits
+ Future guarantee costs
- Future guarantee charges
+/- Value of non-profit business
+/- Future surrender profits
+/- Other realistic liabilities/assets
+ Current liabilities
Net with-profit liabilities
The realistic balance sheet
Total realistic assets
- Non-profit statutory liabilities
- Non-profit RMM
Net with-profit assets
Base asset shares / reserves
+/- Misc surplus allocated to asset shares
+/- Planned enhancements to/retentions from asset shares
+/- Smoothing costs/benefits
+ Future guarantee costs
- Future guarantee charges
+/- Value of non-profit business
+/- Future surrender profits
+/- Other realistic liabilities/assets
+ Current liabilities
Net with-profit liabilities
The realistic balance sheet
Total realistic assets
- Non-profit statutory liabilities
- Non-profit RMM
Net with-profit assets
Base asset shares / reserves
+/- Misc surplus allocated to asset shares
+/- Planned enhancements to/retentions from asset shares
+/- Smoothing costs/benefits
+ Future guarantee costs
- Future guarantee charges
+/- Value of non-profit business
+/- Future surrender profits
+/- Other realistic liabilities/assets
+ Current liabilities
Net with-profit liabilities
Agenda
Regulatory background
The realistic balance sheet
Modelling approach
Modelling issues
Practical issues
Modelling approach
Aim:– Market consistent valuation of insurance contracts
including embedded guarantees and options
Approaches– Deterministic– Black Scholes– Stochastic projection– Stochastic valuation
Deterministic
Present value of projected cash flows
Guarantee cost emerging in the single scenario– no allowance for optionality
Implicit allowance via prudent margins
Currently common (EV approach)
Not market consistent
Black Scholes
Deterministic “risk neutral” projection(s) of payouts and asset shares
Identify replicating portfolio of options
Black Scholes valuation of options
Depending on approach difficult or impossible to allow for smoothing, path-dependency or dynamic nature of bonuses, asset allocation & policyholder behaviour
Stochastic projections
Stochastic projection of guarantee / smoothing costs
Scenarios based on “real world” distribution
Take xth percentile
Discount rate
Not market consistent
Stochastic valuation
Stochastic projection of guarantee / smoothing costs
Scenarios based on market consistent models
– risk neutral or deflator
(Weighted) mean
Most complex and most accurate,
..but still subjective (incomplete markets, decision rules)
Comparison of results
0
100
200
300
400
500
With Profits Bond
Guarantee cost
Agenda
Regulatory background
The realistic balance sheet
Modelling approach
Modelling issues
Practical issues
Market consistent modelling
Theoretical issues
– What is risk free?– Availability market data– Basis risk
Stochastic asset models
– Fit for purpose– Deflator or risk neutral– Asset classes, economies and interaction– Richness of calibration structure– Statistical features– Convergence
Market consistent modelling
Practical issues– number of simulations– projection period– projection steps– ease of use
Audit– relevance calibration to the risk that needs pricing – Check if prices are replicated from the output– Statistical features
Stochastic Accreditation Working party
Liability modelling
Asset share methodology
Bonus philosophy
Investment strategy
Surrender value policy
Policyholder behaviour
Asset share methodology
What is the methodology?
– Is it well documented and fit for this purpose?– Does it cover all classes of business?– Needs to be consistent with disclosures
What about charges for guarantees?
– Is this aspect well documented?– Does it comply with treating customers fairly?– When should charges be levied?
Asset share methodology
Unsmoothed and smoothed asset shares?
– Doubles up the projection code / calculations– Is the smoothing formula clear?– What to base payouts on?
Are current asset shares available?
– Is the historic data there to accumulate them?
Extreme scenarios
– Is the methodology robust enough?
Bonus philosophy
Future reversionary bonus rates
– Based on a reference such as gilt yields?– Maximum and minimum amounts?– Dependent on fund solvency level?– Dependent on existing level of guarantees?– Limits on size/frequency of changes?– How many different rates to model?– Needs to be consistent with disclosures
Bonus philosophy
Future terminal bonus rates
– What percentage of asset share targeted?– How to smooth payouts over time?– How to smooth across policy size?– Dependent on fund solvency level?– Limits on frequency of changes?– Needs to be consistent with disclosures?– Can’t model competitive influences
Investment strategy
What asset mix?
– Do long term guidelines really exist?– What about derivative positions?– Treatment of net cashflows?– Duration matching of fixed interest?– Dependent on fund solvency level?– What about manager bias/performance?– Needs to be consistent with disclosures
Surrender value policy
Current surrender value bases
– Can they be modelled accurately?– Should future changes be modelled?– How robust in extremes?
MVR policy
– Can it be modelled accurately?– It may still be evolving– Needs to be consistent with disclosures
Policyholder behaviour
Take up of options
– What to assume when guarantees are in-the-money
– What to assume in preceding years– Do policyholders know value of guarantees– Surrender activity often not financially driven– Can’t model lifestyle influences
Agenda
Regulatory background
The realistic balance sheet
Modelling approach
Modelling issues
Practical issues
Practical issues
Model point construction
– Focus attention where costs are likely– Goodness of fit to actual policy data– Impacts on run times
Run times
– Can be very long!– Conflicts with accuracy and complexity– Efficient code and systems usage important
Practical issues
Checking
– How do you check stochastic results?– Investigate deterministic scenarios too?
Model maintenance
– Need strong control environment– Separate RBS and other ALM models?
Guidance
– Is more guidance necessary?
Contact details
richard.waller@eu.watsonwyatt.com
michel.abbink@eu.watsonwyatt.com
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