practical aspects of realistic valuations using a market consistent asset model richard waller &...

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