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The Value Proposition of DFA. Basic Applications for Real World Decision Making Bob Mueller ACAS Executive Vice President Middlesex Mutual / Country Companies Group. Perspectives . CFO, Chief Actuary, Corporate Strategist Small to Mid - sized Company . Illustrations .
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The Value Proposition of DFA Basic Applications for Real World Decision Making Bob Mueller ACAS Executive Vice President Middlesex Mutual / Country Companies Group
Perspectives ... • CFO, Chief Actuary, Corporate Strategist • Small to Mid - sized Company
Illustrations ... 1) Asset Allocation Decision 2) Strategic Partnering Decision
Anatomy of an Asset Allocation Decision • Year: 1988
Anatomy of an Asset Allocation Decision • Historic Financial Profile: Low leverage, high equity investment
Anatomy of an Asset Allocation Decision • Emerging Issues • Premium growth 15 - 25% per year • Significant new investment in Real Estate • Pressure from A.M.Best
Anatomy of an Asset Allocation Decision Board Finance Committee: • University president with investment background • Regional bank president • Two president/owners of boutique investment management firms • CFO of a national investment management firm • Key Decision Makers
Approach • Direct, intuitive • Focus on concept and principal • Quick
“Back of the Napkin” Model Total Return = Investment + Underwriting Return T / S = I/S + U/S = I/A x A/S + U/P x P/S = I/A x (1 + L/PxP/S) + U/P x P/S S= Surplus, A= Assets, L=Liabilities, P=premium
“Back of the Napkin” Model Total Return = Investment + Underwriting Return T / S = I/S + U/S = I/A x A/S + U/P x P/S = I/A x (1 + L/PxP/S) + U/P x P/S “constant” leverage factors
“Back of the Napkin” Model Total Return = Investment + Underwriting Return T / S = I/S + U/S = I/A x A/S + U/P x P/S = I/A x (1 + L/PxP/S) + U/P x P/S random variables
Model Results 100% stocks 50% stocks No stocks
Business Conclusions • Risks too high , returns too low at any level of equities • Need to focus on core business issues rather than asset allocation
In Summary ... • Advantages • not a “black box” approach • clear linkage of investment and underwriting • gets management acquainted with DFA • Disadvantages • one year projection • not good for “fine tuning” asset allocation or underwriting strategy
Strategic Partnering Decision • Year: 1996
Strategic Partnering Decision • Business Situation: • $80MM PL in Connecticut and Maine • Good auto results, volatile and unprofitable property results • 100 year return time wind loss = 1.5 x Surplus • Catastrophe insurance ROL approaching 4% • Depressed returns from large real estate investment • Ratings pressure
Alternatives • Open Market Reinsurance Product • Contingent Surplus notes etc. • Demutualization and Sale • Merger • Reinsurance Pooling Arrangement
Pooling Arrangement • All premiums, losses and expenses pooled with member companies • Retrospective reinsurance treatment of prior loss reserves • Pool results redistributed based on “economic value” surplus • Companies maintain separate surplus and investments
DFA Modeling Approach • Focus on the underwriting side of the model • underwriting volatility changes • investment projections left deterministic • State conclusions in terms of relative rather than absolute returns • eliminate need for economic scenarios etc. • Custom built model to accommodate pooling transaction accounting
Underwriting model • Accident year loss ratios by line • decomposed historical to cycle + randomness • No reserve uncertainties • Separate catastrophe loss modeling • Distributions from IRAS model before and after pooling • Catastrophe reinsurance modeling
Model Results • Parameter Assumption sets • Forecast (expected )underwriting results • Better than past average results • $100MM catastrophe loss • Model outputs • Probability that surplus in 5 years would be X% better under pooling than stand-alone
DFA Benefits • Demonstrated significant risk reduction benefit to transaction • Helped achieve regulatory approval • Kept all “stakeholders” focused on the real issues
Summary • Avoid the “model in search of a problem” • Avoid “black box” modeling • Understand the people you’re influencing • Focus on relative performance