Enterprise Risk Management Challenges for Insurers Donald Mango, FCAS, MAAA Director of Research and Development, GE ERC

My Role at GE ERC GE ERC >Worldwide provide of Reinsurance in P&C and Life and Health –2003 NWP ~US$9.8B >Also major US primary insurance carrier –2003 NWP ~US$2.1B >Subsidiary of General Electric –Unwavering parental commitment to risk management Director of R&D >Risk and Pricing Models and Tools –Methods, thought process, software tools >Capacity Management –Techniques, risk modeling >Intellectual Property and thought leadership >Co-report to Chief Actuary and Chief Risk & Underwriting Officer

Four Major Issues 1.Control versus Coordination 2.Point-of-Sale Risk Management 3.Product Cost Forecasts 4.Time Dimension

Four Major Issues 1.Control versus Coordination 2.Point-of-Sale Risk Management 3.Product Cost Forecasts 4.Time Dimension

#1: Control versus Coordination Control >Checks and balances are part of sound corporate governance >Inherent conflict of interest in the underwriting role (sales versus profit) Coordination >Too many controls lead to paralysis >More eyes may lead to different but not necessarily better decisions >Local market presence is undermined by excessive referrals

Mandate the decision processes >Key decision variable suite, information requirements, pricing models, etc. Distribute decision making authority >Acceptable concession to responsiveness, empowerment >Staff the positions appropriately, don’t legislate around weaknesses Audit with Authority >Trust but verify >No self-marked portfolios >Accountability for violations #1: Control versus Coordination Proposal

Four Major Issues 1.Control versus Coordination 2.Point-of-Sale Risk Management 3.Product Cost Forecasts 4.Time Dimension

#2: Point-of-Sale Risk Management Much of the risk management activity is reactive and forensic >Record of executed transactions We end up with after-the- fact, lagging indicators Portfolio information takes so long to compile that it often cannot inform real- time decisions Not well matched to the inherent structural risks of insurers >Commitment to make future payments >Leveraged pool of contingent claims >History of failed companies over- committing

Risk Budgets = linear, additive constraints that reflect product risk characteristics, portfolio situation >Complexity must be distilled out  key challenge facing the quants and actuaries For each opportunity under consideration, give front-line people: the marginal benefit (return) and marginal budget usage, along with cumulative usage-to-date and departmental target Competent people can “improve” a portfolio under these conditions #2: Point-of-Sale Risk Management Proposal

Four Major Issues 1.Control versus Coordination 2.Point-of-Sale Risk Management 3.Product Cost Forecasts 4.Time Dimension

#3: Product Cost Forecasts Accepted industry practice for loss ratio planning involves using one’s own history, modified for trends These are somewhat incestuous, internally-based forecasts >Driving by looking in the rear view mirror Fails to anticipate or even react to changes Economic Invisible Hands move money in and out of various financial products Periodic product cost shocks, followed by gradual restoration of balance May be enough pattern and predictability to eliminate a material portion of the systematic risk

Independent forecast models for product costs and price levels >Need to have cyclical components (e.g., mean reversion) >Movements of the invisible hands >Factoring in major economic drivers Would also be greatly facilitated by public domain synthetic indices, along with tradable options and futures on those indices Would allow us to begin spreading systematic risk across a wide base #3: Product Cost Forecasts Proposal

Four Major Issues 1.Control versus Coordination 2.Point-of-Sale Risk Management 3.Product Cost Forecasts 4.Time Dimension

Project evaluation models are still largely static Our capital usage is dynamic and flowing Capital commitment to an insurance entity is ongoing Yet, paradoxically, the capital is not meant to be “used” Capital allocation and ROE models do factor in one aspect of time – discounting But what about the dynamics and flow? Can we reflect the time dimension in our decision processes? #4: Time Dimension

Capital Allocation may be the wrong asset usage analogue >Allocation can mean either earmarking or transfer >Typical models are based on a capital usage model of transfer to the segment, which then returns it over time This may have theoretical appeal, by facilitating parallels to “project evaluation” from corporate finance But it is unrealistic and unnecessary, and reinforces the static mindset #4: Time Dimension Capital Usage

An alternative asset usage analogue is rental or occupation “THE CAPITAL HOTEL™” Underwriting of business occupies space (capacity) for a length of time >Reserves require supporting capital Occupation of that space excludes it from other uses It should therefore pay an opportunity cost #4: Time Dimension The Capital Hotel

Simple change that clarifies the time dimension Focus on capital as a shared resource simultaneously exposed to depletion by multiple segments Puts the past squarely in the present >Business that hangs around on the books uses up capacity Focus moves to how long business occupies how much capacity (space) >Charged for usage per unit of time #4: Time Dimension The Capital Hotel

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