Dynamic Financial Analysis: Stephen W. Philbrick, FCAS Swiss Re Investors Dynamic Financial Analysis: Taxonomy Revisited Stephen W. Philbrick, FCAS Swiss Re’s Value Proposition This presentation will demonstrate the customer benefit of reinsurance and explain the underlying economic rationale for reinsurance. Copyright Swiss Re Investors

Taxonomy Design Designing a Taxonomy Similar to Designing a Class Plan Identify Distinguishing Characteristics Objective Measurable Swiss Re Investors

DFA Model Structure Initial Conditions Scenario Generator Financial Calculator Results Swiss Re Investors

Profitability Targets…Witcraft Asset Accounting Economic Scenario Financial Statements Report Generator Liability Accounting Liability Scenario Loss Expense Other Swiss Re Investors

Applying a DFA Model…Correnti, Sonlin, Isaac FIRMTM Process Step 1 Evaluation and Simulation of Economy(s) and Capital Market(s) Step 2 Evaluation and Simulation of Balance Sheet Items Business mix Reinsurance strategy Mergers, Acquisitions and Divestitures Investment Strategy Derivatives Capital Allocation/Structure Step 3 Risk/Reward Optimization (Efficient Frontier) Step 4 Analysis of Results: - Decomposition of Risk - Downside Analysis - Solvency Step 5 Sensitivity Testing Strategic Business Decisions Swiss Re Investors

DFA Model Structure Initial Conditions Scenario Generator Financial Calculator Optimizer Results Swiss Re Investors

Dynamic Financial Analysis Initial Conditions History Premium levels Inflation rates, etc. Current Balance sheet Yield curves, etc. Represents estimates of the model assumptions at the start date of the model Swiss Re Investors

DFA Scenario Generator This is where taxonomy is most relevant We will return here after completing discussion of model structure Swiss Re Investors

Financial Calculator - Granularity Policy detail Premium levels Inflation rates, etc. Loss generation Pure premium Exposure/frequency/severity Assets Classes of assets Individual assets Swiss Re Investors

Financial Calculator - Accounting Basis GAAP Statutory Both Economic Swiss Re Investors

Imbedded in Market? Strategy evaluation - contingent decisions capability Model can be stand-alone with implied market interactions Model can formally generate competitors who can affect marketplace Example - corporate financial “games” Swiss Re Investors

Embedded in Market - Status Ongoing work - not much available Hard to do Requires modeling dozens of companies And their interactions Without necessary information Can’t punt on market cycle Swiss Re Investors

Results Financial results for each scenario Objective function to be optimized Ending surplus Probability of insolvency Cost of insolvency (expected deficit) Variance of earnings, surplus... Determination of “drivers” of results Swiss Re Investors

Metrics Swiss Re Investors

Categories of Metrics Simple Stat (mean-based) ROC ROMAC Cost of Cat Simple Stat (non mean-based) Ruin VAR Probability of Missing Goal Swiss Re Investors

Categories of Metrics (Cont.) Multiple Valued Stat Percentiles of: Final Surplus Interim Surplus Net Loss ratio Combined ratio Swiss Re Investors

Categories of Metrics (Cont.) Single Value Incorporating Multiple Points EPD RAROC Utility Two Dimensions of Variates Efficient Frontier Swiss Re Investors

ALM Efficient Frontier Same Risk, Higher Reward Financial Reward Same Reward, Lower Risk Current Strategy Financial Risk Swiss Re Investors

Efficient Frontier The “efficient frontier” is the set of optimal strategies that maximizes reward for each level of risk Efficient Frontier Financial Reward Financial Risk Swiss Re Investors

Scenario Generator Single most important part of a “dynamic” model Various categories regarding approach to: General economic conditions Assets Liabilities Swiss Re Investors

Scenario Generator - Categories Deterministic Simulation Unstructured Structured Swiss Re Investors

Scenario Generator - Deterministic Specify characteristics for each scenario of interest Examples: Recession scenario Acquisition scenario Growth scenario Catastrophe scenario Swiss Re Investors

Unstructured Simulation Specify statistical distribution for each variable Monte Carlo simulation to randomly generate scenarios Output can be automatically summarized as distribution Swiss Re Investors

Structured Simulation Econometric relationships Autoregressive ARIMA Formal relationships with correlations Generated scenarios are internally consistent and plausible Output can be automatically summarized as distribution Swiss Re Investors

Purpose Valuation Strategy analysis Exploration of dynamics Solvency analysis Swiss Re Investors

Conclusions Taxonomy Model Holding up well Significant Progress is Occurring in DFA research Harder Than Some of us Thought Correlation Payment Variability Reserving Swiss Re Investors

Still To-Do Correlation (Parameters) Modeling Some Assets Muni’s Foreign Stocks Real estate Modeling Underwriting Cycle Parameterizing EVERYTHING Swiss Re Investors