Asset Allocation



Investment assets dominate insurance company balance sheets and investment return is typically a major portion of an insurer's total return. Investments provide new capital to support business growth, impact an insurer's premium rate competitiveness and supply liquidity to meet operating needs. All of this is done in a highly constrained environment that attempts to balance the sometimes conflicting needs of tax collectors, state insurance regulators and independent rating agencies. Investment strategy, therefore, must be an integral part of an insurer's business strategy.

Peer Analytics' approach to asset allocation, which is now often referred to as Dynamic Financial Analysis, is to simulate the impact of a range of possible asset mixes in the context of the company's financial statements. We model the operational cash flow, income statement and balance sheet for each of several thousand return draws. This allows us to understand and communicate the tradeoff among the various asset mixes in terms of the potential distribution of the relevant financial measures of value (e.g., Surplus, Net Income after-tax, ROI, etc.).

The principals in Peer Analytics have been involved in assisting clients in the asset allocation process for over twenty years. Together we have conducted over 150 asset/liability studies and developed numerous asset allocation modeling tools for virtually every type of investment organization. Michael Kantor and Dave Newsom developed one of the first stochastic asset allocation models for property casualty insurers in 1989.

Effective benchmarking provides sufficient information to determine when corrective action is necessary.

Indexes are valuable components of the benchmarking process, but by themselves are not sufficient. Simple index comparisons lack the context required to draw meaningful conclusions.

Because indexes provide only a single comparative data point for each time period, it takes decades* to determine with any statistical meaning whether or not an investment manager has positive or negative skill. So by the time you have enough data to reach a conclusion, it's far too late.