For many years, Collins has been on the leading edge in delivering analytical services to crop insurers. Our analytical team, for example, provides insurers with ceding strategy analyses, designed to optimize fund designation efficiencies which can dramatically improve underwriting profitability and mitigate downside loss potential.

Collins can also aid insurers in the analysis and development of a wide variety of "indexable" agricultural risks; for example:

• Weather risks, such as rainfall and temperature;
• New insurance products, such as revenue protection on grains; and
• Multiple risk coverages, such as revenue protection on grains.

Collins agricultural reinsurance clients also benefit from our innovative proprietary crop peril modeling technologies, including:

Collins Stochastic 2-factor (S2f) model. This modeling procedure adjusts historical client performance for the current multiple peril crop insurance (MPCI) pricing and operating environment. It employs historical yield and price changes to recast MPCI performance for a projected book of business and ceding strategy, given the current Standard Reinsurance Agreement (SRA) and premium rates.

The S2f model analyzes yield and commodity-price related coverages. In the past, such analyses were "deterministic," looking only at prior experience. The S2f model, however, provides for a "probabilistic" analysis, allowing a comparison of past experience to the odds of an event occurring or recurring. It also enables an insurer to compare the profit aspects of agricultural insurance to other lines of business.

The S2f Model encompasses more than 20 crops at the state or Crop Reporting District (CRD) level and captures the impact of 90 percent of all total FCIC premiums (and 82 percent of all FCIC liabilities).

The Data Expansion Routine, a tool for expanding historical data sets. This tool is especially useful for crop insurers in analyzing excess-of-loss reinsurance contracts and in allocating capital among different business units.

The Collins Data Expansion Routine expands the variable relationships exhibited over a recent historical period to 1,000 years or more. The expanded data set of statistically-similar variables is then used to permit risk assessment of pure premiums and burn costs for any layer of an excess-of-loss treaty.

The Stratified Ceding Optimizer, employed by Collins to assist clients in managing their MPCI exposure under the SRA. Collins developed the tool to provide an analytical basis for the efficient allocation of gross MPCI policy risk across the seven available funds under the current SRA in each state. The model provides recast gross and net loss ratios by county and crop for each year and period analyzed.

Additional information on Collins' crop modeling services is available from Peter Griffin.