Introduction To Ratemaking And Loss Reserving For Property And Casualty Insurance

This is arguably the single most critical function in an insurance company. If reserves are inadequate (too low), the company may become insolvent when claims are finally paid. If reserves are redundant (too high), the company hides profits and unnecessarily ties up capital.

Uses Bayesian statistics to assign credibility to different parts of the triangle. More sophisticated than CL but requires robust software.

The actuary attempts to determine the relativities—how much more or less risky is Group A compared to the Base Group? For example, if young drivers have 50% more accidents than middle-aged drivers, their rate relativity would be 1.5. This is arguably the single most critical function

: Adjusts current rates based on the ratio of actual to target loss ratios.

However, because losses are unknown at the time of pricing, actuaries work with the concept of the . The goal is to set a premium such that: $$Premium \times (1 - Expense Ratio) = Expected Losses$$ Uses Bayesian statistics to assign credibility to different

This blends historical data with an a priori expected loss ratio (often derived from ratemaking).

This prevents the common phenomenon where ratemaking assumes a 5% loss trend while reserving shows an 8% trend—a contradiction that destroys capital adequacy. For example, if young drivers have 50% more

While ratemaking looks forward, loss reserving looks backward at claims that have already occurred but are not yet fully paid. An insurance company’s balance sheet is dominated by these liabilities.

: Rates must be high enough to cover losses and keep the insurer solvent. Not Excessive