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Snapshot 1: with high levels of risk aversion in the potential insurance pool, adverse selection is not a serious problem

Snapshot 2: with low levels of risk aversion in a pool that is heterogeneous with respect to risk, adverse selection can be a serious problem, even with binary classification systems

Snapshot 3: the locator dividing the low-risk pool from the high-risk pool has been moved so that everyone is now in the low-risk pool; the result is high levels of adverse selection

Snapshot 4: the creation of a classification system decreases adverse selection by permitting a number of low-risk insureds to purchase insurance; premiums for those in the high-risk pool are, however, slightly higher than they would have been if no classification system had been employed

Risk aversion is not measured in this Demonstration using Arrow–Pratt coefficients. Rather, for simplicity and to accelerate computation of optimal behavior, risk aversion is equal to the value such that the insured will purchase insurance if and only if .