Competitive Insurance Pricing

A nonprofit insurer of municipalities and townships was under heavy attack by a commercial insurer offering very low prices for insurance. In five years the competitor had gone from about 10% market share in property & casualty insurance to almost 70% in the nonprofit insurer’s region. Over this period, all other competitors in the region exited. Making the situation more alarming, the low-priced competitor was starting to offer coverage in the workers’ compensation area.

For two years the nonprofit insurer had lowered prices in an attempt to retard loss of market share, but the prices had become so low that reserves held in anticipation of future losses were dwindling. Nevertheless, another round of price cuts was under consideration when Ventana was asked to assess the situation and make strategy recommendations. Working with the client over a nine-week period, Ventana constructed a highly aggregated model of the nonprofit insurer and the low-priced competitor. While the competitor model was somewhat speculative, competitive intelligence was sufficient to bound the competitive uncertainties much like future insurance losses were bounded.

Several important insights emerged from simulations of the models. The first was that the low-priced competitor would be unable to sustain his low-price strategy over the long run. Indeed, the only reasons that the competitor could use the strategy as long as it had was by maintaining rapid growth and an immature book of business. (In the insurance business, customers pay premiums up front, and the insurance company pays for losses that are realized later. And so, rapid growth can temporarily hide poor underwriting practices.) The rapid growth was ending as higher-priced competitors exited the market, and historical losses were beginning to catch up with the competitor. Moreover, the competitor lacked the substantial investment reserves of the nonprofit insurer, and his costs were higher than the nonprofit insurer. Consequently, Ventana recommended that its client maintain its historical pricing practices and not jeopardize the long-term stability of the insurance market by depleting its investment reserves in a senseless market share fight.

Ventana predictions eventually proved very accurate. Indeed, our client reported a few years later that the competitor exited the market very close to our predicted date of insolvency. Benefits of the modeling work also emerged immediately. For the first time, the client CEO felt he had a comprehensive understanding of his competitive environment. The company’s board of directors was particularly pleased because the perspective afforded by the modeling was much deeper than normal. Several board members stated that they felt they were now in a better position to advise the CEO on strategy and insurance policy.

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