Price optimization
A practice that adjusts the premium to each customer's price sensitivity rather than to risk alone, to maximize margin or retention, which several regulators have banned or restricted on fairness grounds.
Classic actuarial pricing sets a premium from the expected cost of the risk, plus expenses and margin. Price optimization adds a second dimension: demand elasticity, that is, the probability that a customer accepts, renews or leaves depending on the price offered. An elasticity model, built on the history of quotes and renewals, then makes it possible to choose, for each customer, the premium that maximizes a commercial objective, margin, volume or retention, under constraints. Two customers with identical risk can thus pay different premiums because one is less likely to shop around or leave. The practice ran into a fairness objection: it makes loyal, older or less competition-savvy customers pay more, for reasons unrelated to their risk. Several US states have banned or restricted it since 2014, and the United Kingdom prohibited in 2022 charging a renewing customer more than a new customer for the same risk. The boundary remains debated: adjusting price to the market is legitimate, discriminating on the customer's inertia much less so.
Two home policyholders with the same risk profile have a technical premium of 400 euros. The elasticity model estimates that the first, a customer for twelve years, has a 95 percent chance of renewing even at 480 euros, and the second, who joined last year, only 60 percent at that price. Offering 480 euros to the first and 410 to the second maximizes margin, and that is exactly what the 2022 UK rule prohibits.
Follow the research
One letter a week. First, the week's underwriting note, when one is published: a dated, argued decision, signed by Paul Bernardski. Then what the observatory published on cyber risk, political risk and insurance. No account, no tracking.
No spam, one-click unsubscribe, no data ever sold.