As the personal lines insurance market softens, carriers are turning to predictive analytics to maintain their underwriting discipline.
Mark Gorman cant see into the future, but he believes underwriters working in personal lines will be attempting to predict what the future holds for policyholders. As carriers resume the battle between soft and hard markets, the soft side currently has the upper hand.
The soft market raises issues within insurance carriers regarding discipline and what happens to underwriting discipline in a soft market as [carriers] are pressured to be more of a market follower relative to price to underwriting, says Gorman, strategic research adviser with TowerGroup. Gorman co-authored a recent TowerGroup report with Deborah Smallwood titled Underwriting Effici-ency and Effectiveness Study: State of the Market and Best Practices.
Carriers are adjusting their evaluations of the underwriting process in the current soft market, Gorman believes. In our discussions with senior management, we saw a strong desire on its part not to do a traditional response to soft-market pressures, he says. It didnt want to fall back on the market-following behaviors that had taken place in previous soft markets.
One issue for insurers will involve an attempt to decrease the complexity many carriers are finding in their underwriting systems in order to get a better handle on underwriting rules and procedures, Gorman notes. A second issue, which he contends insurers are reluctant to discuss publicly, will involve a focus on predictive analytics. They are all taking a strong look at predictive analytics and the ability to segment the business better and provide themselves the opportunity to re-spond to a soft market without necessarily reducing [rates] on a wholesale basis for all of their lines of business, he says.
Predictive analytics can be a confusing area, according to Gorman, because it involves terms such as data mining and business intelligence. Data mining and predictive analytics come under the general term business intelligence, says Gorman. An activity such as data mining is focused on looking at historic data and what has happened in the past. If we look at predictive analytics from an underwriting standpoint, the questions are: What were my loss ratio propensities? What business did we write? How did we price the business we wrote? And what loss experience did we have on that business?
Predictive analytics focuses on segmentation and profiling of the business, explains Gorman. Thats extremely valuable for carriers, he says. We also are seeing a forward look. Predictive analytics is attempting to take the data that is available at the point of decision and predict what the loss ratio will be.
Additionally, the hard and soft markets bring out the differences between retention risk and leakage. As the market hardens, the risk doesnt change, but the price the company charges moves up, says Gorman. When you do that, you remove the leakage, but you also increase the retention risk.
As a result, a competitor will decide to capture the retention risks by lowering rates and going after those customers. [The competitors] lower their rates, and everybody has to follow them, says Gorman. As the rates fall, you increase the leakage and decrease the retention risk. What weve seen historically is an ebb and flow of where the leakage is increasedthats represented by years where weve seen increasing combined ratios and increasing profitability from an underwriting standpoint. On those years where we see the retention risk increase and leakage decrease we see harder markets and more profitability.
This ebb and flow between the hard and soft markets has been going on for the last 25 years, Gorman adds. Carriers need to reduce the total area of retention risk and the total area of leakage, he says. Were seeing a reduction in the complexity of systems and a focus on straight-through processing in order to drive that consistency and improve the responsiveness to the consumer and to the agents.
ROBERT REGIS HYLE