Breakthroughs in Analytics Are Transforming the Insurance Business

By Frank J. Coyne

In just a decade and a half, approximately a third of the insurers serving the United States vanished as escalating competition ate into top-line revenue growth and bottom-line profitability. But it isn't just the intensity of competition that's changing. The nature of competition is changing too.

Spurred by intensifying competition, breakthroughs in analytics are transforming dynamics in insurance markets. Advances in predictive modeling and other analytical techniques are enabling leading insurers of all sizes to target their marketing, under­writing, and pricing as never before.

Advances in analytics are also transforming loss settlement. Smart insurers are using such innovations as data mining, pattern-recognition technology, data-visualization tools, and scoring both to detect insurance fraud and to expedite payment of meritorious claims. Claim fraud adds approximately 10 percent to loss and loss adjustment expenses. Advanced analytics can yield significant savings that ultimately provide a competitive advantage.

Using predictive models to price, underwrite, and market personal auto insurance is fast becoming a competitive necessity, if it ­hasn't already. Today, sophisticated insurers are using models based on credit information and territory or ZIP-code-level data. Next-generation models have already been developed by ISO. Visionary insurers will soon deploy these powerful models based on hundreds and even thousands of variables for individual addresses.

Predictive modeling and other advanced analytics are also applicable to Main Street commercial lines business. With premiums for businessowners policies averaging approximately $1,500, spending significant sums on painstaking underwriting is out of the question. But with the right technology, it takes only seconds to enter a few facts from a policy application and get a score that indicates whether the risk should be underwritten.

Yet even the most sophisticated modeling won't yield correct underwriting and pricing decisions if the information on applications is wrong. In 2005, U.S. personal auto insurers lost $16 billion in premiums because of poor data. Predictive modeling and intelligent database matching now enable insurers to spot flawed information and stop premium leakage.

However, a chasm is growing between insurers using state-of-the-art analytics and those who aren't — the “haves” and the “have-nots.” Increasingly, the haves will be able to write business at the margins they target. The have-nots will fall victim to adverse selection as more sophisticated insurers target the risks apt to prove profitable. And the bar will rise continually as competition drives weaker players from the field. Today's haves are at risk of becoming tomorrow's have-nots.

Sophisticated insurers able to harness large volumes of high-quality data to drive decisioning all along the value creation chain can look forward to a long and prosperous future. But insurers unable to keep up in the intellectual and technological arms race face a grim prognosis.

Surviving and thriving will require devotion to the core fundamentals of the business — cost-based pricing, solid under­writing, strong loss adjudication, and sound risk management. The challenge is to keep up as advances in analytics change what constitutes superior execution against the fundamentals.

Frank J. Coyne is Chairman, President and Chief
Executive Officer of ISO.