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Predictive Analytics Helping Insurers Weather Tough Economic Times

The business landscape for insurance companies continues to change with pressures from the volatile economic conditions.

By Jim Haley | Updated on July 06, 2010
The business landscape for insurance companies continues to change with pressures from the volatile economic conditions. While the business questions have remained the same, they are no longer as easy to answer as in the past. How do we maintain market share, grow our business, keep costs down and generate a profit? How do we best position the organization to take advantage of a harder market when economic conditions improve?

Finding the right answers to these questions is becoming critical for most insurers, resulting in insurers searching for new tools and strategies. One tool garnering a lot of attention and gaining acceptance in the marketplace today is predictive analytics. Used effectively, predictive analytics is able to assist insurers in gaining and maintaining a competitive edge–a differentiator that is becoming increasingly difficult to achieve in today’s market.

In the earliest stages of adoption, predictive analytics was predominantly used in claims within the commercial property and casualty space. Today, it is quite common to see insurers use predictive analytics to support claims reserving issues as well as to identify fraudulent activities within active claims. Much of the impetus for this predictive analytics adoption has been due to the continual rise of health care costs. Rising claim costs, coupled with declining investment income and an economic meltdown, has put tremendous pressure on insurers to secure operating profits from core business activities.

Encouraged by the early success in claims, more insurers are now turning to predictive analytics to support decision making focused directly at underwriting disciplines in an effort to generate a fair return from the business written.

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