Big Data no small feat for carriers of all sizes.
Global professional services firm Towers Watson just released their 4th annual P&C Insurance Predictive Modeling Survey that interviewed 63 North American P&C insurers evenly divided among small, midsize and large carriers.
P&C insurers acknowledged that the capture and transformation of data into useful information has turned into a critical differentiator of performance within the P&C insurance marketplace.
The Towers Watson Predictive Modeling Survey illustrates the importance of predictive modeling to insurers’ business. Personal lines carriers nearly unanimously (98%) said predictive modeling is either essential, or very important, to their business and 80% of small to mid-market commercial lines carriers agreed.
55% of large commercial accounts and specialty lines carriers indicated that predictive modeling is essential or very important to their business.
Desire to improve profitability
The desire to improve profitability emerged as the leading reason why P&C carriers use predictive models, with 90% of U.S. participants citing a desire to improve bottom-line performance as the primary reason, followed by competitive pressure (75%).
P&C insurers diverge on ways they use predictive modeling for their business. Personal lines carriers are more likely to use models for automated renewal decisions, fraud detection, and for pricing. While commercial lines carriers use it more to triage claims or to evaluate claims for litigation potential.
Leveraging Big Data and predictive analytics, Enservio software is used to improve the accuracy of claim settlements for policyholders and carriers. More accurate claim estimations mean faster settlements. Insurance companies use Enservio to service claims, to help in paying claims, and to price policies based on past claims data, demographics, geography, social trends and other data. Enservio handles about $3 billion in property casualty claims annually.
Says Enservio founder and President Jim Fini, “A big risk to predictive modeling and Big Data is the will of carriers to take action on the results. Often the modeling results suggest changes that are politically difficult.”
Most carriers have improved their bottom-line profitability through predictive model implementation.
Midsize and large carriers reported significantly more favorable bottom-line impacts from predictive modeling, particularly in the areas of loss ratio improvement and profitability.
For more information on this Survey please visit http://www.towerswatson.com/press/8977.