Currently, three fast-moving developments are fostering opportunities for predictive analytics to finally make a big play in the world of claims operations. Following the Great Recession and ongoing economic strain, insurers are adapting their business models to a "new normal" era of intense market share competition, rising loss costs, and a complex regulatory environment.

Optimization As The Ultimate Goal
So will predictive analytics be the next "killer app" for claims handling? Insurers have already integrated a range of workflow and automation tools. Because these solutions have paid off by cultivating improved performance and a streamlined claims handling process, insurers are now looking for higher-order optimization opportunities to increase both internal efficiencies and customer satisfaction.

Optimization means minimizing the cost of adjudicating claims while maximizing all stakeholders' satisfaction with the resolution of each claim. Most insurers can identify a number of areas for improvement in this domain, including:

1. Faster, simpler claims resolution.
2. Fraud reduction.
3. Strategic, data-driven insights.
4. Improved decision making.

A Proactive Strategy
Perhaps the greatest opportunity for predictive analytics to positively impact profit lies in its capacity to assist organizations in moving from a reactive to a proactive stance in identifying and managing key risk factors without disrupting a whole book of business. Predictive scoring models, for example, can provide a forward-looking view of frequency, severity, loss adjustment expense (LAE) recovery opportunities, and claims duration. Risk management is all about applying a proactive strategy to pricing and rates. By evaluating past policyholders' characteristics against their outcomes, the underwriter can then predict the performance or behavior of a new policyholder. The claims team, on the other hand, is just beginning to embrace the idea of proactive thinking. However, the potential gains are quite significant for claims organizations, including the ability to anticipate of a claim's severity, the likelihood it will require litigation, the most favorable negotiated settlement for the claim, and perhaps most importantly, a better view of the nature and extent of possible fraud. Predictive analytics is the key driving force behind a successful, proactive claims strategy. Integrating this technique into the claims process can improve operating efficiencies, increase strategic insight, and help reduce many kinds of risk. In a typical situation, a numeric score representing risk level is seamlessly incorporated into a bill review or claims handling system to drive business rules associated with routing and resource assignment. A proactive analytics strategy can also impact automation as well as the adjuster workforce. Insurers are experiencing a crunch as a significant number of adjusters near retirement. Recruiting and training are a critical part of the solution; however, not all insurers are financially or logistically able to mount the kind of staffing initiative required to keep up with demand.