Filed Under:Claims, Investigative & Forensics

Proactive Analytics Strategies

Standardizing Claims Handling, Fraud Mitigation

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.

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.

Many claims organizations are looking to fill this need with improved automation technologies. While it is a pipe dream to expect that the claims process will ever be fully automated, predictive technologies can support adjusters by helping to standardize the handling of high-volume, repeated decisions and by providing an additional, unique perspective on complex, multi-variable claim situations.

Optimizing Workflow
Strong organizations are able to adapt quickly to change. Regulatory shifts, caseload severity, and customer service demands are three types of change that impact the claim organization’s effectiveness. Using optimization technology, insurers can model and test the possible impact of workflow and organizational changes before initiating them.

For example, it is possible to estimate the impact of switching from a generalist to specialist adjuster staffing model. Predictive analytics can help answer questions such as, “Will the increased skill level offset the additional staff and training costs? By how much?”

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