Predictive analytics in claims

Think back to your first day in claims, and then think about what you know today. The difference is staggering, right? Predictive analytics adds exponentially more knowledge to the mix. It leverages the collective experiences of individual claims professionals, entire claims departments and even the entire industry. But that's not all it can do. Here are a few ways it helps everyone, from an individual adjuster to an entire insurance firm:

• More efficiently dole out claims assignments

You may not know it, but predictive analytics is likely at work in your claims department right now—helping to assign claims to the right adjuster at the right time, based on your company's vast amount of data. Within this model, the more-experienced adjuster is given the complex, potentially high-cost claims, while the less-experienced adjuster is given smaller claims. While it may not seem like rocket science, costs aren't always obvious when claims are first reported. For example, what may seem like a simple back strain can result in multiple surgeries and a large settlement. Predictive analytics can sniff out those claims.

• Improve processes

Historical data provides us with insight into how customers want to be contacted, the best options for repairs and much more. This data also helps insurers work with customers to find the appropriate treatment path for injuries, helping the customer get the best, cost-effective care. Attention to customers' individual needs is improved and retention grows. Predictive analytics can also provide a more timely and accurate idea of the ultimate cost of a claim. This financial information is important to both customers and insurers.

• Grow relationships

On a personal level, predictive analytics can help adjusters improve relationships with customers during what can be trying times. The data can help anticipate difficulties a customer may face, enabling an adjuster to help the insured individual with an issue even before he or she needs it or knows the need exists.

• Help customers “look into the future”

On the corporate macro level, new levels of analysis can help commercial clients view their claims trends differently and learn where they could benefit from enhancements to areas like, say, safety. If many of a company's employees are injured in commercial trucking accidents, for instance, additional driver training and monitoring could make a difference.

• Reduce fraud

Another obvious way predictive analytics helps with claims is by detecting and reducing fraudulent ones. The National Insurance Crime Bureau reports that an estimated 10% of all P&C claims are fraudulent but that only around 20% of those fraudulent claims are detected or denied. Analytics can show where and when fraud is most likely to arise and pair that with current claims to help identify potential red flags. Even if just a few types of fraudulent claims are caught per year, in the grand scope of all the claims that are made, this could end up saving insurers millions (if not billions) of dollars per year.

As more and more claims are made and their data/information is processed, the analytics will become stronger and more accurate. Does that mean predictive analytics make us perfect? Not exactly, but it will make our jobs easier and outcomes better. Just ask the Cardinals.

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Judith Vaughan, CPCU, AIC, is a director of content development at The Institutes. E-mail: [email protected]