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In the world of claims management, it can be difficult to tell the difference between a legitimate issue and an attempt to defraud a general professional liability firm. When there’s too many illegitimate cases being filed against a firm, it can cause significant issues in terms of finances and policy pricing.

With that in mind, it’s important that professional liability organizations find ways to detect which claims are which. In the grand scheme of things, big data and the ongoing influx of filings can seem daunting, but they also offer a great opportunity for companies to set their operations apart. For that, predictive analytics is a key factor.

Monitoring and management

In order to differentiate between the real and fake, claims management should learn to see the signs of a problem filing. To gain that kind of insight, organizations must first put solutions in place that are able to monitor and collect significant metrics on how, when, why and by whom claims are issued.

This venture is also strengthened by the fact that general professional liability firms have seen the value of sharing content with one another, as Insurance Tech stated. There’s a limited amount of information that can be gained just by studying the facts isolated within a single corporation. Instead, it makes more sense for companies to learn to work with one another and generate more over-arching insights that show broad trends among fraudulent filings.

“High-level collaboration ranks among the most effective tools for combating fraud,” said Dennis Jay of the Coalition Against Insurance Fraud.

This sentiment has been the foundation of a few growing organizations dedicated to providing, sharing and disseminating important updates to liability firms- regarding what they should be looking for in the fraud landscape. These groups exist in multiple nations, making it easier for firms to gain a level of insight never before possible. It’s also easier in these instances to generate strong analytics regarding where and when fraud is likely to crop up in the claims management landscape.

Government organizations are also stepping in to try and help the facilitation and sharing of this content. Insurance Tech stated that combining forces allows firms to go well beyond their own operations and create better plans for detecting and eliminating these threats to corporate continuity. This helps regulate prices, stop crime and provides more confidence to practicing professionals.

By the numbers

Considering the rate of fraud seen by general professional liability firms, it makes sense that more of them would be willing to work together in order to stop the overall problems and systematic failings that can be caused by fraud. Predictive analytics, when properly outfitted with the right metrics, is able to help companies detect whenever something is wrong with a filing. This allows for faster response time and better handling of these cases, thereby reducing the amount of money organizations might otherwise lose in these instances.

According to CBR Online, many companies are working on setting up predictive analytics systems to complement the insights they’re gaining from information-sharing groups. The source looked at research from SAS and found that over 80 percent are using automated services to help them detect red flags with incoming filings, while about half have analytics tools working on claims management systems to improve insights.

Yet there’s still been about a four percent rise in overall fraud between this year and last, indicating that these solutions aren’t perfect. There needs to be more research and data collected on what best indicates when a case isn’t quite right, as well as more detail on how organized rings generate these filings.