It’s difficult to determine at first glance if a claims management issue is a legitimate case or a potential fraud. However, there are emerging technologies and existing computing methods that could help general professional liability services make these kinds of determinations.
The name of the game, these days, in the professional liability landscape is predictive analytics. As Property Casualty 360 stated, more than 80 percent of insurers in the United States currently have some form of this technology in play. What’s more, they use it not just for market forecasts and policy pricing. Analytics is becoming a powerful tool in the fight against fraudulent claims.
There’s no room for uncertainty in the claims management realm, the source explained. There needs to be a standardized, administrative process that’s backed up by actuarial evidence and proven success. This can be achieved by reviewing the inventory of past cases and finding the trends that exist between legitimate and fraudulent filings.
Data mining in this manner allows organizations to see the cracks in cases that allow these erroneous issues to unravel. Advanced statistics and multi-presence analytical techniques make it easier to find relationships between cases and create commonality that can be applied rapidly to any claims application.
With these kinds of models and formatting ideas in mind, many general professional liability firms are trying to move forward with their plans to reduce fraud and increase the effectiveness of predictive analytics. Every year, Insurance Networking reported, there’s about $80 billion lost in America due to fraudulent claims. If companies can more effectively implement analytics and create meaningful, actionable plans with this data, they could save companies a significant amount of money.
“Lots of carriers are starting to talk about what the industry can do about underwriting fraud,” Claims Management expert, Tim Wolfe, told the source.
As technology continues to improve, so too do the ways in which organizations are able to hone in on potentially fraudulent claims. Faster processing, deeper big data delves and heightened accountability standards have helped companies motivate their IT staff and improve the quality of their agents’ responses to issues that seem to fit fraud trends.
Best of all, predictive analytics is ideal for generating the kinds of metrics that can stand alone in the midst of a chaotic data-driven world. As the progression of tech and tools continues, so too must general professional liability services also strive to keep up with these factors. That way, there’s no way for fraudsters to get the better of predictive analytics.