According to a recent survey by the Coalition Against Insurance Fraud, 65 percent of the 84 insurers surveyed reported that fraud had increased in the last three years. Only 10 percent reported a decrease in fraud and the remainder reported no difference. Increasingly, insurers are turning to analytics to identify and fight fraud:
- Two-thirds of respondents said they planned to earmark funds for predictive tools, compared to only 19 percent in 2016
- Forty-three percent said they planned to invest in link and social media analysis, compared to 16 percent three years ago
- Twenty-one percent said they plan to invest in artificial intelligence technology in the upcoming 1-2 years
According to Claims Journal, this represents an important shift toward predictive analytics over more traditional fraud-fighting tools such as automated red flags and business rules, although these remain popular. Tools such as text mining, link analysis and exception reporting are gaining traction in the industry, expanding the range of tools available. They are also increasing their use of unstructured data as newer tools are developed.
As third-party system providers come online and prices drop, carriers are increasing their hiring of consultants to build and maintain the anti-fraud systems they need.
Detecting fraud continues to be the No. 1 use of anti-fraud tech, although it is also being used to detect cybercrime.
Most insurers prefer quality case referrals over quantity, the survey found. Several insurers reported that some of their largest system challenges involve poor data quality and the integration of data.
Is your organization planning to use artificial intelligence, social media analysis or predictive analytics? These technologies continue to evolve and improve, but they also continue to create false positives and poor data that could add extra time and expense to your analysis. If you are already using technologies like these, do you think they have improved your anti-fraud efforts?