Five data-driven strategies for fighting insurance claims fraudBy Jim Hulett | February 27, 2020
As we enter 2020, the insurance industry looks much different than it did ten years ago. Technological advancements, InsurTech innovations, and customer experience enhancements have transformed the industry. Yet, one thing remains constant—claims fraud continues to challenge insurers.
It’s estimated that one in ten no-fault claims has a measure of fraud. Claims fraud ranges from opportunistic behavior, such as padding losses to receive a bigger settlement check, to orchestrating organized insurance fraud scams on a large scale. Verisk conducted a two-year analysis of industrywide claims data and discovered 17 million discrete fraud networks of two or more individuals with suspicious claim activity. The pervasiveness and amorphous nature of these schemes make fighting organized fraud particularly difficult.
No matter the scale of the deception, it’s critical to detect fraud early. Balancing this need against policyholder demands for faster settlements is challenging. Here are some strategies to help you meet that goal.
1. Leverage predictive analytics for early detection
The dream of no-touch claims processing is getting closer to reality. And as the percentage of low-touch claims increases, insurers need proactive fraud analytic models that identify suspicious claims early to avoid paying for fraudulent claims.
Technologies like artificial intelligence and predictive analytics are critical to making this happen. These technologies provide highly accurate claim scores and reason codes necessary to detect questionable claims quickly and deliver critical insights to investigators.
But according to an Association of Certified Fraud Examiners survey, only 30 percent of organizations are using the technology to fight fraud. To stay ahead of fraudsters, the industry must expand its use of this technology.
2. Analyze industrywide data
The most effective way to analyze claims is to have a broad view. While an insurer’s historical claims data can provide insights and trends of fraud, you’ll miss out on a significant number of suspicious claims with this limited view.
Analyzing broad industry data gives you a wider perspective, helping you review loss histories, prior SIU investigations, prior salvage, mail drop addresses, and other attributes indicative of fraud from claims across the industry. It’s an essential first line of defense against claims fraud. Additionally, industrywide data allows an understanding and view of how seemingly disparate claims, people, and entities are connected through linked events.
3. Detect digital fraud with image forensics
More insurers are using photo estimatics to streamline claims processing, allowing policyholders to submit loss images with claims. But the trend can expose carriers to more fraud from altered images and photos of preexisting damage being used for new claims.
Digital image forensics helps solve the problem. The technology analyzes image data to determine when and where a photo was taken and if it appears on the Internet. As photo estimatics becomes more prevalent, this technology will be increasingly vital to fighting fraud.
4. Access external records quickly
When adjusters or investigators need to find missing information to analyze a claim, supplemental data reports can provide valuable information about an entity or involved parties and uncover suspicious details. Reports such as third-party public records data, social media searches, and vehicle location images are particularly useful in gathering data for investigations. It becomes even more powerful when automated and blended into analytics at first notice of loss. In addition to driving powerful analytics, this information provides deep contextual insight and specific reasons for focused investigation.
But as you look to automate and streamline claim review and fraud checks, it’s important not to get bogged down hunting for details from multiple sources. Accessing supplemental claims information from a single portal helps expedite claims analysis.
5. Embrace automation in case management
SIU operations are more complex than in the past and are being asked to do more with less. They involve centralized resources, task force approaches, investigative vendors, new data sets, and regulatory requirements. Claim systems are no longer effective at managing the unique tasks associated with case management. Further, organizational intelligence derived from investigative results is critical to understand trends and drive predictive analytics.
That’s why having a modern case management system is vital. New SIU case management solutions can automate time-consuming tasks such as triage, auditing, reporting, and compliance to help boost productivity and efficiency. Because SIUs handle major cases that involve organized rings, they’ll need advanced solutions to manage investigations. Further, key data points around investigative results allow for the tuning and retrofitting of predictive models.
Stay on the cutting-edge of fraud detection
The insurance industry landscape continues to shift, and anti-fraud methods must keep pace. Organizations that adopt next-generation fraud tools and modern strategies will potentially stay ahead of fraudsters, mitigate risks, and reduce leakage. Those who continue business as usual risk greater exposure and increasing losses.
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