There was a day when we used typewriters to type documents, stored our records in filing cabinets, and took photos with our 35mm cameras. Those processes evolved as technology advanced at an exponential rate. Insurance companies—which had previously been slow to adopt new methods—had to adapt quickly to remain competitive.
As we create efficiencies in how people purchase insurance—and how we process claims—how do we balance that with fraud fighting efforts? The Coalition Against Insurance Fraud estimates the total annual cost of fraud in the U.S. exceeds $80 billion. Property and casualty fraud costs likely exceed $30 billion, so its impact cannot be dismissed.
Fraud technology cannot be overlooked when considering current and future investments. Since we are moving to less human contact in areas such as underwriting, distribution, and adjusting, we can no longer rely only on staff to alert us to suspicious claims. And it is not just opportunistic fraud that we have to be concerned about; organized fraud also continues to rise. Fraudsters continually develop creative ways to cheat insurers out of money from claims, so insurers need to reevaluate their detection methods to decrease the payouts for false claims.
The same technologies that enable business efficiencies must be leveraged for our fraud investigations. Unlike the investigative days of the past, we are surrounded—and in many cases, overloaded—with data. This includes data from smartphones, social media, the Internet of Things (IoT), vehicle infotainment and telematics systems, police body-cam videos, aerial views, and doorbell cameras. Sorting through and managing that data becomes more challenging as we identify and investigate fraud.
Special Investigation Unit (SIU) leaders must do more than keep up with current technology; they must stay in front of it and drive it forward. Following are seven tips for championing Insuretech in fraud investigations:
1. Work across functions. The important role that a dedicated analyst plays in combating fraud cannot be over-emphasized. Your dedicated analyst must communicate and work in concert with all departments to ensure a fully-integrated process is continually being updated.
2. Ensure SIU has a seat at the table. It is imperative that your SIU management has a seat at the table with senior leadership when discussing process changes and technology that may impact customer service and also influence the way you investigate fraud.
3. Educate your organization on data-mining opportunities. Awareness and training of SIU and claims staff, and others in your organization, regarding current and emerging opportunities to gather data from the many segments of that emerging technology is essential. Transforming data into shared and transparent intelligence applied at the point of a claim changes the game in customer service and fraud detection. Data that used to take weeks to sort can be analyzed and acted upon in minutes today. As technology transforms data into shared and actionable intelligence, claims will be validated more promptly. The increased efficiency will eliminate many unknowns and produce happier customers and higher-quality investigations.
4. Develop a strategy for how data will be used. After data is gathered, you must identify how to process and analyze it, and then integrate the intelligence obtained from the data back into claims, policy, underwriting, actuarial, marketing, and anti-fraud initiatives.
5. Loop in legal. Include your legal team in the discussions and decisions about gathering data from wearable and telematics devices such as mobile phones, metadata, intellectual-property intelligence, geolocation, and digital footprints, as privacy laws vary and continually change between states. Differences include who owns the data and if there is an expectation of privacy.
6. Don’t ignore traditional investigative skills. Just because they are traditional doesn’t mean tried-and-true investigative skills should not be used. Conventional investigative skills and techniques are still required, yet now must be used in conjunction with a new technological skillset.
7. Promote Data Integrity. As fraud models are built out to advance predictive analytics, it is important to note that the validation of data and data integrity is crucial. Many companies are so overwhelmed by the amount of data that, unfortunately, data integrity is often overlooked. A commitment to data integrity is required from your company’s leadership and staff in order to ensure the success of any fraud predictive analytic system. Utilizing data pre-fill systems can help improve the quality of data going into your systems.
From Reactive to Proactive
Historically, insurance companies adhered to a “pay-and-chase process”—rather than a predictive model—to prevent fraud before a bad policy is written, a loss is incurred, or a payout is made on fraudulent claims. We can no longer remain reactive in our approach to insurance fraud. We must be proactive and start identifying fraud at the point of sale, when that application is first submitted, and throughout the various processes where data is submitted, transferred, or gathered.
Developing and maintaining a robust fraud-analytic system along with an effective strategy to proactively deal with mounting insurance fraud problems—using many of the same tools and data that make our lives easier—will enable insurers to detect, prevent, and manage both opportunistic and professional fraud across multiple lines of insurance.
By having a well-trained staff, the tools discussed in this article, and a commitment to staying ahead of the continual technological changes and advancements, we will be prepared for investigating fraud today and in the future. At the same time, we will be able to satisfy customers’ demands for a streamlined process of obtaining insurance and expedited processing of claims. We can meet the needs of the customer without giving up a thorough, quality investigation.