Insurance companies waste considerable time and money sorting out fraudulent claims from real ones. It’s more than just an inconvenience — it means victims of actual accidents must wait longer for compensation.
When claims fraud does slip through the cracks, insurance companies inadvertently reward people for their crimes. Thankfully, data analytics and automation are making it much easier to detect.
Using Digital Image Forensics
Photo-based estimating allows policyholders to take photos of their damaged home, car or other property to submit insurance claims. The catch is they’re easier to manipulate than ever, opening new avenues for fraud. People occasionally skip the Photoshop process entirely by submitting pictures they found online.
That’s where digital image forensics comes in. The technology analyzes data to determine where and when photos were taken. It can also reverse search images to see if a picture appears anywhere online.
Harnessing Predictive Modeling
One of the biggest benefits of advanced analytics is the software’s ability to learn from historical data. By looking at the outcomes of past cases, predictive modeling estimates the chances that a claim is fraudulent.
It employs a combination of text mining, modeling, database searches and exception reporting to flag potentially fraudulent claims fast. Catching potential fraud early means saving time and money companies would otherwise spend trying to recoup lost funds.
Getting a Wider Perspective
Analytical tools make it easier to notice patterns in prior claims fraud cases by providing access to external data. Supplemental reports from public records, social media searches and vehicle location images can offer valuable insights about involved parties — and sometimes unveil suspicious details.
For example, ClaimSearch gives insurance agents a broader view of the insurance sector to detect fraud. This massive database of insurance claims has claims-matching technology, allowing users to connect the dots between prior investigations, previous salvage, loss histories, mail drop addresses and other attributes that hint at deception. It offers a deep dive into how seemingly unrelated claims and people connect through shared events.
Improving SIU Operations
According to the U.S. Federal Bureau of Investigation, false insurance claims cost over $40 billion annually, making fighting claims fraud a full-time job. To collect stolen money and prevent theft in the first place, an insurance company’s special investigative unit (SIU) is tasked with time-consuming tasks like auditing, triage, reporting and compliance procedures.
Case management systems can automate these steps to make the SIU more efficient and productive. Software like Decision Net scans incoming claims for suspicious traits such as previous salvage, prior SIU involvement and foreclosure to flag them for potential fraud.
Processing Claims Faster
Insurance companies often assign the most complicated insurance claims to senior agents. However, they occasionally give complex cases to less experienced adjusters due to a lack of information. When the mistake becomes apparent, they have to reassign the claim to someone with the resources to tackle it. This inefficiency can affect the amount of money paid for settlements, lead to delays in processing claims and impact how policyholders feel about their experience.
Advanced analytics can organize claims based on their characteristics. Software can assign them scores based on how involved they are and how likely it is that they’ll lead to litigation. Then, insurance companies can quickly transfer those cases to higher-level agents who can settle the claims sooner.
Cutting Through the Red Tape
Insurance agents have a notoriously difficult job, especially when fraudsters go to great lengths to commit claims fraud. However, advanced analytics have been a game changer for the insurance industry, helping companies parse a slew of false claims from legitimate ones. Thanks to new computing tools, preventing fraud just got a whole lot easier.
Devin Partida writes about investor technologies, big data and apps. She is also the Editor-in-Chief of ReHack.com.
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