6 Advantages of Insurance Fraud Analytics

Insurance CIO Outlook | Tuesday, May 10, 2022

Carriers have been frustrated for decades by insurance claims fraud. As a result, insurers are left paying millions of dollars in fraudulent claims despite their best efforts.

Fremont, CA: It is unlikely that insurance fraud can be eliminated, but carriers have a new weapon - insurance fraud analytics. Thanks to advanced data technology made possible by digital insurance tools, insurers can finally get ahead of criminals committing fraud.

Eight Benefits of Insurance Fraud Analytics

Better Assess Risk:  A fraud analytics AI is better equipped to identify risk than anyone else: An AI is better equipped to identify risk than anyone. Artificial intelligence and predictive modeling systems can analyze massive amounts of data in fractions of a second that would take a person days to scan before identifying similar patterns.

Improved Fraud Detection: Insurance fraud analytics, just like risk assessment, can identify red flags or anomalies that might indicate fraud schemes. Using these flags, analytics teams can build high-quality referrals for their fraud teams. In addition, the algorithms can identify high-risk areas that should be included in a fraud risk assessment.

Identify Low-incidence Events: Low-incidence events can slip through the cracks and are arguably the most costly to insurers. Because fraud detection is largely based on patterns and trends in behavior, they can be hard to identify. A fraud analytics program can help flag outlier events and refer them to a fraud team for further analysis.

Speed up Fraud Detection:  Fraud analytics make it easier for insurers to identify fraudulent claims or potentially fraudulent claims. It is critical in today's economy, especially in cases of workers' compensation (where fraud is on the rise). Insurance companies can respond and prevent losses more quickly if fraud is identified early.

Increase Fraud Savings: The ultimate goal of fraud detection is to prevent insurers from incurring fraud-related losses. Detecting fraud before it is processed or in a way that enables carriers to act quickly reduces losses.

Identify New Fraud Tactics: As technology advances to catch up with fraud, criminals discover new tricks that will remain undetected. For example, some schemes - such as requesting small claims amounts - will not be caught using off-the-shelf insurance fraud analytics programs. However, advanced AI analytics can be configured to detect new and emerging abnormal claims using machine learning techniques like cluster analysis.

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