Jim Hulett ARM, FCLS

Annually, insurance fraud steals roughly $308.6B from American consumers. Self-insureds could be vulnerable to insurance fraud and undetected leakage.

Straight-through processing is considered the holy grail of digital claims—where insurers can intake, process, and pay claims automatically

Image forensics: How photo data can reveal claims fraud

Photo-based claims estimates have been a growing trend the past few years in the insurance industry, and once the pandemic hit, that trend accelerated significantly.

Insurers are turning to AI to detect claims fraud automatically – but to get the most from their analytics, they need to understand an anti-fraud system.

Taking a closer look at medical billing helps identify pandemic-related issues that can put patients at risk and negatively impact insurers’ bottom lines.

Neural networks, machine learning, multivariate random forest models, and various derivatives of the same are being used to create modern fraud detection models.

Unfortunately, crisis is fertile ground for fraud, whether it be the opportunistic kind or organized criminal activity.

Claims adjusters are now working at home, relying on customer-submitted images and videos to inspect and appraise damages for the foreseeable future.

As we enter 2020, the insurance industry looks much different than it did ten years ago.

For insurers looking to stem the $30 billion-a-year insurance claims fraud problem, early detection is key.