Predictive Analytics
Artificial intelligence in claims fraud: How AI is automating suspicious behavior detection
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.
COVID-19 and workers’ comp: Managing rising claim volume and costs
With thousands of essential employees reporting to work—including health care workers—there could be an influx of workers’ comp claims related to the virus.
The critical role fraud scenarios play in advanced analytics
Neural networks, machine learning, multivariate random forest models, and various derivatives of the same are being used to create modern fraud detection models.
Five data-driven strategies for fighting insurance claims fraud
As we enter 2020, the insurance industry looks much different than it did ten years ago.
New credit-based insurance score taps two powerful resources
Verisk and Equifax have joined to create Inflection, a credit-based insurance score powered by a trended-credit model to increase its predictive potential.
How to find fraud in insurance claims
For insurers looking to stem the $30 billion-a-year insurance claims fraud problem, early detection is key.
Property/casualty medical fraud: 5 strategies for reducing your exposure
It seems like every month there’s news of another medical fraud bust, often involving rings of various types of providers. But that’s just the tip of the iceberg.
How Insurers Can Know When to Enter a New Market or Line of Business
By using powerful data tools, insurers can discover which markets have strong growth potential.
Litigation insights offer the key to rising claim costs
Legal analytics make it possible for insurers to derive actionable insights from legal data to improve claims handling and litigation outcomes.
Successful workers’ comp analytics starts with the right plan
Workers’ comp analytics can improve claims process by identifying high-severity claims early, promoting consistency in claim handling, and improving return-to-work…
All-or-nothing automation? Incremental change is a winning proposition
Robotic process automation (RPA), machine learning, and AI can be embedded in processes throughout the claim life cycle—from triaging through settlement.
3 keys to stopping medical provider fraud, waste, and abuse
It’s no secret that medical fraud is a big problem, with some sources estimating the cost at more than $200 billion annually.
As claim severity climbs, analytic insights hold key to containment
Insurers today are struggling with what seems like an intractable problem: the impact of rising claim severity on their bottom line. This upswing shows no sign of…
Getting serious about fighting medical provider fraud
Complex medical bills can make it difficult for adjusters—already overloaded with cases—to find potential fraudulent or excessive billing.
Refinement comes before insight with telematics data
Usable insight from the Internet of Things (IoT) often flows through data science, predictive modeling, machine learning, and artificial intelligence (AI).