Insurance fraud fighters are planning to accelerate adoption of AI tools

While AI and ML tools garner interest, their adoption for fraud detection has only increased by around 5% since 2019.

Fraud-fighting professionals in the insurance sector have a slightly higher AI and ML adoption rate, as 24% of industry professionals said they currently count these technologies among their fraud-fighting tools. Image generated using Pixlr AI

By 2026, 83% of anti-fraud professionals from across industries expect to be using artificial intelligence-driven tools, according to the Association of Certified Fraud Examiners (ACFE) and SAS, which surveyed worldwide fraud fighters from industries ranging from entertainment and insurance to utilities and warehousing.

“Generative AI has made great strides these last few years, so it’s no surprise that organizations are incorporating it into their anti-fraud initiatives,” ACFE Research Director Mason Wilder said in a release. “As a society, we are still learning all the advantages and disadvantages to using the technology, but more organizations are beginning to take that first step.”

As it stands, more than 90% of organizations use some form of data analysis to fight fraud. However, just 18% of fraud fighters currently use AI and machine learning (ML), while 32% expect to implement those specific technologies within two years.

Fraud-fighting professionals in the insurance sector have a slightly higher AI and ML adoption rate, as 24% of industry professionals said they currently count these technologies among their fraud-fighting tools. Further, 30% of insurance fraud fighters anticipate adding AI and ML to their fraud arsenal in the coming years.

While AI and ML tools draw a lot of interest, the adoption rate of these technologies for fraud detection and prevention has only grown around 5% since 2019. This is well below earlier projections, ACFE reporting, pointing to 2019 and 2022 studies that anticipated adoption rates of 25% and 26%, respectively.

According to Stu Bradley, senior vice president of risk, fraud and compliance solutions at SAS, slow adoption rates show how complex it is to scale up AI and analytics processes across an enterprise. He explained that leveraging segmented processes across a single, AI-powered risk management platform can help make the transition smoother.

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