Rapid Growth in AI Adoption for Anti-Fraud Initiatives Predicted Through 2026

The latest 2024 Anti-Fraud Technology Benchmarking Report, a collaborative effort between the Association of Certified Fraud Examiners (ACFE) and SAS, reveals an expected surge in the application of artificial intelligence (AI) and machine learning in anti-fraud programs across various industries. Insurance, while only 5% of the survey’s respondents, is among the top four sectors leading this shift towards digital vigilance against fraud. This study anticipates that by 2026, 83% of organizations will have integrated generative AI into their anti-fraud strategies, marking a considerable escalation from current adoption rates.

This growing trend reflects a broader willingness among organizations to pool resources and share data to bolster fraud detection capabilities, with over 60% either currently participating in or open to joining data consortiums. Despite financial constraints cited by 82% of organizations as a primary barrier, there is an optimistic outlook on expanding anti-fraud technology budgets in the near future. Remarkably, more than half of the surveyed entities are exploring or planning to adopt advanced technologies such as computer vision analysis, robotics, and behavioral biometrics, indicating a diversification of tools in combating fraud.

The report underscores a significant reliance on data analysis in current anti-fraud efforts, with over 90% of organizations employing some form of this technology primarily for exception reporting, anomaly detection, and monitoring automated red flags. The anticipated leap in AI and machine learning adoption signifies a pivotal shift towards more sophisticated, predictive analytics to navigate the complexities of modern fraud detection. Legal professionals, like CLM member Ian Stewart, emphasize the indispensable role of these technologies in enhancing the efficacy of anti-fraud programs, albeit without completely replacing the critical human element in fraud analysis.