Adrian JohnsonGenerative AI in anti-fraud technology expected to triple, says ACFE | Accounting Today
Generative AI is predicted to play a larger role in anti-fraud efforts, with the use of artificial intelligence expected to triple in the next two years, according to the Association of Certified Fraud Examiners (ACFE). A report from the ACFE indicates that 18% of professionals involved in anti-fraud currently use AI and machine learning, with a further 32% planning to adopt the technology in the next two years. Additionally, 83% of respondents said they expected to see the use of generative AI rise over the next two years. The report also noted that over 50% of existing anti-fraud programmes are utilising or anticipate implementing related technologies, including computer vision analysis, robotics, and behavioural biometrics. AI has already become a key tool in combating fraud across various sectors, and its continued use is expected to be a crucial part of anti-fraud strategies in the future.
Despite the growing interest in AI and machine learning, many organisations cited budget constraints as a major hurdle to implementation. Over 80% of professionals surveyed said that finding the necessary resources was a significant challenge, followed by concerns over data quality and integration (73%) and a lack of perceived return on investment (68%). However, despite these difficulties, 59% of respondents stated that they planned to increase their budgets for anti-fraud technology within the next two years, while only 6% planned to decrease funding. This suggests that professionals recognise the importance of AI in fraud prevention and are willing to allocate financial resources accordingly.
The report also provided insights into the specific types of fraud being monitored by anti-fraud professionals. The highest priority was given to guarding against disbursements and outgoing payments fraud, followed by procurement or purchasing fraud, fraud by customers, travel and expense payment fraud, and fraud involving thefts or incoming payments. The lowest priorities were inventory theft, hacking or data breaches, identity theft or account takeovers, corruption or bribery, and fraud committed by vendors or contractors.
Overall, the use of AI and machine learning in anti-fraud technology is expected to grow significantly in the coming years. Generative AI in particular is predicted to play a major role in future anti-fraud efforts. However, organisations will need to address challenges related to budget, data quality, and integration in order to effectively implement these technologies.