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Study: 8 in 10 fraud fighters expect to deploy generative AI by 2025

Global survey of anti-fraud pros by the ACFE and SAS reveals incredible GenAI enthusiasm – but past benchmarking studies suggest a more challenging reality

Generative AI has captured the public imagination, its power and promise seemingly poised to affect every facet of society. It’s hardly any wonder then that 83% of anti-fraud professionals anticipate adding the technology to their anti-fraud armaments within the next two years, according to the latest anti-fraud tech study by the Association of Certified Fraud Examiners (ACFE) and SAS.

The 2024 Anti-Fraud Technology Benchmarking Report is the third installment of a global research study initiated by the ACFE and SAS in 2019. This latest edition reflects insights from nearly 1,200 ACFE members surveyed in late 2023. The survey data reveals key trends in the evolution of fraud fighting since 2019. Among them:

Interest in artificial intelligence (AI) and machine learning (ML) technology is higher than ever. Nearly 1 in 5 anti-fraud pros (18%) currently counts AI/ML among their fraud-fighting tools. Another 32% anticipate implementing these technologies in the next two years – a peak since the study’s inception. At this rate, use of AI/ML in anti-fraud programs will almost triple by the end of next year.However, AI and ML adoption consistently lags expectations. Despite fervent interest, adoption of AI and ML for fraud detection and prevention has grown only 5% since 2019. That figure falls far short of the anticipated adoption rates revealed in the 2019 and 2022 studies (25% and 26%, respectively).While the use of many data analysis techniques has plateaued, the application of biometrics and robotics in anti-fraud programs has risen steadily. Use of physical biometrics has climbed 14% since 2019, now cited by 40% of respondents. One in 5 survey respondents (20%) reported using robotics, including robotic process automation, up from 9% in 2019. The use of these technologies is notably highest in banking and financial services, with half (51%) using physical biometrics and one-third (33%) using robotics.

“The accessibility of generative AI-powered tools makes them incredibly dangerous in the wrong hands,” said ACFE President John Gill. “Three in five organizations foresee increasing their anti-fraud technology budgets over the next two years. How they invest these funds will determine who will seize the upper hand in what’s become a technology arms race with criminal enterprises. It’s an uphill battle when you consider that, unlike the fraudsters, organizations face the added challenge of having to use these technologies ethically.”

“Explosive interest in advanced analytics techniques juxtaposed with much more modest adoption rates proves the complexities of scaling the AI and analytics life cycle,” said Stu Bradley, Senior Vice President of Risk, Fraud and Compliance Solutions at SAS. “It also underscores the importance of choosing the right technology partner. AI and machine learning aren’t simple, plug-and-play applications. However, their benefits can be more readily realized by deploying modularized solutions across the risk management spectrum on a single, AI-powered platform. That’s SAS’ approach with cloud-native, language-agnostic SAS Viya.”

Explore trends by industry, geography and moreComplementing the benchmarking report, SAS’ online data dashboard allows users to analyze survey data by industry, geographic region and company size.

Survey respondents work in 23 industries – most prevalently banking/financial services and government/public administration (each accounting for 22% of respondents), but also professional services (13%), insurance (5%), health care (4%), manufacturing (4%), technology (4%), education (4%) and more. Their employer organizations span the globe and range in size from fewer than 100 employees to more than 10,000.

Read the report and visit the data dashboard at SAS.com/fraudsurvey to examine cross-industry, anti-fraud tech trends and sentiments around:

Data analysis techniques organizations use to fight fraud.Risk areas where organizations apply data analytics to monitor for fraud.Data sources organizations use in their anti-fraud initiatives and their perspectives on data-sharing consortiums.The prevalence of case management and digital forensics/e-discovery software.Challenges organizations face in implementing new anti-fraud technology.How generative AI is affecting organizations’ anti-fraud programs.

The future of GenAI: Boom or bust?Will the deployment of generative AI in anti-fraud programs skyrocket in line with survey respondents’ passionate intent? Or will real-world challenges like budgetary restrictions, data quality and skills gaps inhibit its predicted ascent? Only time will tell – but organizations can’t be too careful in embracing GenAI and other AI technologies. Responsible innovation requires organizations to ask not only “could we” but also “should we?”

“The use of generative AI in anti-fraud initiatives could play a significant part in identifying anomalies, trends and indications in larger volumes of data with minimal resource concerns,” said one survey respondent. “However, the organization will need to ensure that proper guidelines are in place to minimize errors and bias.”

“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,” said ACFE Research Director Mason Wilder. “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. It will be interesting to see how quickly adoption occurs, in and out of the workplace, in addition to the technology continuing to become more advanced with time.”

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