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AI and ML to Reshape Anti-Fraud Efforts in 2024 Report

TL;DR

  • AI & ML in anti-fraud to triple by next year, signaling a tech revolution in fraud prevention.
  • Despite high hopes, AI & ML adoption in fraud detection has grown just 5% since 2019.
  • Biometrics & robotics are on the rise, with banking leading in tech adoption for fraud fighting.

In an era where digital advancements are at the forefront of corporate strategies, the fight against fraud is no exception. A new report reveals a significant shift towards the adoption of artificial intelligence (AI) and machine learning (ML) among anti-fraud professionals. The 2024 Anti-Fraud Technology Benchmarking Report, conducted by the Association of Certified Fraud Examiners (ACFE) and SAS, outlines the current landscape and future expectations for technology’s role in combating fraud.

Key findings and trends

The survey, drawing insights from nearly 1,200 ACFE members, highlights a strong interest in AI and ML technologies. Currently, 18% of respondents are utilizing these tools in their anti-fraud efforts, with an additional 32% planning to implement them within the next two years. This projected growth suggests a near-tripling in the use of AI/ML for fraud detection and prevention by the end of the following year, marking a peak in interest since the study began.

Despite the optimism, the adoption rate of AI and ML technologies has grown by only 5% since 2019. This figure starkly contrasts with the anticipated 25% and 26% adoption rates reported in the 2019 and 2022 studies, respectively. This discrepancy highlights a gap between expectations and reality, suggesting challenges in the widespread implementation of these technologies.

The report also sheds light on the use of other technologies in anti-fraud programs. The application of biometrics and robotics has seen a steady increase. Physical biometrics usage has climbed by 14% since 2019, with 40% of respondents now employing this technology. Meanwhile, robotics, including robotic process automation, has more than doubled from 9% in 2019 to 20%. The financial services sector, in particular, leads in adopting these technologies, with significant usage of physical biometrics and robotics to enhance fraud prevention efforts.

Anti-fraud Technology Benchmarking Report cite implications for the future

The findings of the 2024 Anti-Fraud Technology Benchmarking Report suggest a dynamic shift in the fraud prevention landscape. The growing interest in AI and ML technologies indicates a recognition of their potential to enhance anti-fraud measures significantly. However, the slower-than-expected adoption rate points to possible challenges, such as the need for specialized skills, budget constraints, or concerns about the accuracy and reliability of these technologies.

The increasing use of biometrics and robotics signals a broader trend toward integrating advanced technological solutions in the fight against fraud. These tools offer new possibilities for securing transactions and identifying fraudulent activities, emphasizing the importance of innovation in maintaining the integrity of financial systems.

As the fraud prevention landscape evolves, organizations must navigate the challenges of adopting new technologies while maximizing their potential benefits. The insights from the 2024 Anti-Fraud Technology Benchmarking Report serve as a valuable resource for understanding current trends and setting the direction for future efforts in combating fraud.

The report underscores the critical role of technology in shaping the future of fraud prevention. As AI and ML technologies become increasingly central to anti-fraud strategies, their successful implementation will require ongoing commitment, investment, and adaptation to the changing dynamics of fraud. With the right approach, these technologies promise to significantly enhance the effectiveness of fraud prevention measures, safeguarding businesses and consumers alike from the evolving threats of fraudulent activities.

Disclaimer. The information provided is not trading advice. Cryptopolitan.com holds no liability for any investments made based on the information provided on this page. We strongly recommend independent research and/or consultation with a qualified professional before making any investment decisions.

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Glory Kaburu

Glory is an extremely knowledgeable journalist proficient with AI tools and research. She is passionate about AI and has authored several articles on the subject. She keeps herself abreast of the latest developments in Artificial Intelligence, Machine Learning, and Deep Learning and writes about them regularly.

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