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In today’s increasingly digital world, fraud and financial crime have become significant concerns. Global research shows that 2022 witnessed aincrease in fraudulent activity, with almost a quarter of survey respondents expecting a significant budget increase for anti-fraud technology through 2025. Given the transformative impact of artificial intelligence across all industry sectors, the challenge of combating financial crime has grown more complex and multifaceted.
Generative AI also holds the potential to transform fraud and financial crime compliance. By incorporating machine learning and network analytics into anti-fraud and anti-money laundering systems, organizations can significantly reduce the number of false negatives and positives, thereby enhancing transaction monitoring efficiency.
A second strategy involves fortifying and expediting authentication processes to validate customers in the digital realm. Leveraging multiple data sources related to device intelligence, behavioral biometrics, and information trustworthiness shared by customers can help identify real customers, fraudsters, or bots. This not only enhances fraud detection but also reduces customer friction.
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