Fighting Financial Crime with AI and Machine Learning
Learn how financial institutions are leveraging AI to detect and combat complex financial crimes like fraud and money laundering more effectively than ever before.
As financial transactions become increasingly digital and instantaneous, the methods used by criminals have grown more sophisticated. Traditional rule-based systems for detecting fraud and money laundering are struggling to keep up. Artificial Intelligence and machine learning are now the front line of defense in the fight against financial crime.
Uncovering Hidden Patterns
AI systems, like the Feedzai Risk Engine, analyze billions of data points in real time to understand what constitutes normal behavior for each user. They can detect subtle anomalies that signal fraudulent activity, such as unusual transaction times, locations, or amounts. For anti-money laundering (AML), AI can perform complex network analysis to uncover hidden relationships between entities that might be part of a sophisticated laundering ring.
Reducing False Positives
A major pain point for legacy systems is the high number of false positives—legitimate transactions incorrectly flagged as suspicious. This frustrates customers and wastes investigators' time. By learning individual behavioral patterns, AI models drastically reduce these false alarms, allowing compliance teams to focus their resources on genuine threats and high-risk cases.