AI Spotlight

Transforming Fraud Detection in Internet Banking with AI

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Explore how Hybrid AI significantly improves fraud detection in the financial sector by combining advanced analytics, pattern recognition, and human expertise. Hybrid AI effectively addresses the evolving and complex fraud patterns in Internet banking. Additionally, integrating these technologies streamlines the work of case analysts, making fraud prevention more efficient and accurate.

Key Benefits

  • Reduction in False Positives: Hybrid AI lowers false positives in fraud detection.
  • Alert Prioritization: High-risk alerts are highlighted, and low-risk alerts are filtered out, improving response times and service quality while reducing cognitive load on investigators.
  • Improved Decision-Making and Transparency: The combination of machine learning (ML) and human expertise improves decision accuracy, while interpretable ML and cognitive models ensure transparent decision-making.

Use Case

Summary

  • A banking and financial services company recently adopted the INFORM Hybrid AI approach, combining Machine Learning algorithms with cognitive intelligence and dynamic profiling to enhance fraud detection in online banking and payment services.
  • This method significantly reduced false positives compared to using only a knowledge-based system, leading to notable improvements in detecting and preventing illicit activities.
  • Additionally, our software optimized resource allocation by prioritizing critical alerts and minimizing unnecessary alert management for case investigators, balancing automated efficiency with human judgment.

How It's Done

  • With knowledge-based decisioning already in place, integrating Machine Learning (ML) was straightforward and smooth. Initially operating as an add-on, the implementation delivers significant results immediately.
  • Alerts generated by the knowledge-based system are prioritized, enhancing case investigations by enabling investigators to focus on relevant cases and use ML explanations for informed decision-making.
  • Both the customer and our team are satisfied with the process and outcomes, demonstrating our ability to execute such projects efficiently without it being a significant undertaking.

Did You Know?

  • Investigating alerts for potential fraud can be a significant expense for banks, with costs per alert typically ranging from $25 to $50. This can lead to substantial financial burden, especially for banks handling large volumes of alerts annually, potentially resulting in multi-million-dollar expenditures. These costs include the resources needed for detailed investigations and the staff time required to manage and analyze the alerts effectively, as reported by NerdWallet.
  • The cost of fraud for banks, particularly in Internet banking, is substantial. According to ABA Banking Journal, Banks incur additional expenses of approximately $4.36 for every dollar lost to fraud due to related costs such as legal fees and recovery efforts. This means that the financial impact extends far beyond the initial fraudulent transaction.

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