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AI and Financial Crime Prevention: Why Banks Need a Balanced Approach
- Financial criminals are leveraging AI technology to produce deepfake videos, voices and fake documents that can get past computer and human detection.
- Generative AI is expected to accelerate fraud losses to an annual growth rate of 32% in the US to reach US$40 billion by 2027 according to Deloitte.
- Banks are deploying AI in anti-financial crime (AFC) efforts to monitor transactions, generate suspicious activity reports, automate fraud detection.
- AI-driven systems introduce a complex “black box” element due to opaque decision-making processes.
- Banks need careful planning, thorough testing, specialized compliance frameworks and human oversight to ensure AI accountability.
- Human judgment remains essential in AFC investigations and AI systems require Explainable AI tools to make AI-driven decisions understandable to regulators.
- Financial institutions can combine a rules-based approach with AI tools to create a multi-layered system that leverages the strengths of both approaches.
- Risk and compliance experts must be trained in AI to develop compliance frameworks specific to AI.
- High-quality, secure data infrastructure is essential for AI implementation.
- AI is a two-sided coin for banks that needs a cautious, hybrid approach to minimize risks and increase efficiency.
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