AML AI Regulations
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Our client has built an AML AI product for transaction monitoring that is a fully machine learning based solution wholly different from traditional rules based models. They have asked for our help with understanding the regulatory guidance and environment across various global regions in regards to AML/ transaction monitoring, receptiveness to AI, and how well their product meets requirements. Note that we are specifically interested in the following countries: Canada, USA, Mexico, Denmark, Germany, Italy, Netherlands, Spain, United Kingdom, France, Brazil, Australia, and India
We are hoping to collect the following information:
- Inventory or summary of global AML / transaction monitoring regulations and guidance
- Perspectives on trends / changes to AML / transaction monitoring practices/ regulations
- Insights on regulatory perspectives / statements on AI, specifically on regulatory receptiveness to AI
- Leading transaction monitoring best practices that regulators assess
- Recent regulatory fines / penalties / feedback related to transaction monitoring
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For Canada specifically, please refer to the latest Draft Guideline E-23 on model risk management by OSFI (our banking and insurance regulator).
To capture the risk posed by AI, the Draft Guideline modernizes the definition of “model” in the original 2017 Guideline to explicitly include AI and machine learning methods. Basically the AI-based solutions are considered “models” and are subject to model risk management requirements. Detailed requirements can be found in the guideline