Status: Draft -- Not PublishedWill be live at 09/25/2019 11:35
Machine Learning Recommendations for Policymakers
Building on the insights from our previous surveys on the adoption of Machine Learning (ML) in credit risk and anti-money laundering, as well as the IIF’s thematic papers on Explainability and Bias & Ethical Implications, this new paper articulates how policymakers and supervisors can assist in ensuring safe innovation, harnessing the benefits of these new technologies while minimizing and mitigating risks.
These recommendations for policymakers are set out in a series of 8 key principles, aligned to 3 key themes of avoiding over-regulation, supporting adoption and ensuring level playing fields. These principles are complemented by some example leading practices set out in the appendices.