The IIF’s recent Machine Learning Governance study details the results of our comprehensive survey on the end-to-end governance of the machine learning development and implementation process within the global financial services industry.

66 financial institutions participated in this survey, and the report covers six key areas of focus, including foundational aspects, data and inputs to machine learning, governance mechanism, model validation, model implementation, and model monitoring.

One of the leading contributors, Rachel Bailey, a senior manager specializing in machine learning in model risk and validation at Lloyds Banking Group, joins IIF report authors Natalia Bailey and Dennis Ferenzy on FRT to discuss the study’s key findings, including around model governance frameworks and controls against bias and discrimination.

While the distribution of the full detailed report is limited to the 66 participant firms and the regulatory community, a summary version of the Machine Learning Governance Report is available here.