Institute of International Finance ‘Explainability’ in Machine Learning

FRT welcomes Chisoo Lyons, Vice President of Analytic Ventures at FICO. FICO kindly provided a case study  in the IIF’s recent paper on Explainability in Machine Learning. Together with IIF lead author Natalia Bailey, Chisoo discusses the main ways in which FICO has been using Machine Learning and big data to help get better insights in the data, with an emphasis on tackling ‘explainability’, and the importance of data quality.

The IIF’s Explainability paper is the first in a thematic series, building on our earlier Machine Learning in Credit Risk report. The second paper in this series will focus on bias and ethical implications, and the third will elaborate on recommendations to supervisors and regulators.