Wednesday, August 22, 2018

2017 & 2018 have seen more banks implementing and/or running pilot projects to deploy Machine Learning techniques in their credit risk management and modeling. While their tools and models have been around for many years, recent increases in computing power and data storage have catalyzed the expanded opportunities for application.

In Episode 3 of FRT, we explore the key findings from the IIF study, in which we interviewed 60 firms (58 banks and 2 mortgage insurers) on their adoption or exploration of machine learning. We discuss the specific techniques applied, key areas of application (such as credit decisioning and the monitoring of deteriorating credits), the benefits yields, and the major challenges and barriers encountered.

IIF Authors

Brad Carr

Brad
Carr
Senior Director, Digital Finance Regulation and Policy
+1-202-857-3648
bcarr@iif.com

Natalia Bailey

Natalia
Bailey
Associate Policy Advisor
+1-202-682-7440
nbailey@iif.com

Michael Kueker

Michael
Kueker
Associate Policy Advisor
+1 202 682-7454
mkueker@iif.com

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