Applying AI to Automate Credit Decisions at Facebook
Managing credit limits for Facebook’s advertisers requires thousands of credit decisions annually. We built a machine learning solution to help automate credit decisions. It uses gradient boosted decision trees to predict whether an account’s invoices will become bad debt with 92.4% ROC-AUC. This enabled Facebook to reduce manual credit decision volume by 62% while avoiding revenue loss resulting from accounts reaching their credit limits.
David Chi is an Operations Research Scientist in Facebook's Enterprise Engineering organization. He works machine learning and artifical intelligence for internal applications built for finance, supply chain, and compliance. He holds a bachelor's degree in engineering from UC Berkeley and a Ph.D. in engineering from Stanford University.