Best practices for fusing internal and external data to enhance credit decisioning for SMB lending with Stripe’s Yaakov Erlichman
- Learn strategic and tactical best practices for maximizing the fusion of internal and external data to enhance credit decisioning and risk management for SMB lending.
- Stripe's Yaakov Ehrlichman, head of capital and SMB risk, covers both conceptual and implementation considerations for reconciling data sources tailored to the unique needs of the SMB market.
As a part of Tearsheet’ Talks: Lending x Credit x Data, Stripe’s Yaakov Erlichman, Head of Capital and Small Business Risk, provides a practical framework for integrating proprietary and third-party data sources in small and medium business lending to drive effective underwriting. He discusses recommendations for sequencing data introduction, balancing model predictive power with applicant friction reduction, optimizing the mix of internal and external data, and managing model degradation.
Yaakov is a seasoned risk management professionalresponsible for leading the credit strategy at Stripe. He joined the company four years ago to build out the risk infrastructure for Stripe Capital. Prior to Stripe, Yaakov was part of the risk teams at Kabbage and American Express.
Learn strategic and tactical best practices for maximizing the fusion of internal and external data to enhance credit decisioning and risk management for SMB lending. The session covers both conceptual and implementation considerations for reconciling data sources tailored to the unique needs of the SMB market.
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