Expanding Credit Access through Cash Flow Underwriting and Machine Learning
Traditional credit scoring models often fail to capture the true creditworthiness of millions, particularly underserved MSMEs and individuals who have thin credit files or lack of formal history. Utilizing real-time cash flow data -using real-time checking, savings, and transaction data – offers a more holistic view of a borrower’s financial health. Leveraging machine learning (ML) helps identify risk patterns that traditional linear models overlook, significantly expanding access without compromising institutional safety. This evolution represents a critical junction where technological innovation meets regulatory necessity, offering a scalable pathway to reduce the credit gap and foster a more equitable financial ecosystem.
Join this webinar to explore:
- Efficacy of cash flow data in credit underwriting.
- Findings from the latest empirical research by FinRegLab: “Advancing the Credit Ecosystem: Machine Learning & Cash Flow Data in Consumer Underwriting.”
- ML governance including explainability, accountability, transparency and oversight requirements for regulatory supervisory authority.
- Intersection of consumer protection and data protection.
- Opportunities of market scale driven by collaborations.
To register click here.
