MSUFCU and automated decisioning

This summary outlines important research findings that help lenders drive a more inclusive environment for customers, while mitigating risk.

A few takeaways:

• Understanding the profiles of who’s more prone to exclusion informs risk management.
• Machine learning techniques can also be deployed to help detect economic interaction effects or shifts.
• Attributes like education level, occupation or rent/utilities payment history have predictive power in credit outcomes.

Join Ashley Knight, Experian’s SVP of Product Management, and Haiyan Huang, Prosper’s Chief Credit Officer, to discover how:

• Alternative finance data is redefining how to verify and connect identities.
• Email and phone intelligence is unlocking new levels of precision in credit marketing.
• Open banking insights are becoming increasingly critical for financial inclusion and mitigating risk.

Read the latest findings about "Closing the credit gap" white paper, and what they mean for financial inclusion and risk management.

Key insights:

• Income and credit trends reveal significant disparities that impact access to financial products.
• Demographic shifts across gender, household structures, ethnicities, and generations are reshaping borrower profiles.
• Lenders who adapt their strategies and product offerings can expand their customer base, reduce default rates, and lead in inclusive finance.

Improve your credit risk decisions with advanced approaches to validating and optimizing decision trees. Learn how stronger models drive smarter, more consistent outcomes across your portfolio.

• Enhance model accuracy
• Strengthen underwriting and collections
• Improve decision speed and consistency
• Align data science and risk teams