Sponsors
The bill directs a joint CFPB–FTC study of alternative financial data for credit scoring that could expand access and provide regulatory clarity, but it also raises substantial privacy, discrimination, and consumer-cost risks if safeguards and careful model design are not implemented.
Thin-file, unbanked, and other credit-invisible consumers could gain fairer access to credit if the CFPB–FTC study finds that alternative data (rental, utility, payroll, BNPL, P2P) meaningfully improves credit assessments.
Consumers (especially low-income households) could receive stronger privacy protections if the study identifies risks from using sensitive data (EBT, payroll deposits, brokerage statements) and regulators act on those findings.
Regulators and industry would get clearer, evidence-based guidance because a joint CFPB–FTC report can increase transparency around credit scoring practices and help shape consistent rules or best practices.
All consumers face increased privacy and data-security risks because the study requires collecting and analyzing broad transaction and P2P data, which could be exposed or misused if not paired with strict safeguards.
Low-income and benefit-receiving individuals could be harmed if examining EBT, payroll, or other sensitive income data normalizes their inclusion in credit scoring, increasing the risk of discrimination or exclusion from credit.
Some borrowers (including middle-class and low-income families) could face higher borrowing costs if alternative-data models misinterpret nontraditional cash flows and label otherwise stable consumers as higher risk.
Based on analysis of 2 sections of legislative text.
Requires CFPB and FTC to report by Dec 31, 2025 on credit‑scoring models that use specified alternative 'key factors' and their effect on creditor creditworthiness evaluations.
Introduced September 2, 2025 by Cleo Fields · Last progress September 2, 2025
Directs the Consumer Financial Protection Bureau Director and the Federal Trade Commission Chair to jointly deliver a report to Congress by December 31, 2025 that studies the use of credit scoring models that rely on a set of specified "key factors" and assesses how those models influence creditor decisions about consumer creditworthiness. The measure defines which models and "key factors" are in scope by referencing existing federal definitions and lists multiple alternative data types—such as rental and utility payments, buy‑now‑pay‑later histories, EBT records, payroll deposits, insurance payments, public records, peer‑to‑peer activity, and depository transaction data—for review.