News & Events

FinRegLab Report Finds Non-Conventional Data Sources Are Critical to Expanding Credit Access and Growth Among Kenyan Micro and Small Enterprises

A new report by FinRegLab details strategies for improving data sources for credit scoring and underwriting of Kenyan micro and small enterprises (MSEs), finding that tapping multiple non-conventional (or alternative) data sources is particularly important to expanding credit access and growth among women-owned MSEs.

March 28, 2024

FinRegLab Responds to Treasury Request for Information on Financial Inclusion Strategy

We therefore urge that a national inclusion strategy reflect the importance of data and technology in impacting financial inclusion, fairness, and equity in
today’s rapidly changing environment.

February 20, 2024

FinRegLab Responds to the CFPB’s Proposed Rule on Personal Financial Data Rights

Over the past three decades, customer-permissioned data flows have become critical to a growing range of consumer financial products and services as well as to public research focusing on household financial health, markets for consumer financial products and services, and the role of consumer financial activity in the nation’s economy.

December 29, 2023

FinRegLab Report and Webinar Examine the Policy Implications of AI in Financial Services as Adoption Continues to Accelerate in Credit Underwriting and Other Use Cases

FinRegLab is extending its investigation of the adoption of artificial intelligence in financial services through a policy analysis focused on the growing use of machine learning models for underwriting credit and a January 17 webinar with senior federal financial regulators to discuss generative AI and other recent developments.

December 7, 2023

FinRegLab Testimony: Senate Committee on Banking, Housing, and Urban Affairs “Artificial Intelligence in Financial Services”

FinRegLab’s testimony provides a general overview of the state of ML/AI adoption across various financial services use cases; potential benefits and risks to customers, providers, and the broader economy; and the ways that federal financial regulatory frameworks are shaping ML/AI adoption in this sector.

September 19, 2023

FinRegLab to Evaluate Data to Increase Credit Access for Minority Business Enterprises and to Scale Lending by Mission-based Lenders

FinRegLab is launching an initiative with support from the U.S. Department of Commerce Minority Business Development Agency (MBDA) to improve credit access for minority-owned companies and other underserved small businesses through the use of non-traditional data sources and mission-based lenders.

September 7, 2023

Events & Conferences

We are planning on attending or speaking at the following upcoming webinars, events and conferences:

Credit Builders Alliance Symposium

June 6, 2024 Credit Builders Alliance

Project REACh Summit

May 29-30, 2024 Office of the Comptroller of the Currency

BIS Innovation Summit

May 6-7, 2024 Bank for International Settlements

FinRegLab in the News

Don’t take our word for it – here’s what people are saying:

Consumer AI Underwriting and Explainability with Melissa Koide

Orrick Herrington & Sutcliffe LLP
October 4, 2023
Jerry Buckley and Caroline Stapleton

“Melissa discusses her organization’s work in evaluating the explainability of complex machine learning algorithms in credit underwriting, model governance and adverse action notices. The conversation covers the CFPB’s recent guidance on credit denial by lenders using artificial intelligence as well as the role explainability plays in promoting fairness and inclusion in lending, methods and tools emerging for lenders to explain credit-related decisions based on AI models, and the ongoing work required to adapt to the digital economy and evolving regulatory landscape.”

Consumer Reports Launches Video Series in Partnership with Kapor
Foundation Highlighting Racial Bias in Algorithms

Consumer Reports
May 2, 2023

Consumer Reports released a video series exploring biases in machine learning algorithms and data sets and the resulting unfair practices faced by communities of color. The series is designed to educate consumers on the risks hidden in seemingly “neutral” technologies. FinRegLab CEO Melissa Koide is featured in the Mortgage Lending episode of the series.

The Credit Scoring System has its Downsides — Here’s What a New Credit Scoring and Reporting System Could Look Like

CNBC
Jan 31, 2023
Trina Paul

“Credit underwriting with cash-flow data involves using financial data insights from a bank account or other types of transaction accounts to evaluate consumers and small businesses for credit,”

Tackle the ‘credit invisibles’ to help close the racial wealth gap

Financial Times
November 28, 2022
Patti Waldmeir

“Some fintechs think including more data and analyzing it with more advanced algorithms could solve the problem. Others say it’s time to build whole new systems.”

New Treasury Report Shows Fintech Industry Requires Additional Oversight to Close Gaps, Prevent Abuses and Protect Consumers

U.S. Department of the Treasury November 16, 2022

“The report finds that, while concentration among federally insured banks is growing, new entrant non-bank firms, in particular ‘fintech’ firms, are adding significantly to the number of firms and business models competing in core consumer finance markets and appear to be contributing to competitive pressure. While these fintech firms are enabling new capabilities, they are also creating new risks to consumer protection and market integrity, such as risks related to data privacy and regulatory arbitrage.”

Should we trust the credit decisions provided by machine learning models?

SUERF
September 2022
Andrés Alonso and José Manuel Carbó

“The use of Machine Learning (ML) models is gaining traction in finance due to their better predictive capacity compared to traditional statistical techniques…One of the use cases with greater potential is its application to credit underwriting and scoring, since by having better predictive capacity, ML models allow better estimates of the probability of default and therefore could result in more accurate credit scores. But this improvement in predictive performance does not come without risk.”

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