Projects
Agentic AI in Financial Services
FinRegLab is tracking the spread of agentic AI in financial services and e-commerce. These dynamic AI systems can be structured to respond to new information and make and execute decisions without ongoing human engagement.
This market scan report traces the adoption of agentic AI systems in financial services and e-commerce, identifying critical questions about how to tap its benefits while mitigating risks to consumers, financial services providers, and the broader economy.
This empirical white paper assesses the impacts on model predictiveness and credit access of both adopting machine learning techniques and incorporating electronic bank account information (often called cash flow data) in consumer underwriting models.
This report details the experiences of mission-based lenders such as community development financial institutions (CDFIs) and minority depository institutions (MDIs) as they adopt electronic bank account data and lending platforms to increase lending to minority-owned businesses and other underserved entrepreneurs. The paper provides both a practical snapshot of how lenders manage data and technology adoption today and a broader analysis of issues that will shape their ability to serve substantially larger numbers of entrepreneurs going forward.
This empirical paper analyzes the impacts on predictive accuracy and credit access of incorporating electronic cash-flow data into small business underwriting models using data from two fintech lenders that lend to a broad spectrum of customers.
The Future We Make: Leveraging AI in Financial Services” contains four themes and nine key insights from the AI Symposium 2024. The goal of this report is to highlight some of the key messages, ideas, and examples that were discussed throughout the Symposium.
This report examines how modernizing federal insurance programs for manufactured home loans can expand affordable housing access. Modern manufactured housing is high quality, but financing for certain loan types is limited due to outdated processes and inconsistent rules. Recommendations include automating underwriting, harmonizing loan requirements, and improving data access to attract more lenders and support underserved communities.
FinRegLab is assessing the potential value of conducting empirical tests and other research to analyze particular data and technology solutions for identity proofing and transaction monitoring to improve financial inclusion and combat bad actors.
This landscape paper details gaps in traditional systems that both make it difficult for millions of consumers to access financial services and for financial institutions to detect and protect against bad actors.
This report delves into the evolving landscape of small business lending following the pandemic, identifying significant trends that are shaping the lending ecosystem. As the economy improves, lenders will face critical decisions about how to meet the capital needs of more small businesses, including record numbers of minority- and women-owned startups since 2020.