Algorithms in Household Finance

This working group will explore the growing role of algorithms and artificial intelligence in household finance — an area of economics that studies how people save, borrow, invest, and use financial products to manage their well-being.

Advances in machine learning and automated decision-making are transforming how financial services are designed, priced, and delivered. These changes raise important questions about efficiency, fairness, consumer welfare, and regulation. Our aim is to bring together researchers and practitioners interested in understanding these developments and their implications.

Format #

We will begin as a reading group, meeting regularly to discuss recent academic papers and key research directions in the field. The initial sessions will focus on influential studies at the intersection of AI, algorithms, and household finance, such as:

• Greig, Fiona, Tarun Ramadorai, Alberto G. Rossi, Stephen P. Utkus, and Ansgar Walther. Human Financial Advice in the Age of Automation. SSRN (2024).
• Fuster, Andreas, Paul Goldsmith‐Pinkham, Tarun Ramadorai, and Ansgar Walther. Predictably Unequal? The Effects of Machine Learning on Credit Markets. Journal of Finance, 77(1), 5–47 (2022).

Future meetings may also include invited talks, collaborative research discussions, or policy-focused workshops depending on the group’s interests.

Working Group Organizer #