JOURNAL ARTICLE
Using AI and Behavioral Finance to Cope with Limited Attention and Reduce Overdraft Fees.
Published In: Management Science (INFORMS), 2026, v. 72, n. 1. P. 204 1 of 3
Database: Business Source Ultimate 2 of 3
Authored By: Ben-David, Daniel; Mintz, Ido; Sade, Orly 3 of 3
Abstract
This article examines the effectiveness of an artificial intelligence (AI)–based human–algorithm interaction designed to reduce overdraft and nonsufficient fund (NSF) fees among users of Mint, a large personal financial management platform in the United States and Canada. Through a randomized field experiment involving 39,607 users, the study finds that sending as-needed email reminders significantly reduces overdraft fees, with simpler and negatively framed messages proving more effective than more complex or positively framed ones. The intervention was most effective for users with medium to high incomes and fair to good credit scores, while those facing greater financial hardship showed less responsiveness, indicating that AI reminders alone may not suffice to overcome financial constraints. The research contributes to understanding AI-based financial advising, human–computer interaction, and behavioral finance by highlighting the role of message design and user characteristics in influencing financial behavior.
Additional Information
- Source:Management Science (INFORMS). 2026/01, Vol. 72, Issue 1, p204
- Document Type:Article
- Subject Area:Business and Management
- Publication Date:2026
- ISSN:0025-1909
- DOI:10.1287/mnsc.2022.00304
- Accession Number:190748645
- Copyright Statement:Copyright of Management Science (INFORMS) is the property of INFORMS: Institute for Operations Research & the Management Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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