Using AI and Behavioral Finance to Cope with Limited Attention and Reduce Overdraft Fees

References

• Agarwal A, Dudík M, Kale S, Langford J, Schapire R (2012) Contextual bandit learning with predictable rewards. Lawrence N, Girolami M, eds. Proc. 15th Internat. Conf. Artificial Intelligence Statist. (PMLR, New York), 19–26.Google Scholar
• Alan S, Cemalcilar M, Karlan D, Zinman J (2018) Unshrouding: Evidence from bank overdrafts in Turkey. J. Finance 73(2):481–522.Crossref, Google Scholar
• Allen L, Shan Y, Tang Y, Yildirim A (2021) Cutting operational costs by integrating fintech into traditional banking firms. Preprint, submitted January 8, https://dx.doi.org/10.2139/ssrn.3703840.Google Scholar
• Amorim LD, Cai J (2015) Modelling recurrent events: A tutorial for analysis in epidemiology. Internat. J. Epidemiology 44(1):324–333.Crossref, Google Scholar
• Andries M, Haddad V (2019) Information aversion. J. Political Econom. 128(5):1901–1939.Crossref, Google Scholar
• Ashraf N, Karlan DS, Yin W (2006) Household decision making and savings impacts: Further evidence from a commitment savings product in the Philippines. Preprint, submitted June 30, https://dx.doi.org/10.2139/ssrn.912771.Google Scholar
• Babar Y, Curley S, Ke Z, Liu D, Sheffler Z (2023) The effects of digitally delivered nudges in a corporate wellness program. J. Assoc. Inform. Systems 24(1):136–160.Google Scholar
• Baker SR (2018) Debt and the response to household income shocks: Validation and application of linked financial account data. J. Political Econom. 126(4):1504–1557.Google Scholar
• Beketov M, Lehmann K, Wittke M (2018) Robo advisors: Quantitative methods inside the robots. J. Asset Management 19(6):363–370.Crossref, Google Scholar
• Benartzi S, Lehrer J (2015) The Smarter Screen: What Your Business Can Learn from the Way Consumers Think Online (Hachette UK, London).Google Scholar
• Bietti A, Agarwal A, Langford J (2018) A contextual bandit bake-off. Preprint, submitted February 12, https://arxiv.org/abs/1802.04064.Google Scholar
• Bhargava S, Manoli D (2015) Psychological frictions and the incomplete take-up of social benefits: Evidence from an IRS field experiment. Amer. Econom. Rev. 105(11):3489–3529.Google Scholar
• Block LG, Keller PA (1995) When to accentuate the negative: The effects of perceived efficacy and message framing on intentions to perform a health-related behavior. J. Marketing Res. 32(2):192–203.Crossref, Google Scholar
• Bossaerts P, Yadav N, Murawski C (2019) Uncertainty and computational complexity. Philos. Trans. Roy. Soc. B Biol. Sci. 374(1766):20180138.Crossref, Google Scholar
• Bracha A, Meier S (2015) Nudging credit scores in the field: The effect of text reminders on creditworthiness in the United States. Preprint, submitted October 19, https://dx.doi.org/10.2139/ssrn.2675695.Google Scholar
• Briganti G, Le Moine O (2020) Artificial intelligence in medicine: Today and tomorrow. Frontiers Medicine 7:27.Crossref, Google Scholar
• Bu D, Hanspal T, Liao Y, Liu Y (2020) Cultivating self-control in fintech: Evidence from a field experiment on online consumer borrowing. Preprint, submitted October 24, 2019, https://dx.doi.org/10.2139/ssrn.3469571.Google Scholar
• Bursztyn L, Fiorin S, Gottlieb D, Kanz M (2018) Moral incentives in credit card debt repayment: Evidence from a field experiment. J. Political Econom. 127(4):1641–1683.Crossref, Google Scholar
• Calzolari G, Nardotto M (2017) Effective reminders. Management Sci. 63(9):2915–2932.Link, Google Scholar
• Caplin A (2016) Measuring and modeling attention. Annual Rev. Econom. 8(1):379–403.Google Scholar
• Chetty R, Looney A, Kroft K (2009) Salience and taxation: Theory and evidence. Amer. Econom. Rev. 99(4):1145–1177.Crossref, Google Scholar
• Consumer Financial Protection Bureau (2017) A closer look: Overdraft and the impact of opting-in. https://files.consumerfinance.gov/f/documents/201701_cfpb_Overdraft-and-Impact-of-Opting-In.pdf.Google Scholar
• Cowan N, Johnson TD, Scott Saults J (2005) Capacity limits in list item recognition: Evidence from proactive interference. Memory 13(3–4):293–299.Crossref, Google Scholar
• Crockett S, Duffy J, Izhakian Y (2019) An experimental test of the Lucas asset pricing model. Rev. Econom. Stud. 86(2):627–667.Crossref, Google Scholar
• D’Acunto F, Prabhala N, Rossi AG (2019) The promises and pitfalls of robo-advising. Rev. Futures Markets 32(5):1983–2020.Google Scholar
• DellaVigna S (2009) Psychology and economics: Evidence from the field. J. Econom. Literature 47(2):315–372.Crossref, Google Scholar
• DellaVigna S, Linos E (2020) RCTs to scale: Comprehensive evidence from two nudge units. NBER Working Paper No. 27594, National Bureau of Economic Research, Cambridge, MA.Google Scholar
• Fisch JE, Turner JA, Center PP (2017) Robo advisers vs. humans: Which make the better financial advisers? Preprint, submitted March 17, https://doi.org/10.2139/ssrn.2932189.Google Scholar
• Franco JP, Yadav N, Bossaerts P, Murawski C (2018) Where the really hard choices are: A general framework to quantify decision difficulty. Animal Behav. Cognition 5(3):223–242.Google Scholar
• Gabaix X (2017) Behavioral Inattention (National Bureau of Economic Research, Cambridge, MA).Crossref, Google Scholar
• Gabaix X, Laibson D, Moloche G, Weinberg S (2006) Costly information acquisition: Experimental analysis of a boundedly rational model. Amer. Econom. Rev. 96(4):1043–1068.Crossref, Google Scholar
• Galai D, Sade O (2006) The “ostrich effect” and the relationship between the liquidity and the yields of financial assets. J. Bus. 79(5):2741–2759.Crossref, Google Scholar
• Ghose A, Guo X, Li B, Dang Y (2021) Empowering patients using smart mobile health platforms: Evidence from a randomized field experiment. Preprint, submitted February 10, https://arxiv.org/abs/2102.05506.Google Scholar
• Ghose A, Kwon HE, Lee D, Oh W (2019) Seizing the commuting moment: Contextual targeting based on mobile transportation apps. Inform. Systems Res. 30(1):154–174.Link, Google Scholar
• Goodman JK, Cryder CE, Cheema A (2013) Data collection in a flat world: The strengths and weaknesses of Mechanical Turk samples. J. Behav. Decision Making 26(3):213–224.Crossref, Google Scholar
• Grubb MD, Kelly D, Nieboer J, Osborne M, Shaw J (2025) Sending out an SMS: Automatic enrollment experiments for overdraft alerts. J. Finance 80(1):467–514.Google Scholar
• Haran Rosen M, Sade O (2022) Investigating the introduction of a regulatory fintech advancement designed to reduce limited attention regarding inactive saving accounts—Data, survey, and field experiment AEA Papers Proc. 112:370–375.Google Scholar
• Hirshleifer D, Teoh SH (2003) Limited attention, information disclosure, and financial reporting. J. Accounting Econom. 36(1):337–386.Crossref, Google Scholar
• Iyer LS (2021) AI enabled applications towards intelligent transportation. Transportation Engrg. 5:100083.Crossref, Google Scholar
• Karlan D, McConnell M, Mullainathan S, Zinman J (2016) Getting to the top of mind: How reminders increase saving. Management Sci. 62(12):3393–3411.Link, Google Scholar
• Kőszegi B, Rabin M (2009) Reference-dependent consumption plans. Amer. Econom. Rev. 99(3):909–936.Crossref, Google Scholar
• Kretzer M, Maedche A (2018) Designing social nudges for enterprise recommendation agents: An investigation in the business intelligence systems context. J. Assoc. Inform. Systems 19(12).Google Scholar
• L’Esperance M (2023) Nudging credit union members to check their credit: Evidence from a field experiment. J. Behav. Experiment. Finance 37:100775.Crossref, Google Scholar
• Levin IP, Gaeth GJ (1988) How consumers are affected by the framing of attribute information before and after consuming the product. J. Consumer Res. 15(3):374–378.Crossref, Google Scholar
• Levin IP, Schneider SL, Gaeth GJ (1998) All frames are not created equal: A typology and critical analysis of framing effects. Organ. Behav. Human Decision Processes 76(2):149–188.Crossref, Google Scholar
• Lindgaard G, Fernandes G, Dudek C, Brown J (2006) Attention web designers: You have 50 milliseconds to make a good first impression! Behav. Inform. Tech. 25(2):115–126.Crossref, Google Scholar
• Liu J, KC D (2023) Nudging patient choice: Reducing no-shows using waits framing messaging. Oper. Res. 71(3):1004–1020.Link, Google Scholar
• Mani A, Mullainathan S, Shafir E, Zhao J (2013) Poverty impedes cognitive function. Science 341(6149):976–980.Crossref, Google Scholar
• Massa M, Simonov A (2005) Behavioral biases and investment. Rev. Finance 9(4):483–507.Crossref, Google Scholar
• Medina PC (2017) Selective attention in consumer finance: Evidence from a randomized intervention in the credit card market. Working paper, Northwestern University, Evanston, IL.Google Scholar
• Melzer BT, Morgan DP (2015) Competition in a consumer loan market: Payday loans and overdraft credit. J. Financial Intermediation 24(1):25–44.Crossref, Google Scholar
• Mintel (2015) Consumers and financial advice – UK – 2015: Consumer market research report. Mintel Group Ltd. https://www.mintel.com.Google Scholar
• Mintz I, Hayman L, Mishraky E (2021) Insufficient funds predictor. U.S. Patent No. 11,042,930. U.S. Patent and Trademark Office.Google Scholar
• Moebs Services (2017) Services and products. http://www.moebs.com/services/nobounce.Google Scholar
• Ofir M, Wiener Z (2012) Investment in financial structured products from rational and behavioral choice perspectives. Preprint, submitted December 23, https://dx.doi.org/10.2139/ssrn.2193282.Google Scholar
• Olafsson A, Pagel M (2017) The ostrich in US: Selective attention to financial accounts, income, spending, and liquidity. NBER Working Paper No. 23945, National Bureau of Economic Research, Cambridge, MA.Google Scholar
• Prentice RL, Williams BJ, Peterson AV (1981) On the regression analysis of multivariate failure time data. Biometrika 68(2):373–379.Crossref, Google Scholar
• Shefrin H (2021) Financial service providers, AI, satisficing, and the human touch in the market for financial nudges and boosts. Preprint, submitted March 18, https://dx.doi.org/10.2139/ssrn.3779635.Google Scholar
• Sims CA (2010) Rational inattention and monetary economics. Friedman BM, Woodford M, eds. Handbook of Monetary Economics, vol. 3 (Elsevier, Amsterdam), 155–181.Google Scholar
• Sleeman D, Langley P, Mitchell TM (1982) Learning from solution paths: An approach to the credit assignment problem. AI Magazine 3(2):2.Google Scholar
• Stango V, Zinman J (2014) Limited and varying consumer attention: Evidence from shocks to the salience of bank overdraft fees. Rev. Financial Stud. 27(4):990–1030.Crossref, Google Scholar
• Thirumalai S, Sinha KK (2013) To personalize or not to personalize online purchase interactions: Implications of self-selection by retailers. Inform. Systems Res. 24(3):683–708.Link, Google Scholar
• Tuch AN, Bargas-Avila JA, Opwis K (2010) Symmetry and aesthetics in website design: It’s a man’s business. Comput. Human Behav. 26(6):1831–1837.Crossref, Google Scholar
• Tversky A, Kahneman D (1981) The framing of decisions and the psychology of choice. Science 211(4481):453–458.Crossref, Google Scholar
• Wang Y, Lu LX, Shi P (2022) Does customer email engagement improve profitability? Evidence from a field experiment in subscription service retailing. Manufacturing Service Oper. Management 24(5):2703–2721.Link, Google Scholar
• Yang J, Eckles D, Dhillon P, Aral S (2020) Targeting for long-term outcomes. Preprint, submitted October 29, https://arxiv.org/abs/2010.15835.Google Scholar