Current societal challenges related to retirement planning, healthcare systems’ evolution and environmental changes require households to pay a closer attention to their personal finances. This in turns calls for the associated industry to transform and scale. To do so, the personal finance industry could potentially leverage artificial intelligence tools for which there has been increasing levels of chatter. However, there is, to my knowledge, little consensus on whether or not those tools are appropriate given the challenges ahead. The literature review at the heart of this article first suggests that the stream of personal finance where transformation is more than needed is the one pertaining to investments, rather than the ones associated to loans, insurances or payments. Second, the productivity levers fueling the transformation of this branch are yet more driven, as of today, by simple digitalization notions rather by the usage of A.I. instruments. Over the next couple of years, more attention should thus be paid to use/business cases associated to investment products and the digitalization of their distribution chain.
Ribes, E. A. Transforming personal finance thanks to artificial intelligence: myth or reality?. Financial Economics Letters, 2023, 2, 7. https://doi.org/10.58567/fel02010002
Ribes E A. Transforming personal finance thanks to artificial intelligence: myth or reality?. Financial Economics Letters; 2023, 2(1):7. https://doi.org/10.58567/fel02010002
Ribes, Edouard A. 2023. "Transforming personal finance thanks to artificial intelligence: myth or reality?" Financial Economics Letters 2, no.1: 7. https://doi.org/10.58567/fel02010002
Ribes, E. A. (2023). Transforming personal finance thanks to artificial intelligence: myth or reality?. Financial Economics Letters, 2(1), 7. https://doi.org/10.58567/fel02010002
Article Access Statistics
Accenture. (2020). Accenture 2020 fintech report by cb insights (Tech. Rep.). Author. Retrieved from https://newsroom.accenture.com/news/fintech-fundraising-grew-strongly-in-most-major-markets-in-2019-accenture-analysis-finds.html
Acemoglu, D., & Restrepo, P. (2022). Tasks, automation, and the rise in us wage inequality. Econometrica, 90(5), 1973–2016.
Agarwal, S., & Zhang, J. (2020). Fintech, lending and payment innovation: A review. Asia-Pacific Journal of Financial Studies, 49(3), 353–367.
Ando, A., & Modigliani, F. (1963). The” life cycle” hypothesis of saving: Aggregate implications and tests. The American economic review, 53(1), 55–84.
Balasubramanian, R., Libarikian, A., & McElhaney, D. (2018). Insurance 2030—the impact of ai on the future of insurance. McKinsey & Company.
Bazot, G. (2018). Financial consumption and the cost of finance: Measuring financial efficiency in europe (1950–2007). Journal of the European Economic Association, 16(1), 123–160.
Berchick, E. R., Hood, E., & Barnett, J. C. (2019). Health insurance coverage in the united states: 2018. Washington, DC: US Department of Commerce.
Berg, T., Fuster, A., & Puri, M. (2022). Fintech lending. Annual Review of Financial Economics, 14, 187–207.
Bernheim, B. D., Shleifer, A., & Summers, L. H. (1986). The strategic bequest motive. Journal of labor Economics, 4(3, Part 2), S151–S182.
Bl¨ondal, S., & Scarpetta, S. (1999). The retirement decision in oecd countries.
Boobier, T. (2016). Analytics for insurance: The real business of big data. John Wiley & Sons.
Cagetti, M. (2003). Wealth accumulation over the life cycle and precautionary savings. Journal of Business & Economic Statistics, 21(3), 339–353.
Callen, M. T., & Thimann, M. C. (1997). Empirical determinants of household saving: Evidence from oecd countries. International Monetary Fund.
Campbell, J. Y. (2006). Household finance. The journal of finance, 61(4), 1553–1604.
Cao, L. (2020). Ai in finance: A review. Available at SSRN 3647625.
Cao, L. (2022). Ai in finance: challenges, techniques, and opportunities. ACM Computing Surveys (CSUR), 55(3), 1–38.
Chatterjee, S., & Grable, J. E. (2022a). 34 the future of personal finance: An educational and research agenda. De Gruyter Handbook of Personal Finance, 599.
Chatterjee, S., & Grable, J. E. (2022b). 34 the future of personal finance: An educational and research agenda. De Gruyter Handbook of Personal Finance, 599–612.
Collardi, B. F. (2012). Private banking: Building a culture of excellence. John Wiley & Sons.
Cull, M. (2022). 30 the growing role of fintech and robo-advisors. De Gruyter Handbook of Personal Finance, 529.
Dedehayir, O., & Steinert, M. (2016). The hype cycle model: A review and future directions. Technological Forecasting and Social Change, 108, 28–41.
Dhieb, N., Ghazzai, H., Besbes, H., & Massoud, Y. (2020). A secure ai-driven architecture for automated insurance systems: Fraud detection and risk measurement. IEEE Access, 8, 58546–58558.
Dobrescu, L. I. (2015). To love or to pay savings and health care in older age. Journal of Human Resources, 50(1), 254–299.
EBA. (2017). Discussion paper on the eba’s approach to financial technology (fintech). European Banking Authority, EBA.
Eletter, S. F., Yaseen, S. G., & Elrefae, G. A. (2010). Neuro-based artificial intelligence model for loan decisions. American Journal of Economics and Business Administration, 2(1), 27.
Fanti, L., & Gori, L. (2012). Fertility and payg pensions in the overlapping generations model. Journal of Population Economics, 25(3), 955–961.
Fanti, L., et al. (2015). Growth, payg pension systems crisis and mandatory age of retirement. Economics Bulletin, 35(2), 1160–1167.
Fitz, S., & Romero, P. (2021). Neural networks and deep learning: A paradigm shift in information processing, machine learning, and artificial intelligence. The Palgrave Handbook of Technological Finance, 589–654.
Foerster, S., Linnainmaa, J. T., Melzer, B. T., & Previtero, A. (2017). Retail financial advice: does one size fit all? The Journal of Finance, 72(4), 1441–1482.
Gai, K., Qiu, M., & Sun, X. (2018). A survey on fintech. Journal of Network and Computer Applications, 103, 262–273.
Goodell, J. W., Kumar, S., Lim, W. M., & Pattnaik, D. (2021). Artificial intelligence and machine learning in finance: Identifying foundations, themes, and research clusters from bibliometric analysis. Journal of Behavioral and Experimental Finance, 32, 100577.
Goos, M., Manning, A., & Salomons, A. (2014). Explaining job polarization: Routine-biased technological change and offshoring. American economic review, 104(8), 2509–2526.
Grable, J. E., & Chatterjee, S. (2022). De gruyter handbook of personal finance. Walter de Gruyter
Grable, J. E., & Kruger, M. (2022). 19 the role of insurance as a household financial management tool. De Gruyter Handbook of Personal Finance, 2, 307.
Grossman, G. M., & Rossi-Hansberg, E. (2008). Trading tasks: A simple theory of offshoring. American Economic Review, 98(5), 1978–97.
Hentzen, J. K., Hoffmann, A., Dolan, R., & Pala, E. (2022). Artificial intelligence in customer-facing financial services: a systematic literature review and agenda for future research. International Journal of Bank Marketing, 40(6), 1299–1336.
Hu¨fner, F., & Koske, I. (2010). Explaining household saving rates in g7 countries: implications for germany.
Huggett, M., & Ventura, G. (2000). Understanding why high income households save more than low income households. Journal of Monetary Economics, 45(2), 361–397.
Ibbotson, R., Xiong, J., Kreitler, R. P., Kreitler, C. F., & Chen, P. (2007). National savings rate guidelines for individuals. Journal of Financial Planning, 20(4), 50–61.
K¨onigstorfer, F., & Thalmann, S. (2020). Applications of artificial intelligence in commercial banks–a research agenda for behavioral finance. Journal of behavioral and experimental finance, 27, 100352. Lasry, J.-M., & Lions, P.-L. (2007). Mean field games. Japanese journal of mathematics, 2(1), 229–260.
Kessler, D., Perelman, S., & Pestieau, P. (1993). Savings behavior in 17 oecd countries. Review of Income and Wealth, 39(1), 37–49.
King, M. R., Timms, P. D., & Rubin, T. H. (2021). Use of big data in insurance. The Palgrave Handbook of Technological Finance, 669–700.
Knewtson, H. S., & Rosenbaum, Z. A. (2020). Toward understanding fintech and its industry. Managerial Finance, 46(8), 1043–1060.
Linden, A., & Fenn, J. (2003). Understanding gartner’s hype cycles. Strategic Analysis Report Nº R-20-1971. Gartner, Inc, 88, 1423.
Masson, A., & Pestieau, P. (1997). Bequests motives and models of inheritance: a survey of the literature. Is inheritance legitimate?, 54–88.
Matthews, C. (2022). 32 the future of payments: Cash, cryptocurrencies, and peer-to-peer payments. De Gruyter Handbook of Personal Finance, 569.
Maude, D. (2010). Global private banking and wealth management: the new realities (Vol. 610). John Wiley & Sons.
Milana, C., & Ashta, A. (2021). Artificial intelligence techniques in finance and financial markets: a survey of the literature. Strategic Change, 30(3), 189–209.
Morik, K., & K¨opcke, H. (2004). Analysing customer churn in insurance data–a case study. In Knowledge discovery in databases: Pkdd 2004: 8th european conference on principles and practice of knowledge discovery in databases, pisa, italy, september 20-24, 2004. proceedings 8 (pp. 325–336).
Mutual, N. (2017). Planning & progress study 2016.
Navaretti, G. B., Calzolari, G., Mansilla-Fernandez, J. M., & Pozzolo, A. F. (2018). Fintech and banking. friends or foes? Friends or Foes.
OCDE. (2022). Health at a glance: Europe 2022. Retrieved from https://www.oecd-ilibrary.org/ content/publication/507433b0-en DOI: https://doi.org/https://doi.org/10.1787/507433b0-en
OECD. (2021). Pensions at a glance 2021: Oecd and g20 indicators. Organisation for Economic Cooperation and Development OECD.
Oldenski, L. (2014). Offshoring and the polarization of the us labor market. ILR Review, 67(3 suppl), 734–761.
Opati, T. Z. (2020). Employing artificial intelligence and algorithms in the digital lending industry: Measuring and managing risky consumer behaviour. In Impact of mobile payment applications and transfers on business (pp. 43–70). IGI Global.
Philippon, T. (2016). The fintech opportunity (Tech. Rep.). National Bureau of Economic Research.
Philippon, T. (2022). Harnessing the promise of fintech. Shifting Paradigms: Growth, Finance, Jobs, and Inequality in the Digital Economy, 95.
Polansky, S., Chandler, P., & Mottola, G. R. (2019). The big spenddown: Digital investment. The Disruptive Impact of FinTech on Retirement Systems, 129.
Ribes, E. (2021). How does education influence individuals’ use of bequests as a long-term care insurance? (Unpublished doctoral dissertation). PLPSOFT.
Ribes, E. (2022a). Using classification techniques to accelerate client discovery: a case study for wealth management services.
Ribes, E. (2022b). What are the financial implications of an ageing population for european citizens?
Riikkinen, M., Saarij¨arvi, H., Sarlin, P., & L¨ahteenm¨aki, I. (2018). Using artificial intelligence to create value in insurance. International Journal of Bank Marketing.
Rocher, S., Stierle, M. H., et al. (2015). Household saving rates in the eu: Why do they differ so much? (Vol. 5). Publ. Office of the Europ. Union.
Ross, S. M. (1995). Stochastic processes. John Wiley & Sons.
Ryman-Tubb, N. F., Krause, P., & Garn, W. (2018). How artificial intelligence and machine learning research impacts payment card fraud detection: A survey and industry benchmark. Engineering Applications of Artificial Intelligence, 76, 130–157.
Shang, B., & Goldman, D. (2008). Does age or life expectancy better predict health care expenditures? Health Economics, 17(4), 487–501.
Singh, S., & Chivukula, M. (2020). A commentary on the application of artificial intelligence in the insurance industry. Trends in Artificial Intelligence, 4(1), 75–79.
Takeda, A., & Ito, Y. (2021). A review of fintech research. International Journal of Technology Management, 86(1), 67–88.
Tepe, G., Geyikci, U. B., & Sancak, F. M. (2021). Fintech companies: a bibliometric analysis. International Journal of Financial Studies, 10(1), 2.
Tilmes, R., & Schaubach, P. (2006). Private banking und private wealth management–definitionen und abgrenzungen aus wissenschaftlicher sicht. Private Banking und Wealth Management, BankakademieVerlag GmbH, Frankfurt am Main.
Todd, T. M., & Seay, M. C. (2020). Financial attributes, financial behaviors, financial-advisor-use beliefs, and investing characteristics associated with having used a robo-advisor. Financial Planning Review, 3(3), e1104.
Vives, X. (2017). The impact of fintech on banking. European Economy(2), 97–105.
Witt, U. (1993). Evolutionary economics. Edward Elgar Publishing.
Yue, T., Au, D., Au, C. C., & Iu, K. Y. (2023). Democratizing financial knowledge with chatgpt by openai: Unleashing the power of technology. Available at SSRN 4346152.