Author
Listed:
- Nina Toivonen
(University of Helsinki)
- Marika Salo-Lahti
(University of Vaasa, School of Accounting and Finance, Business Law)
- Mikko Ranta
(University of Vaasa, School of Accounting and Finance, Accounting)
- Helena Haapio
(University of Vaasa, School of Accounting and Finance, Business Law
Tampere University, JARGONFREE Contract Language Research Group
Lexpert Ltd)
Abstract
TechnologyTechnology plays a significant role in today’s over-indebtedness. However, its potential to help people overcome debt problems and maintain good financial healthFinancial health remains largely untapped. The need for alternative, personalized solutions to over-indebtedness is becoming increasingly pressing worldwide, especially since many people struggling with debt do not have access to judicial debt rehabilitationDebt rehabilitation programs. This chapter explores how generative AIGenerative AI (GenAI) could support individuals in financial distress. Using the behavioral COM-B modelCOM-B model as a framework for designing effective interventions, we discuss how AI could help improve individuals’ capabilities, opportunities, and motivation to achieve financial well-beingFinancial well-being, and what solutions already exist for these purposes. Inspired by fitness applications that offer personalized advice, we used OpenAI’s GPT Builder to create “Finance FriendFinance friend,” a simple prototype of a financial adviser, and explored its potential as a personalized financialPersonalized financial coaching coach. While the tool shows great promise for the future of financial coaching, we also emphasize the need for trustworthy technologyTechnology and regulatory frameworks that promote responsible design, implementation, and use of AI in the context of debt rehabilitationDebt rehabilitation.
Suggested Citation
Nina Toivonen & Marika Salo-Lahti & Mikko Ranta & Helena Haapio, 2025.
"Generative AI for Individuals’ Financial Well-being and Debt Rehabilitation,"
Perspectives in Law, Business and Innovation, in: Marcelo Corrales Compagnucci & Helena Haapio & Mark Fenwick (ed.), Generative AI, Contracts, Law and Design, pages 127-147,
Springer.
Handle:
RePEc:spr:perchp:978-981-95-2058-9_8
DOI: 10.1007/978-981-95-2058-9_8
Download full text from publisher
To our knowledge, this item is not available for
download. To find whether it is available, there are three
options:
1. Check below whether another version of this item is available online.
2. Check on the provider's
web page
whether it is in fact available.
3. Perform a
for a similarly titled item that would be
available.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:perchp:978-981-95-2058-9_8. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.