Optimizing financial decision-making for emerging adults: A compact Python-based personalized financial projection approach

Alex Yue Feng Zhu

Technology in Society, 2024, vol. 77, issue C

Abstract: The financial decisions made by emerging adults significantly influence their long-term financial well-being. To make effective decisions, they need both financial literacy and a forward-looking mindset. However, existing literature lacks tailored financial interventions for this demographic. Addressing this gap, our study implemented and evaluated a Python-based Personalized Financial Projection (PFP) among emerging adults in Hong Kong. Our findings indicate that the Python-based PFP effectively promoted prudent financial behaviors by enhancing participants’ perceived financial literacy and future time perspectives. This represents a significant advancement, providing the first empirical evidence supporting the integration of computer programming into financial education initiatives. In an era of interactive Artificial Intelligence (AI) for financial guidance, the Python-based PFP stands out as a pivotal resource capable of leveraging interactive AI to enhance financial decision-making processes.

Keywords: Financial education; Python; Personalized financial projection; Interactive AI; Financial literacy; Future time perspectives (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0160791X24001477
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:teinso:v:77:y:2024:i:c:s0160791x24001477

DOI: 10.1016/j.techsoc.2024.102599

Access Statistics for this article

Technology in Society is currently edited by Charla Griffy-Brown

More articles in Technology in Society from Elsevier
Bibliographic data for series maintained by Catherine Liu ().