From Borrowing to Building: A Systematic Literature Review of DataDriven Strategies for Cultivating Better Money Habits through Consumer Credit

The cultivation of sound money habits is central to individual financial wellbeing and broader economic resilience. In the digital era, consumer credit has evolved from traditional lending instruments into data-driven platforms that both enable and influence financial behavior. This systematic literature review synthesizes academic and industry research on how alternative data sources, machine learning techniques, and behavioral insights are integrated into credit systems to foster healthier money habits. Findings highlight three major domains: (1) the use of social, behavioral, and transactional data to expand financial inclusion and improve credit risk prediction; (2) the role of behavioral economics, including personality traits, self-control, and financial literacy, in shaping borrowing and repayment behaviors; and (3) the impact of information design, disclosure practices, and technological feedback mechanisms on financial literacy and long-term behavior change. While these innovations hold significant promise for more equitable credit access and personalized financial guidance, they also raise pressing concerns about data privacy, algorithmic bias, and the ethical use of consumer information. The review concludes that adaptive feedback loops and transparent AI systems represent the most promising avenues for sustainable habit formation, but achieving balance between innovation and consumer protection remains a critical policy and industry challenge.