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

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.