Answers are grounded in this paper and cite their sources.
This study examines how FinTech companies transform consumer behaviour data into financial value through artificial intelligence, predictive analytics, and hyper - personalisation. It explores how transactional, behavioural, and demographic data are collected, analysed,and converted into personalised financial products, recommendations, interfaces, and communication strategies. The study further evaluates how these practices influence customer retention, customer lifetime value, return on investment, average revenue per user, customer acquisition cost, and churn. Particular attention is given to machine learning, customer segmentation, recommendation systems, and predictive models used to anticipate consumer needs and improve engagement. The paper also considers the strategic role of data in product development, cross-selling, and marketing optimization. Alongside these benefits, it critically examines privacy, consent, algorithmic bias, cybersecurity, and regulatory compliance. The study concludes that AI-driven personalisation can create substantial commercial value in FinTech, but sustainable growth depends on transparent, secure, fair, and responsible use of consumer data over the long term.
No takes yet. Share an insight, caveat, or question.
Metaksh Jangid (2026) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: