The Influence of AI-Based Predictive Marketing on Fintech Customer Acquisition and Financial Performance: Evidence from Digital Banking Platforms

Abstract

Artificial intelligence (AI) adoption in predictive marketing has revolutionised the customer acquisition patterns in the fintech industry, and empirical data regarding its direct influence on financial performance is scarce. This research paper examines how Artificial Intelligence-based predictive marketing can enhance customer acquisition, retention, and overall financial performance of digital banking services. We utilise a machine learning-based predictor of customer subscription behaviours using the Bank Marketing Dataset of UCI to evaluate the effects of different predictors on customer lifetime value (CLV), marketing return on investment (ROI), and profitability. The findings show that AI-based approaches, especially using neural networks, can be a powerful tool to increase the conversion rates and utilise the marketing resources maximally, resulting in better revenue growth and increased ROI. Moreover, the paper presents the most important moderating variables, including regulatory compliance, data privacy, and consumer trust, that determine the effectiveness of AI marketing activities in fintech platforms. The results will provide useful information to the fintech managers who will need to employ AI-based marketing systems to boost business and increase customer interactions when coping with external forces. The study will help fill the gap in the current literature concerning marketing analytics and financial outcomes within the fintech industry and provide both theoretical and empirical evidence on the role of AI in making marketing investments rational.