Abstract
Financially empowered consumers are better equipped to manage debt, build savings, and invest in their future. This, in turn, boosts economic growth, drives business innovation, and supports government efforts to combat poverty and income inequality. This study aims to demonstrate that digital transformation in the banking sector and the adoption of Fourth Industrial Revolution (4IR) technologies—such as automation, mobile banking, big data, advanced business analytics, and human-AI collaboration—can significantly enhance consumer financial well-being.
Explainable Machine Learning techniques are applied to banking big data to predict and explain consumer financial distress and financial rehabilitation. The study illustrates how explainability can be leveraged to develop prescriptive actions that support consumer financial well-being, identifying at-risk individuals and providing personalised supportive measures.
Additionally, the study examines the adoption of mobile banking and human-AI collaboration within the banking sector, proposing how these platforms can be utilised to implement the outcomes of explainable machine learning and prescriptive modelling. Two delivery frameworks are discussed: automated consumer journeys via a mobile banking app and telephonic interactions through a call centre utilising human-AI collaboration. These frameworks ensure that the advanced technologies investigated are not merely theoretical but can be practically applied within banking to enhance consumer financial well-being.