This chapter examines the transformative role of data-driven finance in reshaping development paradigms and creating innovative models for inclusive growth. Traditional financial systems in developing economies have often been constrained by weak infrastructure, information asymmetries, and limited access to credit, which hinder productive investment and sustainable development. The advent of big data, digital platforms, fintech, and artificial intelligence introduces new opportunities to address these structural constraints by enabling real-time decision-making, improving financial inclusion, and facilitating risk management. Through analysis of case studies across Africa, Asia, and Latin America, the chapter demonstrates how mobile banking, digital credit scoring, blockchain, and algorithmic lending models are expanding access to finance for previously excluded populations, particularly women, youth, and small-scale entrepreneurs. It highlights how these innovations enhance transparency, reduce transaction costs, and mitigate corruption risks, while also fostering trust between governments, financial institutions, and citizens. However, the chapter also underscores the challenges posed by data-driven finance, including regulatory gaps, cybersecurity risks, digital divides, and ethical concerns around privacy and algorithmic bias. By integrating insights from development economics, financial technology, and institutional theory, the analysis situates data-driven finance as both a disruptive and enabling force in advancing the Sustainable Development Goals. Ultimately, the chapter argues that unlocking the full potential of data-driven finance requires not only technological innovation but also strong governance frameworks, equitable access to digital infrastructure, and inclusive policies that prioritise development outcomes over profit maximisation.
