Exploring Cutting-Edge Algorithms in FinTech: Leveraging Machine Learning and Artificial Intelligence for Achieving Sustainability

Abstract

Abstract This chapter explores the intersection of cutting-edge algorithms in the financial technology (FinTech) sector, with a particular focus on the application of machine learning (ML) and artificial intelligence (AI) to enhance sustainability and ethical finance practices. The transformative capabilities of ML and AI are examined through their roles in revolutionising financial services by increasing operational efficiency, improving decision-making processes and enhancing risk management strategies. Specific applications discussed include fraud detection, anomaly detection in financial statements, robo-advisory services, prediction of customer deposits, combating money laundering, sentiment analysis, loan eligibility prediction, stock price prediction and the automation of routine tasks through chatbots. Additionally, the chapter addresses the crucial role of AI and ML in supporting green finance initiatives, reducing carbon footprints and promoting financial inclusion, thereby contributing to sustainable economic development. The detailed exploration provides insights into how these advanced technologies are key in shaping the future of the financial industry towards more sustainable outcomes.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 31 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.