Data Fabric and Data Mesh in Banking: Applications for Risk, Fraud, and Regulatory Intelligence

Abstract

This paper examines the application of data fabric and data mesh in banking, with a focus on their roles in enhancing risk management, fraud detection, and regulatory compliance. It evaluates how these architectures address key challenges in the banking sector, such as data fragmentation, growing fraud concerns, and regulatory complexity. It utilises real-world use cases to demonstrate how data fabric supports real-time analytics and governance, while data mesh empowers domain-led innovation and agility through decentralisation. The combined approach offers a scalable, intelligent framework for financial institutions navigating digital transformation. The paper also identifies key technical, organisational, and regulatory challenges, offering strategic insights for successful implementation in complex banking ecosystems.