Big Data in the financial industry: Applications, potential and regulatory approaches

Abstract

In the financial industry, the volume and complexity of data is growing exponentially. These vast amounts of data can potentially offer valuable insights that can contribute to process optimisation, risk management and decision making. Many companies in the industry, however, face the challenge of how best to leverage this data. Despite a general awareness of the significance of Big Data, there is often uncertainty surrounding the optimal use of this data for practical applications. This paper summarises the existing real-world applications, especially those with implications for financial stability, and highlights the specific benefits of Big Data in the financial sector. The paper comments on the role and implications of Big Data regulation from the perspective of a regulatory authority. It shows that artificial intelligence (AI)-driven Big Data processing has expanded from customer interfaces to banks’ back ends. Numerous use cases exist along the value chain within the financial sector, including at central banks. Big Data offers both opportunities and risks for the financial system as a whole. The paper thus also emphasises the importance of striking a balance with regard to regulating AI. Overall, the paper argues that the effective use of Big Data has the potential to enable the financial industry to cultivate better efficiency in business practices and ensure greater resilience in the financial system.