Abstract

Supervisory Technology (SupTech) combines artificial intelligence (AI) with machine learning (ML) for the specific purpose of supervision of the financial markets. SupTech offers transformative solutions for the regulation, monitoring and surveillance of financial markets. This article presents a literature review examining the role of SupTech in enhancing market surveillance. Using the PSALSAR framework, we conduct a Systematic Literature Review (SLR) of 55 articles published between 1999 and 2022. The review highlights the potential of SupTech to navigate the complexities of the financial landscape, and its versatile applications for financial supervisors and regulators, stock exchanges, intermediaries, and investors. Our findings indicate that SupTech models can effectively detect instances of market manipulations, insider trading, and fraud. These models also showcase exceptional potential to forecast crises in markets, economies, corporations, and in the banking sector. They are useful in empowering policymakers and regulators to make informed decisions. The study provides a strong foundation for future research and policy development to explore and deploy the potential of SupTech, paving the way for greater transparency, efficiency, and resilience in financial markets.

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