Role of Cyber Physical System in Insider Trading

Illegal insider trading detection and enforcement of insider trading laws is a challenging task that attracts the attention of regulators due to its serious harm to confidence of investors and sustainable development of financial markets. Due to the finite availability of resources, it's still very difficult for the regulators to book the offenders into the act of doing it. The paper focuses on the significance of having advanced technology in this area while it discusses the recent studies on insider trading detection. The author explicitly discusses the challenges faced in detection of financial crime by applying machine learning and data mining techniques. The paper also examines several market surveillance strategies that are used to protect financial markets. The primary goal of the study is to provide a thorough review of the potential effects of data mining and machine learning on market data and how to use them to ensure the integrity of financial markets. Furthermore, the author identifies some of the key challenges that currently exist and proposes potential solutions, such as integrating new tools and techniques with existing mechanisms to detect insider trading. Finally, the paper concludes with some recommendations that could be implemented in practice.