Cross-Asset Risk Management and Fraud Detection: Assessing the Role of Multidimensional Data Analytics in Modern Financial Trading
Dang Quoc Bao
Rustam Mukhitdinov
Abstract
This paper explores the critical role of multidimensional data analytics in cross-asset risk management and fraud detection within modern financial trading. As financial markets become increasingly interconnected, managing risk across multiple asset classes requires advanced tools and techniques that account for complex interdependencies. Similarly, the detection of fraudulent activities has become more challenging due to the high volume and speed of transactions. The integration of machine learning, big data analytics, and real-time surveillance systems has significantly improved the ability of financial institutions to anticipate risks, detect fraud, and respond to threats. By leveraging these tools, institutions can enhance decision-making, improve market transparency, and protect against financial fraud.
