Downloads: 4 | Views: 262 | Weekly Hits: ⮙1 | Monthly Hits: ⮙3

Informative Article | Risk Management | India | Volume 12 Issue 11, November 2023 | Popularity: 4.7 / 10

Rate This Article!      

AI-Driven Risk Management and Fraud Detection in High-Frequency Trading Environments

Yash Jani

Abstract: High-frequency trading (HFT) environments, characterized by the rapid execution of trades and large volumes of data, demand sophisticated and real-time risk management and fraud detection solutions. Traditional systems need help to keep up with the velocity and complexity of data, leaving gaps that can be exploited. This paper proposes an AI-driven architecture leveraging machine learning models to enhance risk management and fraud detection in HFT environments. Implemented using Amazon SageMaker for AI/ML processing, the architecture is designed to be scalable, efficient, and capable of real-time decision-making. The study presents the detailed architecture, discusses each component's role, and evaluates the system's performance in mitigating risks and detecting fraud in live trading scenarios.

Keywords: AI-driven risk management, fraud detection, high-frequency trading, machine learning, Amazon SageMaker, real-time data processing, predictive modeling, anomaly detection, algorithmic trading, decision support systems

Edition: Volume 12 Issue 11, November 2023

Pages: 2223 - 2229

DOI: https://www.doi.org/10.21275/SR24827092909

Make Sure to Disable the Pop-Up Blocker of Web Browser

Click to Cite this Article