Design and Implementation of Financial Risk Prevention and Control Platform Based on Spark

In order to improve the efficiency and accuracy of financial risk management and control, we design and implement Spark-based big data processing platform, and study the key technologies of multi-source heterogeneous data acquisition, risk feature extraction, real-time warning and data visualisation. Through the combination of distributed architecture and machine learning algorithms, the platform analyses the dynamically changing features of corporate financial data, and constructs an efficient computing framework and a multi-dimensional feature evaluation model. The results show that the platform has excellent performance in real-time monitoring, high concurrency processing and risk identification accuracy, which can effectively support the risk management needs under complex financial scenarios and provide efficient and stable technical guarantee for enterprises.