An anomaly prediction framework for financial IT systems using hybrid machine learning methods

no code implementations • 30 Jul 2019 • Jingwen Wang, Jingxin Liu, Juntao Pu, Qinghong Yang, Zhongchen Miao, Jian Gao, You Song

To improve the efficiency and accuracy of system failure detection and thereby reduce the impact of system failures on financial services, we propose a novel machine learning-based framework to predict the occurrence of system exceptions and failures in a financial software system.

BIG-bench Machine Learning Time Series Prediction