The research and application of enterprises' dynamic risk monitoring and assessment model based on related time series

For the risk management problem of key enterprises in the area, we propose a time-series based risk monitoring and assessment model which could manage and predict enterprises' dynamic risk levels. Our model takes a systematic method to monitor and evaluate enterprises' various types of risk indicators: by collecting real-time categorical data through pre-designed data-collection portal, the model applies Z-score algorithm on processing and normalizing enterprises' categorical data and generates a time-series based risk intensity matrix. After that, our model uses entropy method to assign different weights on risk indicators to generate initial comprehensive risk index values; by applying the superposition of time-series risk attenuation function on the initial risk index values, we get the overall risk index values which is used to reflect enterprises' business risks. The simulation results of our method prove that our risk management model provides an effective solution to monitoring and evaluating enterprises' risks in the region. We have built monitoring and assessment information systems for several enterprises based on this risk management model; the purpose of this paper is to explain procedures the model takes to implement risk monitoring and assessment functions.