Risk Control Model Construction In Petrochemical Industry

With the deepening of the market extent and growing enterprise competitiveness, the internal management of petrochemical industry is continuously expanding in the scope and depth, and the management and control of business risk became an essential part for enterprise to strengthen their management. This research combined with rough sets, vague sets, BI and Multi-agent technology to solve problems in the risk control of petrochemical industry enterprises. It realized source data collection through a first level financial accounting system, and applied JIT method to implement monitoring in business process. Meanwhile, through supply chain management and team accounting system, it strengthened the internal control, and put forward a method about using uncertainty theory to identify the potential risks, using data mining, data warehouse and other business intelligence tools to analyze the risks, and multi-agent system to simulate human's decision-making mechanism for risk prevention and control. By the use of modern information technology tools and platforms to build a set of comprehensive, scientific and reasonable risk control system platform, so as to effectively solve the complex and uncertain problems of petrochemical enterprises in the process of risk identification, risk measurement, risk early warning and risk control, realize early warning of potential risks, and effectively prevent and control risks. The main research work includes the following content:The first part is the basic theory of enterprise risk management. It introduced the involved concepts and techniques, and provided ideological and theoretical basis for the next steps.The second part is about theory application in enterprise risk management. It researched the application of vague set and rough set theory in enterprise risk identification. First of all, vague set theory was introduced into evaluation of the risk factors. Then rough set was used in the identification of enterprise risk factors.The third part is about model construction of enterprise risk management. This part is the focus of the research. It mainly studied how to establish the early warning model of petrochemical enterprise risk prevention and control system. First of all, BI technology was used in the establishment of early warning model of enterprise risk management. Then multi-agent technology was introduced according to the characteristics of risk management, and it illustrated and described the structure of multi-agent risk prevention and control model based on JADE. Based on above, it put forward the method about prior extension of data collection points, using JIT monitoring during the entire process, using information technology to integrate multiple system, to establish petrochemical enterprise risk prevention and control platform. Finally, it presented the concrete technical scheme about how to build the risk prevention and control platform.This research proposed a multi-level business management prevention and control platform based on modern industrial control computer data acquisition, team management, supplying chain management, first level financial accounting system, JIT monitoring and other relative systems. It used multi-agent system to simulate human's decision. Through the effective integration of multiple application systems, it implemented risk prevention and control during the whole process from risk assessment, risk early warning, risk decision, and risk control. The main innovation is:(1) Introduced rough set and Vague set theory into the risk management process, proposed the whole processing risk prevention and control concept based on source data acquisition and JIT thought. Through the integration of one first level accounting system, supplying chain management, team accounting system, and many other systems to strengthen internal control, built risk prevention and control system according to petrochemical enterprise characteristics.(2) Using business intelligence and multi-agent technology, combining with data mining and data warehouse and other business intelligence tools, built petrifaction enterprise risk management model, divided complex risk management modules into relatively independent agent, to find enterprise risk occurrence and diffusion law.(3) Based on above risk management model, effectively integrated a plurality of application management systems, established a distributed architecture petrochemical enterprise risk prevention and control platform including financial, capital, goods and materials, marketing and a wide range of business resources.