Design of Project Cost Risk Management System Based on Improved Fuzzy Rule Weight Algorithm

Aiming at the low accuracy of index weight calculation and risk type identification in traditional cost risk management systems, this paper proposes a project cost risk management system based on an improved fuzzy rule weight algorithm. We analyzed the types of project cost risks, adopted a three-tier technical architecture to design the system frame structure and functional organization structure of the cost risk management system, and adopted the B/S architecture for network structure deployment. In the software part, an improved fuzzy rule weight algorithm is used to calculate the weight of project cost risk indicators, thereby improving the effectiveness of risk management. Experimental results show that the designed system works well, can accurately calculate the weights of risk indicators, and can effectively identify multiple risk types.

Modeling of Bank Credit Risk Management Using the Cost Risk Model

This article deals with the issue of managing bank credit risk using a cost risk model. Modeling of bank credit risk management was proposed based on neural-cell technologies, which expand the possibilities of modeling complex objects and processes and provide high reliability of credit risk determination. The purpose of the article is to improve and develop methodical support and practical recommendations for reducing the level of risk based on the value-at-risk (VaR) methodology and its subsequent combination with methods of fuzzy programming and symbiotic methodical support. The model makes it possible to create decision support subsystems for nonperforming loan management based on the neuro-fuzzy approach. For this paper, economic and mathematical tools (based on the VaR methodology) were used, which made it possible to analyze and forecast the dynamics of overdue payment; assess the quality of the credit portfolio of the bank; determine possible trends in bank development. A scientific and practical approach is taken to assess and forecast the degree of credit problematicity by qualitative criteria using a mathematical model based on a fuzzy technology, which can forecast the increased risk of loan default at an early stage in the process of monitoring the loan portfolio and model forecasting changes in the degree of credit problematicity on change of indicators. A methodology is proposed for the analysis and forecasting of indicators of troubled loan debt, which should be implemented as software and included in the decision support system during the process of monitoring the risk of the bank’s credit portfolio.

Supply risk management: A case study of halal food industry in Malaysia

The purpose of this study is to identify the types of halal food supply risks, types of mitigation strategies for the upstream supply chain and to examine the relationship between halal supply risk and mitigation strategy efforts using the lens of the agency theory. Exploratory factor analysis (EFA) is used to validate the variables of the study and regression is performed to analyze the relationship of halal food supply risk and mitigation strategy. It is identified that halal food supply risk (agency uncertainties) consists of quality risk, delivery risk, and price/cost risk. The mitigation strategy efforts consist of behavior-based management, buffer-based management, and traceability-based management. Results indicate that halal food supply risk significantly increase mitigation strategy efforts of firms. However, price & cost risk does not significantly increase behavior-based management. Practical implications include suggesting the firms to invest more in buffer-oriented so as to mitigate the agency uncertainties.

Research on the Whole Process Cost Risk Evaluation Index System of Real Estate Park

The development focus of real estate enterprises has shifted from traditional buildings to industrial park construction. After summarizing and analyzing the risk factors of the traditional construction cost, the WBS-CBS-RBS method is used to classify and identify the whole process cost of the industrial park. Finally, eight first level evaluation indexes and 37 second level evaluation indexes are established to form the whole process cost risk evaluation index system of the industrial park construction, which provides the basis for the whole process cost risk assessment of the subsequent industrial park construction.