Assessment of M and A risks based on fuzzy consistent matrix

Merger and acquisition is an important commercial activity which facilitates business efficiency and contributes to macroeconomic growth. However it is challenged by various risks, amongst which integration risk is complicated and difficult to identify. In this paper, integration risk was analyzed, identified, processed and assessed with big data technology. Based on fuzzy consistent matrix method, a simulated case study was conducted to establish an applicable fuzzy comprehensive model for integration risk assessment in merger and acquisition. In the theoretical analysis, the research firstly analyzed the feature of integration risk, elaborated different categories of integration risk, while explained the suitability to adopt big data technology in risk management. Information asymmetry, multi source of information and quantification of qualitative information in integration risk required unique valuation method. Corporate governance risk, cultural and social integration risk, technology integration and human resource integration risk has respective characteristics and are represented by different variables. And then, several merger cases are closely studied, combined with success cases and failed ones, indicators and risk related information were elaborated. The various sources of data were provided for big data analysis, from individual firms, industrial level and macro policy and market environment level. In the empirical analysis, the fuzzy evaluation method includes the establishment of comparison preferential matrix, transformation into fuzzy consistent matrix, calculation for single objective sequencing, and final achieved overall risk assessment result. Future research prospects and policy implications were also discussed.