In the context of big data era, the traditional valuation methods for company mergers and acquisitions have limitations and are difficult to comprehensively consider the uncertainties in enterprise value. Based on the background of big data, this study combines data mining technology and real options theory to construct an assessment model for M&A valuation. Firstly, an empirical study is conducted on information technology service company S through financial index analysis, and data mining technology is used to analyze its four financial indexes, namely, development ability, solvency, operation ability and profitability; secondly, a real option valuation model is used to make valuation calculations. The results show that the valuation result of the real option valuation model in the M&A valuation of S Company is 5,711,100,000 yuan, which is 165.31% value-added over the book value of 2,152,600 yuan; the discrepancy rate compared with the valuation result of the income approach of 5,680,000 yuan is only 0.55%; and the discrepancy rate compared with the pricing of 5,780,000 yuan of the actual deal is 1.19%, which is lower than that of the income approach of 1.73%. The study concludes that the real option valuation model not only considers the uncertain assets not reflected in the book value of the enterprise, but also considers the option value in the M&A transaction, and its valuation results are closer to the actual transaction pricing, which can be used as an effective supplement and validation of the traditional valuation method, and provide a more scientific and reasonable theoretical basis and methodological tools for the company’s M&A decision-making under the background of big data.
