The advent of the era of big data has promoted the transformation of traditional financial management models, and the automated sharing of public financial information has gradually appeared in the public’s field of vision. Gradually recognized by business managers, there has been an upsurge in the application of public financial information automated sharing models. Especially it has been widely used in large enterprises and multinational enterprises, and it has also attracted the attention of many large enterprises. With the continuous maturity of big data technology, financial information has shown diversified characteristics, and more accurate financial analysis capabilities are required. The management of enterprises has gradually realized that applying big data mining algorithms to the automated sharing of public financial information should be possible. Bring new progress to sharing centers and enterprises. Slowly, with the continuous development of technology, more and more senior corporate managers realize the importance of automated sharing of public financial information and the practicality of big data mining algorithms. Research shows that this article mainly uses the literature research method to study the origin, definition and implementation process of the public financial information automation sharing model by domestic and foreign scholars, and proposes the process modules that need to be improved and optimized under the big data environment. Studies have proved that the company’s products have gradually gained advantages after 2015, reflecting that the company’s profitability is gradually recovering, and the utility of the automatic sharing model of public financial information based on big data mining algorithms has begun to gradually come into play. At the same time, the main business income and net profit respectively showed a downward trend in 2015, and showed a steady increase after 2009. In 2008, the company’s public financial information automatic sharing model based on big data mining algorithms incurred relatively large costs in the early stage, which also had a greater impact on the company’s related profit indicators.