Financial Diagnostic Study Based On Data Mining And Programs Generation

With the increasingly fierce market competition, enterprises are facing unprecedented challenge, the importance of financial diagnosis is growing. Traditional financial diagnostic process is that diagnosis experts accept the commission of enterprises, then determine the topic, make the formal diagnostic analysis specific and finally give the diagnostic results and recommendations. But traditional financial diagnostic process is too simple, defective and it lacks the careful consideration of the internal and external environment, the low efficiency of diagnosis, and it can not provide a more reliable and valid diagnostic program.This article is based on the MCS model proposed by Professor Ge Fuliang in2004. He proposed the financial diagnostic study based on data mining and programs generation. First, using cluster analysis methods in the data mining technology to collect financial information and then building a database of corporate financial diagnosis. Second, constructing the index system of financial diagnosis and using the method of statistical analysis in diagnostic analysis. Finally, putting diagnostic results in chart so that the diagnostic results are intuitive and simple, easy to understand. At the same time, using program generation technology to generate a basic diagnostic program on the base of the diagnostic results and combined with expert experience in evaluation and analysis of the diagnostic programs to achieve a final program.In this paper, company X is taken as an example to describe the specific application of data mining and financial program generation technology in diagnostic process and program generation techniques. That data mining technology as an information collection technology can depth analysis a lot of financial data, obtain useful financial information. The data mining techniques used in corporate financial diagnosis can reduce the complexity of manual operations, improve financial efficiency of diagnosis, combining method of statistical analysis to optimize the financial diagnosis process, so that the financial diagnostic process become more logical operational, results of financial diagnosis are more objective and scientific. Program generation technology as a systems engineering technology applied to financial diagnosis achieve a person-machine combination, which improve the diagnostic efficiency and effectiveness of diagnostic programs.