Fraud identification of financial reports based on neural network algorithm

This paper combines the correlation test with the neural network algorithm to form a financial report fraud identification model. Based on the triangular theory of financial reporting fraud motives, stress factors and opportunity factors are subdivided into 8 aspects: profitability, asset management ability, solvency, cash flow, asset quality, business development ability, internal and external supervision, and the indicator system for identifying fraud in financial reports is established. The empirical result shows that the profitability, asset management ability, debt paying ability and cash flow of non fraud companies are better than those of fraud companies. Fraud companies have more problems in internal and external supervision. On the whole, the financial report fraud identification model based on neural network algorithm can effectively identify the financial report fraud, and the generalization ability of the model is good.