Audit Risk Evaluation Model for Financial Statement Based on Artificial Intelligence

In recent years, the economy in China has been steadily improving. The financial situation of enterprises mainstream industries become focus public concern. However, statement frauds, which occur frequently, greatly disrupt economic order country. Thus, it is practical significance to accurately identify and evaluate audit risks statements. For this purpose, paper proposes an risk evaluation model based on artificial neural networks (ANN). Firstly, authors designed indices quantified fraud factors statement. Next, verification was established for used verify predictions three aspects statement, namely, violation penalty (AVP), announcement (AVA), restatement (FSR). Finally, a feedforward network constructed homomorphic encryption algorithm, subsequently predict effectiveness our proved valid through experiments.