Abstract
Today, the prediction of bankruptcy holds a great importance. The urgency of this problem has led to the fact that there are many various methods and techniques that allow predicting the onset of bankruptcy of an enterprise with varying degrees of proba bility. However, there are many problems in this area. Namely, there are practically no methods that could predict an unfavorable outcome with a high degree of reliability. Most of these methods proved to be untenable during the global financial crisis. Therefore, the creation of systems that allow overcoming the shortcomings of existing models, as well as taking into account the specifics of Asian countries, is an urgent problem. A potential solution to this issue is the use of neural network technologies, which are a highly effective tool. In this research a neural network mathematical model was developed to predict bank bankruptcy by ten input factors. Numerous well-known companies, including General Electric, Procter & Gamble, Coca-Cola, American Airlines, and others, employed neural networks to foresee the financial crisis.