| Abstract [eng] |
The topic explores the use of big business data to facilitate business decision-making. The relevance of the topic “Credit risk assessment model of potential company customers” is based on the need of the business before concluding (extending) a contract with the client to ascertain whether it will be able to meet its financial obligations. Using mathematical methods, the most important evaluation criteria are selected, a model based on financial indicators. Data source – “Bloomberg” platform. The final project analyzes the financial statement data, creates a sample of the model data, a list of variables and a statistical and artificial intelligence method for companies' credit risk assessment model, which assesses the probability of financial default, compares the model's effectiveness, classifies companies into risk groups and determines their credit rank. In order to identify the most commonly used credit risk assessment methods, the scientific literature and publications are presented, which present the credit risk assessment models developed by the authors. The analysis identifies which credit risk methods are the best and creates credit risk assessment models that analyze the data of potential companies. |
