This chapter provides information on the use of artificial neural networks and fuzzy logic, also discusses risk assessment methods based on artificial neural networks and on the basis of fuzzy logic. The advantages and disadvantages of intelligent methods for determining credit risk are described.

This chapter also provides examples of the methodology for assessing investment risks and assessing credit risks, as well as examples of using fuzzy logic to assess the risks of the current activity of an enterprise and using fuzzy sets for analyzing investment projects.

Using the fuzzy set method provides several advantages, as it allows you to: include qualitative variables in the analysis; operate with fuzzy input data; operate with linguistic criteria; quickly simulate complex dynamic systems and compare them with a given degree of accuracy; overcome the shortcomings and limitations of existing methods for assessing project risks. Based on the conclusion made in the future, fuzzy logic will be used to develop a model for assessing credit risk.