In this monograph for further research, an analysis of credit risk was adopted as one of the most important in the banking sector. When managing credit risks, it is necessary to determine the goals of the bank and also the means for their implementation within a certain time period. This strategy should consist of the main stages: determining the period of time (for example, short-term, medium-term and long-term planning); determination of the goals of managing the system of credit risks (for example, final and intermediate); development of credit risk management measures; development and improvement of a monitoring system for the implementation of strategic plans [45–49].

It is worth considering the fact that currently used borrower credit rating systems should take into account the current state of the company. They should also be aimed at predicting the level of financial stability for the entire lending period. The development of advanced credit risk management technologies is necessary for the development of the real production sector, as well as to ensure an acceptable level of risk in the client portfolio for banks. It should be taken into account that the development of modern technologies for assessing the creditworthiness of borrowers can serve as a source of information when making decisions.

Lending itself refers to the profitable activities of banks of any level, but at the same time, the issuance of loans is one of the risky banking operations. The effectiveness of banking activities depends on the degree of optimization of credit risk management, since the success of almost any decision in the field of strategic and tactical financial management is determined by the ability to identify and evaluate risks, carry out credit controlling of the behavioral characteristics of open risk positions that ensure the achievement of the bank's target functions. The methods used today for assessing the creditworthiness of a borrower should take into account only the current state of the organization and be able to predict the level of financial stability for the entire lending period.

Under the management of credit risk in the banking sector, it is worth taking the organized impact of the management entity on the asset (for example, credit risk) to reduce the bank's credit risk indicators. Credit risk management should be understood as an organized sequence of actions that can be divided into several stages. These steps include: detecting credit risk factors; credit risk assessment; the choice of a specific strategy; selection of ways to reduce risk; control of changes in the degree of credit risk.

In order to fulfill the condition for ensuring the financial stability of banks, it is worth applying not linear trending, but more complex forecasting systems that are designed on the basis of the borrower's internal environment (using fuzzy logic) [45].

Analysis of the banking sector found that the dynamics of the loan portfolio shows an unstable situation in the quality of the loan portfolio in second-tier banks of the Republic of Kazakhstan. At present, there are difficulties in second-tier banks or microcredit organizations in analyzing the financial condition of individuals and assessing their creditworthiness. Modern realities encourage banks not only to determine the level of risk of the loan portfolio, but also to determine its forecast value.

It is worth noting that second-tier banks of the country and microcredit organizations apply various methods of forecasting credit risk, which allow you to calculate risks and reduce their impact on the financial performance of a bank or organization. As was indicated in the first chapter of the monograph, all existing methods for assessing the credit risk of a portfolio can be conditionally classified into classic and «progressive». It is worth noting that the first methods are too formalized and do not accurately take into account the complex nature of credit risk. Classical methods include a system of internal credit ratings and a methodology for weighing risk assets officially adopted by the Basel Committee on Banking Regulation and Supervision [50-55].

Note that the classic approach to determining credit risk is based on a standard assessment of the borrower's creditworthiness and assigning a credit rating to the borrower. Thus, risk assessments for each borrower are generated, which allows for analysis at the portfolio level. The applied system of internal credit ratings makes it possible to accurately determine credit risk and the amount of capital to cover it. This method takes into account such parameters as: probability of default (in other words, the probability of non-fulfillment of the contract); exposure to credit risk at the time of default; level of losses upon default; effective period to                     maturity [56].

It is worth noting that the «progressive» methods are more complex. The methods under consideration use complex mathematical models that more accurately take into account the specifics of credit risk. The dynamism of internal models gives them an advantage over static counterparts [57].

In addition to loans provided by second-tier banks for individuals and legal entities, the Government of Kazakhstan is developing a number of measures aimed at developing small and medium-sized businesses. So in 2018, within the framework of the unified program of support and development of the business «Business Road Map 2020», 38.8 billion tenge was provided. 30 billion tenge will be allocated for subsidizing, guaranteeing loans and issuing state grants. And in order to meet the business needs for new projects, the Ministry prepared a budget application in the amount of 12.2 billion tenge in 10 regions [58].

As an example, Halyk Bank of Kazakhstan JSC is conducting a consultation process and collecting applications under the state program to support the automotive industry (preferential loans to individuals for the purchase of domestic cars), has completed the development of funds under the Program of conditional allocation of funds in second-tier banks for subsequent lending to entities female entrepreneurship.

The above data indicate that the consumer lending market is extremely profitable, but at the same time shows a rather high risk of this event. One of the main reasons for high risks is that the risks of credit organizations are not yet amenable to sufficiently reliable assessment and forecasting.

It is also worth noting that in Kazakhstan, different regions have a strong differentiation of regions according to the conditions of socio-economic development. This suggests that the risk assessment system will vary in different regions of the country. It is worth noting that when developing a model for assessing credit risk, it is worth taking into account the characteristics of each country or individual region of the country, taking into account economic and financial characteristics [1].

To create a model for determining credit risk, the main factor is the determination of the main criteria for determining the credit rating of the borrower. This paper considers the option of consumer lending, which has received quite a lot of demand among the residents of our country. When determining a credit rating, the parameters are taken into account: credit history of the borrower, financial condition of the borrower, demographic position of the borrower, ownership of real estate. Each of these indicators has its own indicators. For the accepted criteria for evaluating a credit rating in consumer lending, we define a range for the listed variables. For example, the range for the variable Age is from 18 years to 65 years, which is the norm that most banks adhere to, the range of the variable Credit rating is used from 0 to 10. The range for the variable Salary and Ownership of real estate is presented in dollars. Range for variables for determining credit rating [59]:

а) the credit history of the borrower;

1. b) the financial condition of the borrower:

1) salary;

2) official status;

3) work experience;

1. c) the demographic position of the borrower:

1) age;

2) education;

3) marital status;

4) number of children;

1. d) the ownership of real estate.