Management of financial risks of a commercial bank. Banking risks. lack of information resources

Relevance of the topic. Development banking business and proposal of new banking products takes place in the conditions of uncertainty in the formation of the final results of activities (i.e., profit or loss), which, on the one hand, increases the riskiness banking operations, and on the other hand, it affects the volume of lending to the economy.

Being integral part financial and credit system of Russia, the banking system is affected by general and specific financial risks. These risks are due to the need to manage funds attracted from clients and the presence on the balance sheet, along with highly liquid and quickly realizable assets (securities), such assets as loans and deposits that cannot be instantly realized.

Commercial banks of Russia in modern conditions become full members of the international business community, for this, starting from October 1, 2004, the Central Bank of the Russian Federation introduced mandatory reporting under IFRS, and from 2006 it plans to completely switch to international reporting standards.

Thus, at present, effective financial risk management is required in credit institutions, and there is a need to form a unified regulatory and methodological framework for risk management and a comprehensive assessment of the financial condition of partner banks. The function of the regulator and chief risk manager was assumed by the Central Bank of the Russian Federation, which organizes the management of the banking system through supervision, using the so-called "risk-oriented" approach. The fundamental document is the Regulation of the Central Bank of the Russian Federation of December 16, 2003 No. 242-P “On the Organization of Internal Control in Credit Institutions”, according to which credit institutions are required to control the banking risk management process on an ongoing basis, using financial management methods. In practice, the functions of controlling financial risks in credit institutions are delegated to specialized banking divisions, which develop intra-bank regulations and constantly monitor the risks taken.

At the same time, the guidelines proposed by the Central Bank of the Russian Federation are clearly insufficient for creating an effective financial risk management system. In this connection banking organizations, relying on methodological basis The Central Bank of the Russian Federation, using the richest world experience in financial risk management, develops its own methodological approaches to risk assessment and management, taking into account national and industry specifics of financial management and the rationality of the management methods used. Thus, for the successful development of the risk management system in commercial banks and increasing their competitiveness in the financial market, the issues of creating a unified regulatory and methodological framework for managing financial risks are brought to the fore.

Insufficient development of theoretical and regulatory framework, a small number of scientifically based and practically tested methods of financial risk management in credit institutions in relation to the current stage of development of the banking system and financial management in Russia predetermined the choice of the topic, goals, objectives and main directions of the study.

Purpose and objectives of the study. The purpose of the dissertation research is to improve the financial risk management system of commercial banks, taking into account the specifics of their operations through the use of modern financial management methods and the development of practical recommendations for banks to identify, assess, record and monitor financial risks in operations in the interbank financial market.

Realization of the set goal predetermined the need to solve the following tasks:

Clarify the essence of financial risks, determine their place in the system of entrepreneurial risks;

Summarize methods for identifying risks and criteria for classifying financial risks in the activities of commercial banks;

Research and evaluate the effectiveness of individual methods of financial risk management in the implementation of commercial bank operations;

Substantiate the proposed classification of bank limits as one of the main methods for managing the financial risks of credit institutions;

Justify the need for the formation and adjustment of financial reserves by banks, taking into account the diversification of risk and the quality of the banking portfolio for operations in the interbank financial market, and develop practical advice on reserve management using the methods of economic and mathematical analysis, the Monte Carlo method and the methodology of UAYA and ILYAOS.

Subject and object of research. The subject of the study is the methodological foundations for managing the financial risks of commercial banks. The object of the study is the financial risks arising from the implementation banking.

Theoretical and methodological foundations of the study.

The theoretical basis of the study was the works of domestic and foreign scientists on the theory and practice of risk management: Algina

A.P., Balabanova I.T., Belykh L.P., Blanka I.A., Bora M. Z., Voronina D.

V., Ershova M. B., Lukasevich I. Ya., Maslachenkova Yu. S., Panovoy G. S., Polyaka G. B., Sevruk V. T., Sokolinskaya N. E., Shirinskaya E. B.

As a methodological basis of the study, a systematic approach, methods of generalization and comparison, analysis and synthesis, the method of grouping, mathematical modeling, the method of historical and logical analysis, as well as risk management models used in practice by modern foreign and Russian banks were used.

The methodological foundations for assessing the financial risks of credit institutions are well developed in foreign economic literature, therefore, the thesis widely used the works of such economists as Altman E.I., Merton R.C., Joseph F., Sinkey Jr.

The information base of the study was legal acts and recommendations, conference materials, financial statements of Russian commercial banks, and official statistics. In the process of research, the author studied instructive-methodical and regulations Bank of Russia on control and regulation of commercial banks, as well as materials of the Basel Committee on Banking Supervision and Regulation.

Of particular interest were the practical developments of Western analytical companies and banks in the field of risk management "Bankers Trust", "Chase Manhattan" and "J.P. Morgan". Electronic information materials were also used.

Scientific novelty. The scientific novelty of the study lies in the development and testing of a methodology for managing financial risks and creating reserves for commercial bank operations in the interbank financial market, clarifying the definition of financial risks, substantiating the proposed classification of risks and limits in the Russian banking system. The following results containing scientific novelty were obtained in the work:

Modern approaches to the disclosure of the essence of financial risks are summarized, the definition of this category is specified, elements of the financial risk management system are identified;

The methods of financial risk management are identified, the criteria for the formation of limits in commercial banks are determined;

An assessment of the effectiveness of the use of domestic and foreign methods of financial risk management in the activities of credit institutions is given;

Developed and tested a methodology for managing financial risks in commercial banks' operations in the interbank financial market, containing new approaches to determining the volume of incurring obligations of counterparty banks based on the analysis of the net balance and determining the market value of assets;

Criteria for assessing the financial condition of banks in the post-Soviet space are proposed, taking into account national characteristics, based on the universal grouping of balance sheets. accounting regulated by international standards financial reporting;

Justified the amount of reserves under possible losses on operations in the interbank financial market, used for the effective management of financial risks by applying the Monte Carlo method, the methodology of the UAYA and the CLEA.

Practical significance. The dissertation describes the financial risk assessment methods used in credit institutions. The practical significance of the study lies in the development by the author of his own methodology for assessing the financial condition of commercial banks in order to accept the risks of counterparty banks and form reserves. The methodology can be demanded by banks in the process of limiting operations in the domestic or external interbank financial market, both in terms of national charts of accounts, and in the context of the transfer of Russian reporting to IFRS. The paper also formulates proposals for the classification of risks and limits of credit institutions when performing transactions with partner banks. The dissertation materials can be used in the educational process in the preparation of students in the specialty "Finance and Credit".

Approbation of the results of the study was carried out in CB "Medinvestbank" and JSCB "Interprombank" in the implementation of financial analysis and subsequent monitoring of the financial condition of Russian counterparty banks, work on operations in the interbank financial market.

The main provisions of the dissertation are set out in 5 articles with a total volume of 2.8 p.p., including the author's contribution of 2 p.p.

The dissertation consists of an introduction, three chapters, a conclusion, a list of references and applications.

IV. Conclusions and offers

After the decision to open limits has been made, the structural subdivisions of risk management carry out monthly monitoring of the financial position of banks.

According to the results of monitoring, which is carried out on the basis of financial statements for each reporting month, the bank's management is informed about the following indicators: the size of the current limit, the volume of the risk limit, the synthetic coefficient of the financial position, the risk of insolvency, the dynamics of active and passive operations, the characteristics of capitalization (sufficient, low, upward, low, high), bank development forecast (positive, neutral, negative). Based on the monitoring results, conclusions and proposals are also made on changing the amounts and terms of limits, or on their possible opening or closing.

In addition, in accordance with the regulation of the Central Bank of the Russian Federation of March 26, 2004 No. 254-P "On the procedure for the formation by credit institutions of reserves for possible losses on loans, on loans and equivalent debts", banks calculate the risk group for possible losses on loans and determine the amount of reserves based on the motivated judgment of analytical units. The reasoned judgment is based on the results of monthly monitoring of the financial condition of counterparty banks.

The proposed methodology allows you to create your own intra-bank rating of counterparty banks, compare it with existing ratings and analyze the position own bank compared to banks of similar size in terms of assets and capital.

I would like to summarize the main points that fundamentally distinguish the proposed methodology for assessing the financial condition commercial bank from other banking methods. The complexity of the comparison is determined by the fact that banks prefer not to disclose their methodological approaches, but, as a rule, disclose only the final results.

1. The developed methodology is close to international reporting standards, and, as the Central Bank of the Russian Federation knows, since 2005, in parallel with Russian standards obliges banks to prepare reports in accordance with IFRS in accordance with the letter of the Central Bank of the Russian Federation 181-T On methodological recommendations “On the procedure for compiling and submitting financial statements by credit institutions”. In this way, commercial Bank, using the proposed methodology, can painlessly begin to analyze the financial position of counterparty banks that prepare statements in accordance with international standards. In addition, the practice of cooperation with the banks of Kazakhstan, Belarus and Ukraine, made it possible, on the basis of the above methodology, to refine it and apply it to assessing the financial condition and determining limits for banks in these regions. Appendix 7 presents an analysis of the financial condition of Kazkommertsbank (Kazazstan), made on the basis of reporting on the national chart of accounts.

2. Based on the calculation net assets lies the method of netting balances for some accounting accounts. The accounts of interbranch turnovers (ZOZA and ZOZP), accounts budget funds, accounts of the bank's claims to receive interest (20319, 20320, 32501, 32502, 40311, 459, 47427) and deferred income from credit operations (32801, 47501, 61303), the bank's obligations to pay interest (accounts 31801-31804, 47411, 47426, 47606-47609) and deferred expenses on credit operations (accounts 32802 and 47502).

3. The introduced concept of net assets and net liabilities, on the basis of which banks are identified as net creditors and net borrowers, makes it possible to differentiate the risk of solvency and the amount of risk taken.

4. The own working capital is taken as the basis for calculating the maximum and settlement limit. It should be clarified that basically all methods in other banks use the size as the basis for calculating the limit. equity, calculated according to the instructions of the Central Bank of the Russian Federation, and adjust it for the state of liquidity. The indicator of own working capital, in contrast to the requirements of the Central Bank of the Russian Federation, takes into account not only the amount of losses incurred and immobilized assets in the form of fixed assets on the balance sheet, but also problem debt. In this regard, it should be noted that the following are classified as problematic:

Overdue debt (accounts 20317, 20318; 32401, 32402 (minus 32403), 40310, from 45801 to 45817 (minus 45818), 50505 (minus 50506, 50507);

Doubtful debt (accounts 47408; 51501, 51502, from 51506 to 51509, 519, (minus accounts 51510 and 51910), from 512 to 514, from 51608 to 51609.51808.51809);

Uncollected debt on factoring and guarantee operations (accounts 47402 minus 47401 and 60315).

5. In addition, the size of the limit also depends on pure value of the bank's capital, and if its negative value exceeds its own working capital, the stop indicator comes into effect and the limit is not set.

6. Calculation of coefficients, risk groups and risk qualification based on the developed coefficient analysis. Such a classification of insolvency risk as minimal, low, moderate, increased, high was introduced, and the classification of interbank liabilities was given as standard, non-standard, doubtful, dangerous and hopeless. These categories of classification are used by analysts of other departments when determining the amount of provisions created for loan debt, which is ultimately reflected in the profitability of the bank. In addition, the coefficient analysis allows not only to weigh and evaluate individual active and passive operations, but also to show the sources of funding for active operations, their urgency, indicate the sources of repayment of possible losses, the degree of diversion own funds into non-current assets, reveal the bank's ability to satisfy the requirements of creditors with the help of liquid assets within a reasonable time, as well as determine which part of the assets is non-risk, identify the ratio of the risk of operations and their profitability.

7. The originality of the methodology lies in the distribution of assets by the degree of decreasing liquidity and determining the size of discounts in the same order, which leads to the formation of the net capital of the bank or the market value of assets, which are used in the assessment of regional banks in the event of their purchase or merger.

8. Based on the methodology, a bank development forecast is determined, which is communicated to other departments that provide banks to partners with non-treasury products (for example, when issuing plastic cards or opening Nostro accounts).

9. The generalized analysis data based on the methodology made it possible to evaluate two main indicators - the risk and profitability of operations, and to prove that the risk is not always justified, and its increase does not always adequately affect the profitability.

10. Stop indicators have been introduced, in the presence of which the bank is not considered as an applicant, which greatly facilitates the work of analysts, especially in branches. The stop indicator is applied when the value of the synthetic coefficient is from 0 to 40, when classifying the risk of insolvency as high.

I. Equity capital is taken as the basis for the risk of insolvency, since it is he who, performing a protective function, allows the bank to resist in the event of crisis situations. Insufficiency of capital entails not only financial risks, but also reputational risks, as it shows that the owners of the bank are not interested in increasing capital, carry out risky operations and have intentions in the limited life of the bank. 12. The methodology has been repeatedly tested in practice, which is especially significant in that the bank using it was able to avoid losses during the so-called "banking crisis of confidence" in the summer of 2004, suspending operations with such banks as JSCB "Credittrast", JSCB " Dialogue-Optim”, JSCB “Merit Bank”, JSCB “Style Bank”. For example, the analysis of financial data and the calculation of risk ratios for CB "Dialog-Optim" showed a greater dependence of the bank on interbank requirements, maintaining liquidity through mutual lending in the interbank market, low liquidity indicators, a significant package of illiquid valuable papers, against dependence on resources in the form of contributions individuals, a low payout ratio and a growing negative cost of net worth. Thus, the bank was assigned a negative development outlook.

3.2 Creation of economically justified reserves for operations in the interbank financial market.

The result of applying the developed methodology is the formation of a limit on interbank transactions, as well as a quantitative assessment of the risk of the counterparty bank's obligation, expressed by the risk ratio.

However, along with limiting, commercial banks also use other risk management methods for transactions in interbank financial markets. This paper presents a methodology developed by the author for calculating the necessary economic capital to cover the financial risks of a bank when operating in the interbank financial market.

The risk of a portfolio of assets placed on the interbank market lies in the probability of losses associated with a possible default of the borrower. To assess these losses, we use two indicators: expected (average) losses for the portfolio and unexpected (maximum) losses.

Expected losses are a function of the default probability of counterparty banks and the value of assets at risk that will be irretrievably lost as a result of the default of a particular bank. Such losses are predictable, relate to the costs of this type of activity and are reimbursed through the pricing mechanism for the services provided. To estimate the amount of expected losses, the indicator of the average probability of default of counterparty banks and the average share of the return of funds are used.

Unexpected losses reflect the spread of losses around their expected value (volatility), and the size of these losses is determined by the joint distribution of default probabilities of counterparty banks, taking into account the value of assets at risk. These losses can no longer be included in the cost of instruments and are compensated by the equity reserve, the cost of formation and maintenance of which, in turn, is compensated by the profitability of the services provided, adjusted for risk. To assess unexpected losses, the correlation indicator between the spread of losses for various counterparties around their average values ​​is used.

Thus, the probability of default of a counterparty bank is determined by its rating, that is, the risk ratio (probability of losses) calculated from a qualitative analysis of the bank and can take values ​​from 1 to 100%. Then the expected loss on an individual asset is defined as the product of the probability of loss and the value of the asset at risk:

ЕЫ = Аг * Рг (6) where ЕЫ - expected losses,

A1 - the value of the asset at risk, determined by adjusting the value of the asset by the amount of partial recovery of value in the event of a default, for example, through the sale of collateral, the execution of guarantees, etc.

M is the probability of loss.

Then the expected losses on the portfolio of assets are equal to the sum of the expected losses on a separate asset: N YAi*Pi

7) j=i where ELp - expected portfolio losses.

Further, it should be noted that within the framework of this methodology, unforeseen losses on a portfolio of assets are defined as the excess of the maximum possible losses on a portfolio of assets, at a reliability level of 99%, over the expected losses of the portfolio. In this case, the maximum losses for the portfolio are determined taking into account the correlation of assets included in the portfolio.

This follows from next moments:

1. The maximum loss probability for an individual asset included in the portfolio can be determined by evaluating the empirical loss probability distribution function of this asset using the Value at Risk method, that is, finding the maximum loss probability (VAR) with a given probability (confidence level): where Р - the maximum value of the loss probability distribution density function,

1 - SS - confidence level.

The confidence level is set at 99%, according to the recommendation of the Basel Committee on Banking Supervision.

2. To simulate the empirical loss probability distribution function for a separate asset, it is proposed to use the Monte Carlo Method, that is, random processes are simulated by a pseudo-random method with given

Vxob(VAR>P) = \-a (8) with parameters: the mathematical expectation of the loss probability and the standard deviation of the probability. At the same time, these indicators are calculated based on the dynamics of changes in the rating of the counterparty's bank (probability of loss) based on retrospective data.

3. Then the maximum level of losses for an individual asset is found by multiplying the corresponding value of the VAR by the value of the asset at risk:

Maxy \u003d L * UASH

9) where MAXY - the maximum level of losses / assets with a given confidence level,

VAS - the maximum probability of loss / asset, A1 - the value I of the asset at risk.

3. The value of the maximum losses for the asset portfolio MaxLp, taking into account the correlations of changes in the ratings of counterparty banks, is found as the square root of the product of the column vector (i.e. the transposed row vector) of the maximum individual losses, the correlation matrix and the row vector of the maximum individual losses:

Max Max1\ Max4 1

K\,n-\ Kr,n-\

L-1.L n- \, n 1 y.\MaxTs. MachTs. MaxT (10) where MaxI - the maximum level of losses I of the asset with a given confidence level,

K is the correlation coefficient between the respective assets.

MaxLp is the maximum loss for a given portfolio of interbank financial assets with a given level of confidence. Thus, the amount of funds required to cover unforeseen losses (Credit VaR) can be determined:

CreditVaR - MaxLp - ELp (11)

Credit VaR reflects the required amount of the equity reserve against unforeseen losses with a given level of confidence.

The implementation of this technique is carried out as follows:

1. At the first stage, the ratings of counterparty banks and risk ratios are determined, the obligations of which are included in the portfolio. The values ​​are determined for the last year, that is, for the last 12 reporting dates. The choice of this period of the retrospective range is due to the peculiarities of banking activities and the structure of the interbank financial market. In our opinion, it is precisely with this range that it is possible to determine with sufficient reliability the main trends in the development of the bank and identify its problem areas. The choice of a longer period of analysis is not optimal due to the influence of historically distant data on the final indicator.

Let's analyze the portfolio of assets of a commercial bank at risk, worth 5,870 USD LLC, with the following structure:

Conclusion

Risk, being historical and economic category, initially had a mathematical expression, and then was already transferred as a choice of the optimal solution to certain aspects of social and economic life.

Financial risks arose with the advent of monetary circulation and borrower-lender relationships. Adam Smith was the first to single out "risk payment" in the structure of entrepreneurial income in the form of compensation for the possible risk associated with entrepreneurial activity. Other scientists, including Russian ones, developed further theoretical basis risk.

Having studied various approaches to the definition of financial risks, we found that risk is associated with action, with choice, and there is a deviation from the goal. Thus, the characteristic features of risk are uncertainty, probability and action.

Having studied and summed up the opinions of Western and Russian scientists, we have refined the definition of financial risks in the activities of credit institutions as follows: external and internal factors of development in the conditions of uncertainty of the economic environment.

This definition reflects the basic concepts that characterize the category of risk (uncertainty in decision-making, the likelihood of a negative or positive situation, and links the risk with the activities of a credit institution and the influence of independent factors on it). A new point in the above definition is the probability of earning income.

To account for and manage banking risks, it is necessary to classify them. Risk classification means the systematization of a set of risks on the basis of any signs and criteria that allow combining risk subsets into general concepts. To clarify the classification of risks, we have developed a number of our own criteria that the risk system must satisfy: compliance with the purpose of a particular organization, attitude to regulation, terms of the transaction, convenience of the risk system, belonging to active or passive operations.

All scientists involved in the problems of risk management offer their own classifications, however, they proceed from the characteristics banking risks, proposed by Peter S. Rose, who identifies six main types of risk (credit, unbalanced liquidity risk, market, interest, profit risk, insolvency risk) and four additional risks (inflationary, currency, political, abuse risk).

After analyzing various forms and types of risk classification, we found that each bank is characterized by the main types of risks named above, but at the same time, each credit institution has its own set of risks, depending on the specifics of its activities (for example, banks specializing in retail, innovations, interbank operations, servicing foreign trade operations).

We believe that the classification of banking risks should be based on common map risks, and each credit institution refines and supplements it depending on the profile of its activities.

Once the classification of risks has been determined, they can be managed. The risk management system is a scientific and methodological set of measures for managing a credit institution, aimed at identifying and assessing risk, using specific techniques and methods in order to create conditions for the sustainable functioning of the bank, maximize equity capital, meet the requirements of customers and partners of the bank and ensure its profitability. activities.

The risk management system is aimed at ensuring an optimal ratio between the profitability of banking operations and their riskiness, maintaining liquidity at a sufficient level while optimizing the volume of profits, and meeting equity capital adequacy standards.

The risk management system in relation to banking risks performs methodological, analytical, regulatory, and control functions. The functions are performed through the stages of financial risk management: identifying the risk and the causes of its occurrence, assessing the risk and possible losses, making a decision on accepting or rejecting the risk, implementing regulatory actions on the risk by using management methods (monitoring, setting standards and limits, diversifying operations , formation of a sufficient level of reserves to cover losses, hedging), organization of the process of control and monitoring.

One of the main profitable operations of banks is operations in the interbank financial markets. Operations carried out by banks in the interbank financial markets are divided depending on the entity with which the operations are carried out, and by the type of operation. Participants of the interbank financial market provide each other with interbank loans or deposits, carry out conversion operations and banknote transactions, term transactions (Forex, Spot), operations with securities, account for and avalize promissory notes of counterparty banks, carry out documentary operations (issuance and acceptance bank guarantees(guarantees) confirmation of uncovered letters of credit) and REPO operations.

In the interbank financial market, banks manage payment risk and liquidity risk, for which they develop special methods for assessing the financial condition of counterparty banks in order to reduce the risk of failure by the counterparty bank to fulfill its obligations on time and in full, increase turnover in the interbank financial market by increasing the volume of transactions and expanding the reliable circle of banks, and, consequently, increasing profitability.

In world practice, various methods for assessing the financial condition of counterparties are used, the most famous of which is the American CAMELS system. These methods are based on the assessment of the financial condition of the bank according to selected criteria, which ultimately come down to the analysis of capital adequacy, liquidity, asset quality, risk assessment and management quality. However, the applicability of Western methods in Russian practice is not always possible and justified, which is due to the peculiarities of development banking sector Russia and the specifics of the functioning of the financial markets of Russia and Western countries.

The paper studies Russian methods of analyzing the financial condition of banks, reveals their advantages and disadvantages. Since they do not assess the risk of accepting an interbank obligation and are not suitable for monitoring the financial position of a counterparty bank, the paper proposes a method developed and tested in practice for calculating the limit on interbank transactions. The objective of the methodology is the quantitative and qualitative assessment credit risk a bank arising from transactions in the interbank financial market and the securities market. Quantitative risk assessment involves the calculation of the total (cumulative) acceptance limit monetary obligations counterparty bank for credit transactions and non-credit transactions - foreign exchange, operational, market, etc. Qualitative assessment involves the definition of a risk group.

In the methodology, the process of analyzing the financial condition of the bank is divided into several stages: the formation of the consolidated balance sheet of the bank, the net structure of assets and liabilities, determining the amount of the net capital of the bank, determining the size of the limit for accepting monetary obligations of the counterparty bank and drawing up an analytical report on the financial condition of the counterparty.

The methodology is close to international reporting standards, which is confirmed by the practice of cooperation with banks in Kazakhstan, Belarus and Ukraine.

As one of the methods for calculating indicators, the method of netting accounts of individual accounting accounts is proposed. The concept of net balance, introduced into the practice of analysis, makes it possible to identify banks as net creditors and net borrowers, the risk of solvency for which is different. The limit is calculated from the bank's own working capital and the bank's net capital.

Based on the coefficient analysis, the risk group is determined, the qualification of the risk of insolvency is derived, and the classification of the interbank liability is given. In the future, these data are used by analysts from other departments of the bank when determining the amount of provisions for loan debt. The ratio analysis also shows the sources of funding for active operations, their urgency, determines the sources of repayment of possible losses, the degree of diversion of own funds into non-current assets, reveals the bank's ability to satisfy creditors' requirements with the help of liquid assets within a reasonable time, and also determines which part of the assets is represented by non-risk ones, determines the ratio of the risk of operations carried out to their profitability.

Based on the methodology, a bank development forecast is determined, which is communicated to other departments that provide non-treasury products to partner banks (for example, when issuing plastic cards or opening Nostro accounts).

The introduced stop indicator filters applicant banks before analysis, which greatly facilitates the work of analysts, especially in branches. Equity capital is taken as the basis of the risk of insolvency, since it, performing a protective function, allows the bank to withstand in case of crisis situations. Insufficiency of capital entails financial and reputational risks, as it shows that the owners of the bank are not interested in increasing capital, carry out risky operations and have intentions in the limited life of the bank.

To assess the possible losses of a commercial bank when operating in the interbank financial market, two indicators of losses are used: expected and unexpected. This division is due to different economic importance these indicators:

Expected losses are a forecast value and are charged to the expenses of this type of banking activity; for their assessment, the value of the risk coefficient for a particular bank, calculated according to its latest rating, is used.

Unexpected losses are characterized by the maximum possible loss for each asset, and to determine such losses for the portfolio, correlations between the ratings of counterparty banks are taken into account. These losses are compensated at the expense of own capital, which is formed from the profitability of banking activities.

To determine the value of the maximum loss for an individual asset, the method of modeling random Monte Carlo processes is used.

An analysis of the maximum losses for the relevant asset makes it possible to identify the most risky borrowers and form additional requirements for limits for a particular counterparty bank.

In the developed methodology, unforeseen losses on a portfolio of assets are defined as the excess of the maximum possible losses on a portfolio of assets, at a reliability level of 99%, over the expected losses of the portfolio. At the same time, in order to take into account correlations between changes in bank ratings, a correlation matrix is ​​built that takes into account the relationship between changes in the corresponding ratings of banks.

To characterize the amount of own funds required to cover unforeseen losses in the portfolio, the Credit VaR indicator is used, which reflects the total risk of the portfolio. To assess portfolio risk and individual values ​​for each financial asset, taking into account their profitability, we suggest using the RAROC (Risk Adjusted Return on Capital) indicator, which determines the risk-adjusted return on capital. Comparing the value of this indicator for each asset with the value for the portfolio, a conclusion is made about the profitability of an asset relative to the average value.

The RAROC indicator is used when comparing the profitability and riskiness of various types of bank activities, to determine priority areas for development and identify the most problematic areas in current activities credit organization.

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124. Share of IBC in assets (million rubles)

125. Name of the bank 01.01.2001 01.01.2002 Change from the previous year 01.01.2003 Change from the previous year 01.01.2004 Change from the previous year Change from 01.01.01

126. IBC Share in Assets, % IBC Share in Assets, % IBC Share in Assets xv% IBC Share in Assets, %

127. Alfabank 19,305.40 17.80 18,299.40 18.60 -5.21% 38,919.90 27.00 112.68% 8,229.70 4.60 -78.85% -57.37%

128. Bank of Moscow 3,044.00 7.10 3,453.90 5.50 13.47% 10,599.00 11.10 206.87% 1,392.20 1.00 -86.86% -54.26%

129. Rosbank 1,818.00 4.00 5,213.50 7.80 186.77% 5,101.30 7.70 -2.15% 5,088.30 4.50 -0.25% 179.88%

130. PSB 2,101.00 9.40 4,954.10 15.20 135.80% 6,981.00 14.80 40.91% 735.80 1.10 -89.46% -64.98%

131. Uralsib 1,887.50 19.00 2,426.30 10.10 28.55% 6,923.10 15.80 185.34% 3,177.00 4.90 -54.11% 68.32%

132. City 17,378.00 55.70 19,646.50 50.00 13.05% 28,999.80 49.60 47.61% 3,844.80 6.30 -86.74% -77.88%

133. Nikoil 1,136.90 21.70 1,777.00 16.20 56.30% 3,914.10 17.40 120.26% 1,357.40 4.10 -65.32% 19.39%

134. Transcredit 581.90 8.50 386.30 4.10 -33.61% 625.80 4.00 62.00% 1,615.00 5.60 158.07% 177.54%

135. Rus. Standard 284.80 23.10 313.00 9.30 9.90% 1,393.70 24.80 345.27% 25.20 0.20 -98.19% -91.15%

136. Vanguard 1,187.80 24.10 1,325.60 20.80 11.60% 1,387.90 15.40 4.70% 793.30 5.40 -42.84% -33.21%

137. KMB 1,307.50 76.20 3,016.80 80.90 130.73% 3,178.90 59.20 5.37% 742.20 9.50 -76.65% -43.24%

138. IBRD N.D. N.D. 574.50 5.60 N.D. 1,497.60 14.20 160.68% 1,038.60 5.00 -30.65% N.A.

139. Nizhegoro PSB 20.60 0.70 87.50 2.50 324.76% 558.30 11.10 538.06% 119.20 1.90 -78.65% 478.64%

140. VTB 17,185.20 15.50 45,488.20 30.40 164.69% 43,148.30 24.50 -5.14% 29,088.00 11.30 -32.59% 69.26%

141. MDM 10,294.10 40.80 14,644.10 44.50 42.26% 28,696.20 35.20 95.96% 6,012.70 5.70 -79.05% -41.59%

142. Menatep 2,179.30 9.70 2,643.70 9.80 21.31% 4,479.70 12.30 69.45% 556.40 1.50 -87.58% -74.47%

143. Petrocommerce 951.60 8.50 2,217.90 9.70 133.07% 4,044.50 12.60 82.36% 680.50 1.50 -83.17% -28.49%

144. Zenith 649.00 7.20 1,763.80 10.50 171.77% 2,515.70 11.30 42.63% 1,558.90 5.20 -38.03% 140.20%

145. Nomos 1,699.00 23.60 3,193.40 22.60 87.96% 3,685.70 19.20 15.42% 2,313.10 7.50 -37.24% 36.14%

146. Promsvyazbank 316.20 5.50 962.80 8.20 204.49% 1,733.50 7.50 80.05% 3,286.20 8.80 89.57% 939.28%

147. Commerzbank 1,187.20 43.80 5,262.00 78.00 343.23% 12,318.10 81.80 134.10% 2,854.40 10.80 -76.83% 140.43%

148. Absolute 663.60 30.10 862.00 25.60 29.90% 1,103.40 26.50 28.00% 797.10 9.30 -27.76% 20.12%

149. Omsk PSB 6.70 0.30 21.60 0.80 222.39% 132.30 3.50 512.50% 30.10 28.80 -77.25% 349.25%

150. Cedar n.d. n.a. 25.00 1.20 N.D. 72.10 2.70 188.40% 10.60 0.20 -85.30% N.A.

151. Yeniseisk. United Bank N.D. n.a. 53.50 6.90 N.D. 45.90 3.20 -14.21% 340.80 22.00 642.48% n.a.

152. Southern trade n.d. n.a. n.a. I.D. N.D. 118.40 13.70 n.d. n.d. | N.D. N.D. n.a.

153. Share of borrowed interbank loans in liabilities (million rubles) m 91.91.ZWS 1.91.2004 1.99.2 004 91.97.2004

154. MBK Dm** p-M MBK 1! i- Dm * "Shsavi Lmash Pu Sh "n- t MBK Dm" "1. MBK thousand" t<. %% щиН. %% тые.»т«. шитС. %%

155. VTB 175 917446.00 431 483.00 0.25% 256 938 146.00 52 284 783.00 20.35% 286 599 909.00 61 080594.00 21.31% 299 632 771.00 628

156. R"<«ы« (б 049 501,00 5 101 345.00 7.72% 113 025 322,00 7 348 338.00 6,50% 111 765 021.00 8 857 019,00 7,92% 116 760 862,00 5 893 622,00 5,05%

157. MDM 81 579480.00 28 696 150.00 35.18% 105 564 798.00 41 388 045.00 39.21% 116 448 561.00 50321287.00 43

158. MMB 79,343,036.00 6,505,902.00 8.20% 83,774,375.00 9,293,067.00 11.09% 94,001,775.00 9,647,271.00 10.26% 90,853 654.07 13

159. CITY 58 507 923.00 28 999 797 00 49.57% 61 ose 9bb.oo 23 751 545.00 38.94% 59 447 2 52.00 18 248 704.00 30.70% 65 566 485.00 198 5.00 %

160. Pprvtm. 32,155,277.00 4,044,499.00 12.58% 44,320,135.00 1,074,843.00 2.43% 46,656,990.00 7,939,652.00 17.02%

161. DNB 31 519432.00 2 084 091.00 6.61% 25 010341.00 12 639734.00 50.54% 29 592 619.00 13 006174.00 43.95% 28 649 690.00 17.60 12 803

162. Trikkuedagt 15 581 201.00 625 751.00 4.SE% 28 949978.00 751 613.00 2.60% 5 284 669.00 2 499 236.00 47.29% 26 930 707.00 1 44.5% 55.00

163. K “” m “Rkbazh 15 067 036.00 12 318 145 00 81.76% 26482448.00 22 968 666

164. AzhBa* « 14 957 52\.00 V 209066.03 8.08% 22.012621.00 1 854 159.00 8.42% 30 588 215.00 1 405 093.00 4.59% 32 782 600.00 70.350 1 096

165. IBRD 10,542,230.00 1497,558.00 14.21% 20,838,454.00 1,825,949.00 8.76% 17,196,732.00 2,859,802.00 16.63% 18,923,907.00 35.700 35.700 35.700

166. RBR 6443 381.00 635 780.00 9.87% 7 994 726.00 1 919482.00 24.01% 6 730017.00 794 280.00 11.80% 1 236 061 00 816 236.00 66.04%

167. M*<ж^феа.бамг 6121 401.00 384 272.00 6.28% 10 312 066.00 1 775 230,00 17^2% 9221 311.00 143 626,00 1.56% 9 238 218.00 1 277 246.00 13.83%

168. M Ruesk. Spp. 5612638.00 1393748.00 24.83% 15404308.00 5175951.00 33.60% 21744137.00 8914687.00 41.00% 22486393.00 9370 41.7%

169. A(yazht 5 182 552.00 1 103 378.00 21.29% 8 530 242.00 2 480112.00 29.07% 10 036117.00 2 714 341.00 27.05% 9 768 009.00 60.423

170. Nyakhpgm LSB 5,032,782.00 558,346.00 11.09% 6,147,379.00 900,467.00 14.65% 6,880256.00 882,894.00 12.83% 129,371.00 440 417.0%

171. UBRD 4,739,376.00 26″, 578.00 5.58% 7,782,346.00 386,376.00 4.96% 9 SE6,221.00 1,341,572.00 14.86% 140469.00 465,855.00 5.72%

172. UVTB 4,552,616.00 1,256,419.00 27.60% 6,287 8 97.00 917,885.00 14.60% 6350835.00 807,416.00 12.71% « 156,735.00 682,089.00 11.08%

173. Ch'-ya 4,288,528.00 38,822.00 0.91% 6,262,523.00 160,904.00 2.57% 7,334,512.00 246,605.00 3.36% 7,318,071.00 173,829.00 2.38%

174. Tshrpshm E 481,508.00 206,621.00 5.93% 5,065,311.00 129,399.00 2.55% 7,268,222.00 87,113.00 1.20% 7,296462.00 87,244.00 1.20%

175. Ripvzh 3,377,820.00 2,312,353.00 68.46% 4,508,710.00 E 129,551.00 69.41% > 959,612.00 3,583,031.00 60.12% 5,462,633.00 4,083,823%

176. E 247 886.00 508 427.00 15.65% 3 556438.00 237 117.00 6.67% 4 136722.00 512 095.00 12.38% 4 277 962.00 515 727.06% 31 3 022 788.00 506 804.00 16, 77% 5,103,606.00 1,338,416.00 26.22% 5,924,409.00 1,099,780.00 18.56% 6,262,289.00 1,210,388.00 19.33%

177. S K "" 2,661,199.00 72 14,000 2.71% 4,251,182.00 4,687.00 0.11% 5,503 V 64.00 9,562.00 0.17% 5,613,717.00 3,084.00 0.05 %

178. For"""< 2 345 970,00 6.00 0.00% 1 194 208.00 0,00 0,00% 1 951240,00 0,00 0,00% 1 735 353.00 0,00 0,00%

Yarov feet 1 615 578.00 0.00 0.00% 2 525 140.00 18 500.00 0.73% 2 437 695.00 25 200.00 1.03% 2 470914.00 5 190.00 0.21%

180. Eat. yoga<ж 1 429002,00 45 902,00 3.21% 1 545 861,00 102 431.00 6.63% 2 166 932,00 82 607.00 3,81% 2 518 141,00 77 549.00 3.08%

181. Mmp*pim 1 032 401.00 15 106.00 1.46% 1 227 331.00 11 48 9.00 0.94% 1 562 755.00 95 033.00 6.08% 1 452 148.00 99 152.00 6.83%

182. RNKB 987 787.00 YP 9^2.00 9.92% 145! 171.00 375 651.00 25.8-9% 144 140.00 20L 401.00 "7.87% 109* 293.00 150 600.00 17.42%

183. M Mo. Bayak Aer. 48 9 787.00 166 103.00 33.91% 678 891.00 299 607.00 44.13% 806 705.00 366 906.00 45.48% 802 695.00 434 570.00 54.14%

184. Khshmom 347,781.00 0.00 0.00% 518,422.00 0.00 0.00% 619,050.00 7,006.00 1.13% 606,737.00 18.00 0.00%

185. See* K.D. K.D. 23 952 106.00 4 375 413.00 18.27% 26 132 061.00 6 28 9 081.00 24.07%

186. Tsaium ^ dat te.*. I. A 16 586273.00 g 336,787.00 14.09% 12,356,910.00 1,309,775.00 10.60% 17 141 303.00 30 141.00 0.18%

187. Smipmg K. Ya. 5 026887.00 759 843.00 15.12% 6 592 587.00 583 1 65.00 8.85% 7 192 800.00 545 978.00 7.59%

188. Gch> "gm, Ya. Ya- k. Ya. 4,355,518.00 1,801,242.00 41.36% 4,326,320.00 1,755,320.00 40.57%

189. Taletteom. M.Ya. N-I-k.l. E 286593.00 2,091.00 0.06% 3,836,042.00 71,329.00 1.86%

190. Oi "-PSB *-I 5,238,108.00 94,119.00 1.80% I-I. I1 m.d. M-Ya Yap

191. Bask S-P 12 556221.00 1 751 731.00 13.95% 13 135 628.00 59*5 00! .00 4.54% 13,311,974.00 540,137.00 4.06%

192. A "" sch-" rd n-a. 14,561,385.00 2,137,203.00 14.68% 15,917,722.00 2,487,696.00 15.63% 14,799,139.00 I 438,286.00 9.72%

193. Consolidated calculation of the cost of banks as of 01.01.2003. (thousand rubles) Negative cost

194. Caik; assets net worth

195. Imnexbank 14,214,604.00 948,207.00 2,632,010.00 36.03% 80.44

196. Petrocommerce 32,155,277.00 ¡35,993.00 6,658,609.00 2.04% 80.00

197. Ak Bars 14957 521.00 561 617.00 3 110 049.00 18.06% 77.63

198. Chelind 4,288,528.00 138,911.00 710,314.00 19.56% 76.00

199. Northern Kasha 5,111,614.00 484,138.00 556,392.00 87.01% 74.25b Mosk. credit. bank 6,121,401.00 1,475,259.00 1,530,229.00 96.41% 73.50

200. ABN Amro 14,353,383.00 248,492.00 1,722,176.00 14.43% 72.81

201. Dialogue-optnm 6,807,965.00 267,413.00 1,311,192.00 20.39% 72.69

202. Nomos 19,246,695.00 436,983.00 4,407,281.00 9.92% 72.56

203. CITY 58,507,923.00 4,161,046.00 6,481,931.00 64.19% 72.13

204. Tssngr-Iniest 3,022,788.00 105,299.00 623,922.00 16.88% 71.56

205. Cedar 2,661,199.00 232,882.00 340,602.00 68.37% 71.31

206. Omsk-PSB 3,821,251.00 458,509.00 506,288.00 90.56% 70.81

207. Uralsib 43,706,733.00 3,191,944.00 8,630,698.00 36.98% 70.50

208. Me bo dok pal 1,032,401.00 132,365.00 135,932.00 97.38% 70.06

209. Sberbank 1,081,784,306.00 105,958,449.00 126,820,307.00 83.55% 70.00

210. Raiffeisen 42,477,183.00 4,710,646.00 2,882,405.00 163.43% 69.63

211. Gazprombank 153,554,763.00 21,498,911.00 20,288,783.00 105.96% 69.13

212. Regnobank! 896,529.00 164,402.00 174,890.00 94.00% 68.75

213. Russian. general, ball to 7 448 238.00 557 617.00 914 023.00 61.01% 67.81

214. Nikoy l 22,478,516.00 477,322.00 6,458,471.00 7.39% 67.56

215. UVTB 4,552,616.00 588,132.00 403,863.00 145.63% 66.13

216. Yarsotsbank 1,615,578.00 98,120.00 263,412.00 37.25% 65.81

217. Eurofinance 23,429,610.00 857,818.00 3,264,591.00 26.28% 65.75

218. Industry 23,223,869.00 3,653,534.00 2,772,942.00 131.76% 64.63

219. Tauride 3,481,508.00 160,439.00 720,994.00 22.25% 64.25

220. Metallinvest 4,892,235.00 245,284.00 1,324,290.00 18.52% 64.19

221. South Trade 863,160.00 65,347.00 168,092.00 38.88% 63.44

222. Gas bank 3,770,267.00 605,478.00 374,621.00 161.62% 61.88

223. District 2,345,970.00 37,539.00 382,189.00 9.82% 61.44

224. Menatep 36,287,136.00 6,721,055.00 2,763,731.00 243.19% 60.50

225. Intern rum 5,389,078.00 668,410.00 460,045.00 145.29% 60.44

226. RRRR 4,739,376.00 504,954.00 757,759.00 66.64% 60.13

227. Probusinessbank 7,478,249.00 675,798.00 1,089,693.00 62.02% 59.56

228. MDM 81,579,480.00 12,553,155.00 8,434,980.00 148.82% 59.50

229. Far East 2,340,647.00 216,252.00 28 6,363.00 75.52% 59.25

230. Veet LB 8,720,242.00 552,294.00 770,702.00 71.66% 59.19

231. Zenith 22,358,135.00 4,024,305.00 2,689,527.00 149.63% 58.50

232. Alpha 143,992,371.00 15,489,475.00 24,629,827.00 62.89% 57.88

233. PSB 47,057,414.00 7,072,911.00 4,114,093.00 171.92% 57.69

234. Bank of Moscow 95,425 ¡63.00 17,806,676.00 9,845,763.00 180.86% 57.19

235. KME 5,370,317.00 989,637.00 403,570.00 245.22% 57.00

236. Russian Standard 5,612,638.00 387,447.00 1,255,385.00 30.86% 56.75

237. Cr.Lions 7,267,571.00 539,341.00 1,359,633.00 39.67% 53.69

238. IMB 79,343,036.00 8,891,200.00 4,758,857.00 186.83% 51.19

239. Traccredit 15,581,201.00 1,087,709.00 2,504,439.00 43.43% 50.8848 div 31,519,432.00 6,936,832.00 5,174,138.00 134.07% 50.00

240. Rosbank 66,049,501.00 12,012,962.00 10,292,005.00 116.72% 48.061. Positive value

241. Buy* actins COST capital rate/capital ray 1 msh

242. RNKB 987,787.00 206,272.00 406,173.00 50.78% 83.13

243. VTB 175,917,446.00 ¡2,966,413.00 57,095,912.00 22.71% 82.06

244. Rossslkhoz 9,015,884.00 2,055,471.00 3,799,000.00 54.11% 81.63

245. Kras Bai k 3,247,886.00 381,874.00 1,030,728.00 37.05% 79.50

246. Cr. Swiss 9,765,813.00 2,160,074.00 2,192,849.00 98.51% 76.63

247. Orgres 5,037,038.00 979,836.00 1,880,929.00 52.09% 76.44

248. IBRD 10,542,230.00 616,475.00 2,856,420.00 21.58% 76.38

249. RDB 6,443,381.00 3,984,620.00 5,356,279.00 74.39% 76.31

250. Int. Bank Azerbaijan 48U 787.00 230,522.00 315,797.00 73.00% 75.75

251. P Absolute 5,182,552.00 348,133.00 1,304,814.00 26.68% 75.63

252. Nizhny Novgorod PSE 5,032,782.00 133,446.00) 372,991.00 9.72% 73.06

253. Yong not. merged I 429,002.00 42,139.00 286,979.00 14.68% 71.81

254 Deutsche 12,279,807.00 846,478.00 2,717,684.00 31.15% 69.13

255. Ripablnk 3,377,820.00 192,498.00 820,062.00 23.47% 68.63

256. Khakassia 347,781.00 13,625.00 99,313.00 13.72% 66.81

257. Consolidated calculation of the cost of banks nl 01.01.2004 (thousand rubles)1. Returns: p.i.p. cost

258. The bank's assets by clearing the bank account. capital st/capshad ■ rating

259. Euro fi is ours; 20,256,318,134,259 3,388,683 3.96% 79.69

260. Imi ikeban k 15,989,714,889,206 3,032,982 29.32% 79.31

261. Northern Treasury 5 498479 390 191 670 627 58.18% 75.88

262. Petrocommerce 33,140,830 450,019 6,920,662 6.50% 75.25

263. Ak Bars 17,882,857 1,319,873 3,069,898 42.99% 75.06

264. Southern Trade 919,435 80,718 158,713 50.86% 74.63

265. Persons IND 4,673,695,256,168,752,678 34.03% 74.00

266. Xlr 3,098,018 230,290 374,828 61.44% 73.75

267. Raiffweisea 50,453,171 5,944,477 3,163,157 187.93% 72.38

268. CITY 51,597,856 2,872,916 7,459,951 38.51% 71.75

269. Regiobank 1,884,004,216,334,185,811 116.43% 69.25

270. Gazprombank 189,943,120 27,100,675 21,204,441 127.81% 68.94

271. Gazbank 4,630,884,567,257,428 2X0 132.45% 68.56

272. Menatep 41,614,352 6,605,050 3,453,093 191.28% 68.06

273. Dialog-optim 7,315,077,758,266 1,323,191 57.31% 67.13

274. AEN Amro 14,427,919,835,023 12,053,120 6.93% 66.88

275. Wem LB 8,989,872,428,695,902,892 47.48% 66.69

276. Uralsib 49,203,226 4,375,856 9,692,062 45.15% 66.56

277. Moscow credit, bank 6,827,362 1,041,686 1,537,045 67.77% 66.56

278. Commsbank 18,151,205 2,862,497,726 361,394.09% 66.56

279. UVTB 4,912,563,735,673,424,156 173.44% 66.25

280. Nomos 22,771,043 1,522,423 4,329,430 35.16% 65.88

281. Center-Invest 2,624,840,325,475 637,963 51.02% 65.56

282. Omsk-PS B 4,247,435,536,718,566,889 94.68% 64.56

283. Tavrichesky 4,374,629,326,473,735,720 44.37% 64.062

284. PS B 54,021,030 7,047,444 4,566,808 154.32% 62.25

285. Granscredit 18,866,984 1,470,137 2,688,172 54.69% 61.56

286. Alfa 156399740 17,980,934 24,352,572 73.84% 61.503 Yarsotsbank 1,574,780 100,412 278,920 36.00% 60.25

287. Promsvyaz 22,734,589 3,738,299 2,893,110 129.21% 59.94z: Intern rom 5,775,811,943 100,473,337 199.24% 58.31

288. Nikoil 23,932,849,463,845 6,236,692 7.44% 57.06

289. IBRD 20,672,592 2,272,622 2,996,253 75.85% 56.94

290. Zenith 24,349,036 4,202,709 3,067,571 137.00% 56.56

291. Bank of Moscow 109,772,211 19,564,759 10,854,449 180.25% 56.06

292. UBRD 5,541,361,724 262,750,397 96.52% 55.88

293. Far East 2,277,212,236,992 303,447 78.10% 55.06

294. IMB 79,987,432 8,667,995 4,842,397 179.00% 53.56

295. Rosbank 743,057,774 13,654,167 10,396,290 131.34% 53.25

296. KME 5,228,573,952,001 422,579 225.28% 53.00

297. MDM 86,017,884 17,023,631 8,418,642 202.21% 50.56

298. KrLione 8,751,688,882,994 1,380,027 63.98% 49.81

299. Vanguard 9,592,209,589,990 2,022,852 29.17% 48.75

300. DIB 40,869,440 11,631,691 6,088,619 191.04% 47.061. Positive value

301. Bap!| SG1 | "NM stonmisga: kishggal et-t'/kyashpal reshshi

302. VTB 204 793 35! 16,974,512 60,894,729 27.88% 91.63

303. Absolute 5,882,637 269,949 1,309,173 20.62% 83.38

304. Khakassia 318,779 30,116,101,300 29.73% 80.50

305. RNKB 1,352,464,203,111,503,491 40.34% 80.00

306 Russian Standard 5,987,606 207,596 1,800,542 11.53% 79.13

307. Kras Bank 2,982,457 201,245 1,049,851 19.17% 76.94

308. Cr. Swiss U 708,481 2,366,400 2,399,165 98.63% 76.63

309. Orgres 5,002,567,805,140 1,880,856 42.81% 76.00

310. Rosselkoz 9,940,940 1,527,011 3,972,082 38.44% 75.81

311. Lower City PSB 5,099,946 236,715 1,522,753 15.55% 74.81

312. Mszhd, Bank A 1srbay 612 17! 251,372 318,033 79.04% 71.50

313. Metal invest 5,153,161 76,966 1,326,831 5.80% 70.31

314. Deutsches 13,427,537,391,241 2,887,127 13.55% 69.69

315. Republic 3,501,415 74,092 811,202 9.13% 68.44

316. RDB 6,478,937 4,058,583 5,526,127 73.44% 64.00 full cost calculation

317. PvccK-General Bank 45,501.00 8,980,396.00 1,733,686.00 2.62% 77.08g VTB 77,509,552.00 344,930,292.00 65,479,209.00 118.37% 77.56e Slavinvest47 .00 8,084,840.00 1,379,296.00 48.69% 75.56

318. M metal invest 234,430.00 7,147,683.00 1,643,868.00 14.26% 75.50

319. Lnkshi 1 b78,550.00 40,909,723.00 9,395,102.00 17.87% 74.57

320. Probnnessbanks 1,599,937.00 12,272,186.00 1,771,135.00 90.33% 74.25

321. Petrik Mary 4,629,218.00 45,379,130.00 7,710,771.00 60.04% 74.00

322. I HRC S0 191.00 20,790,631.00 3,812,574.00 2.10% 73.44

323. Eurofshans 2,458,482.00 33,408,372.00 5,468,305.00 44.96% 73.13

324. Russian Standard 916,763.00 26,085,369.00 5,918,774.00 15.49% 70.38

325. I MDM 10509 221.00 113 133 806.00 10 834 859.00 96.99% 70.13

326. CITY 5,753,368.00 67,856,790.00 11,215,015.00 5 1.30% 69.38

327. My fiber cash 182,109.00 1,035,561.00 129,973.00 140.11% 68.75

328. Nomos 3,555,990.00 3,469,283.00 b 376,230.00 55.77% 68.25

329. Enis obed bank 90,544.00 1,941,023.00 306,541.00 29.54% 67.31

330. Rnnablnk 118,664.00 5,738,192.00 83S 307.00 14.21% 67.19

331. ASh 535,304.00 21,591,477.00 2,337,880.00 22.90% 66.56

332. Absolute 754,622.00 9,051,480.00 1,475,671.00 51.14% 66.56

333. VgetLB 158,087.00 I 471,314.00 I 053,378.00 15.01% 66.44

334. Exchange 6,804,229.00 40,955,467.00 4,732,613.00 143.77% 66.38

335. VTB 1,167,361.00 6,443,260.00 485,010.00 240.69% 66.25

336. Toljattihi mSap k 229,476.00 3,775,173.00 707,256.00 32.45% 65.7523 81

337. Rosbank 1Ya 510,700.00 118,029,052.00 1 2,394,486.00 14935% 63.69

338. Gazprombank 32,047,876.00 242,820,144.00 29,656,816.00 108.06% 63.31

339. Zenith 6,267,449.00 41,857,200.00 4,292,974.00 145.99% 62.44

340. Wash to redit. bank 1,974,300.00 9,265,673.00 2,022,255.00 97.63% 62.31

341. Chepiml 943,702.00 7,732,875.00 924,438.00 102.08% 62.0629 leagues 2,939,710.00 27,441,721.00 5,280,456.00 55.67% 62.00

342. Yarsotsbaik 296,661.00 2,390,511.00 263,770.00 112.47% 61.56

343. Alpha 15,757,394.00 162,571,040.00 31,451,640.00 50.10% 60.63

344. Tauride 747,754.00 6,951,162.00 1,169,135.00 63.96% 60.50

345. Menatep 2,052,578.00 23,324,673.00 3,303 1 51.00 62.14% 60.50

346. Imtksbaik 4,329,078.00 28,746,186.00 3,291,090.00 ¡3154% 60.19

347. BankS-P 1,977,622.00 14,151,477.00 ! 304,495.00 151.60% 60.0636

348. Uralsnb 7,586,136.00 75,128,150.00 12,481,616.00 60.78% 59.69

349. Ak Bars 5,131,252.00 32,141,559.00 3,780,322.00 135.74% 59.36

350. MME 16,407,587.00 103,425,215.00 7381,851.00 222.27% 59.13

351. Vanguard 1,152,890.00 ¡4,602,636.00 2,987,455.00 38.59% 58.63

352. Intern rum 1,216,636.00 8,509,545.00 729,616.00 166.75% 58.31

353. Gazbank 1,045,792.00 6,309,834.00 566,727.00 184.53% 57.25

354. Ce) credit 1,257,165.00 11,850,211.00 3,025,358.00 41.55% 57.19

355. IBRD 2,036,350.00 19,567,643.00 3,102,771.00 65.63% 55.75

356. Northern Kazhi 1,470,074.00 8,897,317.00 985,639.00 149.15% 54.56

357. Union 5,619,423.00 29,972,698.00 4,240,667.00 132.51% 54.00

358. Raiffeichem 11,773,479.00 72,179,227.00 5,592,680.00 210.52% 53.94

359. Bank of Moscow 23,773,261.00 134,822,790.00 13,504,731.00 176.04% 52.69

360. Kommsrnbank 5,172,000.00 27,307,781.00 1,394,725.00 370.83% 52.06

361. PSB 12,505,839.00 74,883,401.00 7,597,587.00 164.60% 51.56

362. RRRR 1,253,130.00 7,590,593.00 862,598.00 145.27% 51.13

363. KM B 1,657,630.00 8,880 165.00 677,318.00 244.73% 47.63

364. Kr.Lnonp 999 S65.00 8,300,827.00 1,352,207.00 73.94% 41.501. Positive value

365. S tsr shish B ««* assets cost sg-t/kaiital rating

366. RNKB 332 168.00 995 629.00 549 125.00 60.49% 78.19

367. Orgrzs 454,743.00 7,833,779.00 2,072,347.00 21.94% 77.25

368. Garant 127,053.00 3,838,157.00 957,383.00 13.27% 77.13

369. On account 175,850.00 1,456,742.00 552,284.00 31.84% 76.56

370. Krasbapk 326,458.00 4,054,688.00 1,262,985.00 25.85% 76.25

371. Rosselkhoa 544,553.00 16,976,250.00 4,923,232.00 11.06% 74.19

372. Morgan 1,008,882.00 5,552,232.00 1,301,063.00 77.54% 73.13

373 Deutsche 1,223,822.00 15,603,405.00 2,904,510.00 42.14% 72.88

374. Hakvssia 67,913.00 563,725.00 211,264.00 32.15% 68.81

375. To r. Vise 2 419 492.00 17019761.00 2912049.00 83.09% 68.13

376. RPR 4,046,598.00 6,775,840.00 5,912,534.00 68.44% 66.13

377. Int. Dzerbai Bank 85,281.00 1,053,378.00 325,961.00 26.16% 65.56

378. Nnzhegorod PSB 97,077.00 5,686,385.00 1,531,294.00 6.34% 60.06

379. Characterization of synthetic coefficients

380. Coefficient Coefficient name Coefficient purpose Interval Assigned Weight in final coefficient

381. CoeDDshgieitm depending on the interbank t.shk-l: Kmb

382. Km « The ratio of attracted SBS and client sources Correlation of the two main attracted sources of resources allows us to assess the balance of the bank's resource base<10% 10-25% 25-40% 40-50% >50% 50 75 100 25 0 03

383. Km b 0.ZChKmb1 + Kmb2) + 0.2*GKmb3 + Kmb4 > 0.15

384. CoeAAi ■ lent debt: Km

385. KszZ The share of problem loans in the total loan debt Characterizes the quality of the bank's loan debt<5% 5-10% 10-15% 15-20% >20% 100 75 50 25 0 0,25

386. Ksz 0.4 * Kp1 + PL5 * K (p2 + 0.25 * KszZ 0.15

387. KpeAAipneitm independence: K from

388. Knz 0.4 * (Knz1 + Ksh2) + 0.2 * KnzZ 0.2

389. Liquidity ratios: Yuis

390. KlkZ The share of highly liquid investments in assets Identifies what part of total assets is in risk-free instruments and instruments with a minimum level of risk<3% 3-5% 5-10% 10-15% >15% 0 25 50 75 100 0,2

391. Klk \u003d 0.4 * (Klk1 + Klk2) + 0.2 * KlkZ 0.2

392. Coefficients of balance stability: Kbu

393. Kbu2 The ratio of the difference between term investments and term sources to demand liabilities Estimates the degree of dependence of the bank's term investments on the most unstable obligations<0% 0-15% 15-30% 30-45% >45% 75 100 50 25 0 0,4

394. Kbu = 0.4 "(Kbu1 + Kbu2) + 0.2" KbuZ 0.2

395. Profitability ratios: Krn

396. Krn1 Profitability of own working capital Shows the effectiveness of investing own working capital in reporting period, and it is assumed that their value as a whole has an inertial character<0% 0-5% 5-10% 10-15% >15% 0 25 50 75 100 0,4

397. Krn \u003d 0.4 * Krn1 + 04 * Krn2 + P.Z "Krn.1 0.1

398. Synthetic coefficient K \u003d 0.15 * (Kmb + Ko) + 0.2 * (K1p + Clk + Kfu) + 0.1 * Krn