Determination of additional banking stability regulation factors to Basel III standard

Nowadays regulation of banking sphere is based on Basel standards which are developed by Committee on Banking Supervision of the Bank for International Settlements.

The last set of standards is called Basel III which is revision of Basel II done after financial crisis of 2008. This standard is applied in Russia as well as all over the world. [1]

Basel III is aimed at strengthening regulation, supervision and banking sector risk management (better transparency and disclosures). Generally, it means that the general aim is to make banking sector as strong as possible. [7]

Basel III has three main principles: capital requirements, leverage ratio, and liquidity requirements.

Central Bank of Russia is working on implementation of these principles. For example, Bank of Russia developed approaches to define systemically important financial institutions. The CBR defined all changes and implementations in a very detailed way. For example, the minimum level of the short-term liquidity, set at 60% (2015), said to increase in equal annual parts up to the value of 100% (1 January 2019). The same is done with capital conservation buffer and the level for the base capital, which are also minutely explained, i.e. annual level until they reach 2.5% of RWAs (from 0.625% in 2016) and 1% of RWAs (from 0.15% at 2016) respectively. Moreover, there are some additions such as possibility without any punishment to use highly liquid assets in order to cover cash outflows and then usage of the CBR irrevocable loan lines to fill back highly liquid assets. [4]

Basing not only on these measures, but on other as well, BIS reported that Russia is compliant with minimum Basel capital and liquidity standards and their framework components. [6]

BIS decisions are seen by the CBR and then published so that everybody can get the understanding. For example, in one of the reports it was announced and described that Regulatory Consistency Assessment Program recognized the CBR regulations as relevant with BCBS Basel II and Basel III standards in all aspects. [5]

However, what if these requirements are not the only one which should be paid attention to. Maybe there are some other aspects that influence Russian banks, but are not regulated. That is why there is an idea to construct an econometric model to evaluate influence of different indicators on the possibility that bank will close. Such modeling and prognostication are quite developed nowadays, and there special computer software, such as Eviews which is used for calculations shown below. Some of the indicators are included in current Basel standards and some are not. And these not included in Basel standards factors are our main aim as they could be added to the current considered indicators. [2]

The equation model and results of its estimation look like the following:

Table 1

Method: Least Squares

Included observations: 85

CL_B=C(1)+C(2)*BANKROLL_BOX_ATM+C(3)*FUNDS_SETTLEMENT+C(4)*

RES_HIGH_LIQ_ASSET+C(5)*RES_IBL+C(6)*BONDS+C(7)

*RES_BONDS+C(8)*PR_NOTE+C(9)*RES_PR_NOTE+C(10)

*LOAN_LE_RESIDENT_GE+C(11)*LOAN_PP_RES+C(12)

*IBL_NONRESIDENT+C(13)*RE

	Coefficient	Std. Error	t-Statistic	Prob.
C(1)	14.13933	3.965159	3.565892	0.0006
C(2)	-0.027109	0.006588	-4.114988	0.0001
C(3)	-0.007409	0.004768	-1.723394	0.0892
C(4)	0.433648	0.221420	1.958484	0.0540
C(5)	0.251764	0.047526	5.297454	0.0000
C(6)	0.003568	0.001196	2.983602	0.0039
C(7)	0.341321	0.090874	3.755971	0.0003
C(8)	-0.018320	0.006923	-2.646094	0.0100
C(9)	-0.930969	0.201234	-4.626307	0.0000
C(10)	0.009895	0.004907	2.016400	0.0475
C(11)	-0.017484	0.005647	-3.096243	0.0028
C(12)	-0.006301	0.001863	-3.381861	0.0012
C(13)	-0.006330	0.001623	-3.900602	0.0002
R-squared	0.709154	Mean dependent var		5.623529
Adjusted R-squared	0.660680	S.D. dependent var		3.814061
S.E. of regression	2.221736	Akaike info criterion		4.574352
Sum squared resid	355.4000	Schwarz criterion		4.947934
Log likelihood	-181.4100	Hannan-Quinn criter.		4.724617
F-statistic	14.62948	Durbin-Watson stat		2.549582
Prob(F-statistic)	0.000000

The equation is highlighted by the yellow colour, where

CL_B is the number of closed banks in Russia,

BANKROLL_BOX_ATM is bankroll held in ATMs of all banks (assets, in billion roubles),

FUNDS_SETTLEMENT is funds in settlement (assets, in billion roubles),

RES_HIGH_LIQ_ASSET is reserve on highly liquid assets (assets, in billion roubles),

RES_IBL is reserve on interbank loans (assets, in billion roubles),

BONDS is the value of bonds (assets, in billion roubles),

RES_BONDS is reserves on bonds (assets, in billion roubles),

PR_NOTE is the value of promissory notes (assets, in billion roubles),

RES_PR_NOTE is reserves on promissory notes (assets, in billion roubles),

LOAN_LE_RESIDENT_GE  is  the volume of loans  given to governmental legal entities (assets, in billion roubles),

LOAN_PP_RES is the volume of loans given to people (assets, in billion roubles),

IBL_NONRESIDENT is amount of interbank loans taken from nonresidents (liabilities, in billion roubles),

RE is retained earnings (equity, in billion roubles).

Results are based on monthly data taken from January 2010 until January 2017, which means that we have good pool of data for modern time. Data was taken from data services: 1) (financial data); and 2) (data on closed banks). It is important to add that data was taken for all Russian banks.

Now let us say several words on the model. It has high R2 which means that equation is good because the regression line well fit the data. Supporting this, result of F-statistic probability proves that equation is of high quality and R2 is not random.

All variables present in equation are significant basing on results of probability and t-test, so we should not exclude any variables.

Furthermore, using White-test, it appeared that model is not subject to heteroscedasticity, and using Durbin-Watson test for autocorrelation we cannot be sure if there is some autocorrelation or not. However, such result means that we are not obliged to reject the model, and it is possible to continue to use it.

Additionally, model performed well in adequacy test which gives us final confirmation that model is of good quality, and we can use it. [3]

Thus, the model shows that some of the reserves (word “some” is used because not all types of reserves were used) proposed by Basel III standard, such as, reserve on highly liquid assets, are really important. However, during regulation and analysis of banking, attention should also be paid to such areas as bankroll held in ATMs of all banks, funds in settlement, amount of bonds held and reserves for them, amount of promissory notes and reserves for them also, and other indicators shown and explained before. All these additional elements may be included or may be controlled more strictly in the regulation standards, as these elements influence banks in one or another way and show the level of banks healthiness and stability.

Sources:

• 1.    Альберт Бикбов, Базелева болезнь, Реальное время, 11.01.2016 URL: http://realnoevremya.ru/articles/20985

• 2.    Трегуб А.В., Трегуб И.В. Методика прогнозирования показателей стохастических экономических систем //Вестник Московского государственного университета леса – Лесной вестник. – 2008. – №2 (59). – С. 144-152.

• 3.    Трегуб И.В., Хацуков к.л. Проверка применимости модели для прогнозирования экономических показателей // Экономика и социум. 2014. № 4-4 (13). С. 1345-1349.

• 4.    Центральный банк Российской Федерации (Банк России), Пресс-служба, О мерах по реализации Базеля III и о регулировании деятельности      системно      значимых      банков      URL:

• 5.    Центральный банк Российской Федерации (Банк России), Пресс-служба, О соответствии нормативной базы Банка России стандартам Базеля      II,      Базеля      2,5      и      Базеля      III      URL:

• 6.    Basel Committee on Banking Supervision, Implementation of Basel standards, A report to G20 Leaders on implementation of the Basel III regulatory reforms, August 2016 URL: http://www.bis.org/bcbs/publ/d377.pdf

• 7.    Bank for International Settlements, Basel Committee on Banking Supervision, Basel III: international regulatory framework for banks URL: http://www.bis.org/bcbs/basel3.htm

• 8.    Banks Financial Data URL: http://kuap.ru/banks/9999/balances/

• 9.    Data          on          closed          banks          URL:

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