Risk-weighted Assets Research Articles

Funding Liquidity and Risk-Taking Behavior of Banks in India

This study, utilizing bank-level data for India, investigates the relationship between funding liquidity and banks’ risk-taking behavior. The study uses two risk measures: risk-weighted assets (encompassing credit, market, and operational risk) and liquidity creation (encompassing intermediacy risk). Findings reveal that banks with higher funding liquidity exhibit higher risk-taking behavior. This risk-taking behavior is more pronounced during economic recuperation and expansionary monetary policy phases. Notably, during economic recuperation, banks display heightened intermediacy risk, contrasting with the absence of such evidence during expansionary monetary policy phases. Larger banks with higher deposit shares demonstrate lower risk-taking behavior. Additionally, banks with a return on equity (ROE) below the average ROE exhibit a proclivity for increased risk-taking. This study advocates for liquidity regulation as a crucial complement to bank capital regulation, offering empirical support for moderate risk-taking among highly liquid banks and fortify their balance sheets for a stable banking system in India. JEL Codes: E32, E52, G21, G28

Evaluation of Total Risk-Weighted Assets in Islamic Banking through Fintech Innovations

The assessment of total risk-weighted assets (LTRWAs) in the banking sector is of the utmost importance. It serves as a critical component for regulatory compliance, risk management, and capital adequacy. By accurately assessing LTRWAs, banks can effectively meet regulatory requirements, efficiently allocate capital resources, and proactively manage risks. Moreover, the accurate assessment of LTRWAs supports performance evaluation and fosters investor confidence in the financial stability of banks. This study presents statistical analyses and machine learning methods to identify factors influencing LTRWAs. Data from Bahrain, Jordan, Qatar, the United Arab Emirates, and Yemen, spanning from 2010 to 2021, was utilized. Various statistical tests and models, including ordinary least squares, fixed effect, random effect, correlation, variance inflation factor, tolerance tests, and fintech models, were conducted. The results indicated significant impacts of the unemployment rate, inflation rate, natural logarithm of the loan-to-asset ratio, and natural logarithm of total assets on LTRWAs in regression models. The dataset was divided into a training group (90% of the data) and a testing group (10% of the data) to evaluate the predictive capabilities of various fintech models, including an adaptive network-based fuzzy inference system (ANFIS), a hybrid neural fuzzy inference system (HyFIS), a fuzzy system with the heuristic gradient descent (FS.HGD), and fuzzy inference rules with the descent method (FIR.DM) models. The selection of the optimal model is contingent upon assessing its performance according to specific error criteria. The HyFIS model outperformed others with lower errors in predicting LTRWAs. Independent t-tests confirmed statistically significant differences between original and predicted LTRWA for all models, with HyFIS showing closer predictions. This study provides valuable insights into LTRWA prediction using advanced statistical and machine learning techniques, based on a dataset from multiple countries and years.

Mapping Capital Ratios to Bank Lending Spreads: The Role of Efficiency and Asymmetry in Performance Indices

Beyond the 2007–2008 financial crisis, the collapse of the Silicon Valley Bank and the acquisition of Credit Suisse by the Swiss investment bank UBS Group AG in 2023 have brought fresh attention to the need for new regulatory capital, liquidity risk management, and leverage requirements. To meet tightened capital requirements, banks have to increase their capital ratios either by increasing equity or by decreasing risk-weighted assets. Both options lead to banks’ performance deterioration. One remedy for banks to recover is raising their lending spread. A critical question is how much the lending spread should be increased to offset the drop in the bank’s financial performance level. In this study, we focus on the asymmetries and efficiency consequences of performance indices such as economic value added (EVA) and the more commonly used return on equity (ROE) in determining the loan spread. Using data on the largest U.S. banks over the period 2018–2022, our results show that the ROE rule significantly overestimates the magnitude of the lending spreads required to offset the negative financial consequences of increases in capital ratios. The EVA approach, on the other hand, prescribes on average a significantly lower lending spread of 0.4505 basis points against a lending spread of 21.0441 basis points associated with the use of the ROE approach. The efficiency and the level of lending spreads should enable banks to maintain their competitive advantages in the loan markets impacting overall economic productivity and growth.

Measurement of Risk-weighted Assets of Commercial Banks under the New Basel Accord and Capital Management Approach

Measurement of Risk-weighted Assets of Commercial Banks under the New Basel Accord and Capital Management Approach

Accounting for climate transition risk in banks’ capital requirements

This paper uses a stylized simulation model to assess the potential impact of climate transition risk on banks’ balance sheets in a climate-stress-testing (i.e. short-run) framework. We show that a moderate to high transition risk increases overall bank losses only relatively modestly if the baseline is a stressed macroeconomic scenario. However, even in a benign macroeconomic scenario, if high-carbon assets are at least 13% riskier than comparable assets a fire sale mechanism could amplify an initially contained shock into a systemic crisis, resulting in significant losses for the EU banking sector. We show that transition risks are concentrated, and find that an additional capital buffer of 0.9% risk-weighted assets on average would be sufficient to protect the system.

Capital Adequacy Ratio — a Panacea for Indian Banks during COVID-19 Pandemic

A stable financial system acts as a catalyst for the economic growth and development of a country. The healthy banking sector is the core of a sustainable economy as banks act as intermediaries between depositors and lenders of money. In the surge of the COVID-19 pandemic, the financial sector witnessed significant transitions in terms of digital transformation. In India, the banking sector has remained resilient throughout the pandemic due to government and regulators’ policy efforts and the maintenance of capital adequacy requirements. Banks have maintained higher capital buffers, better liquidity requirements, and lower leverage, cushions against pandemic shock. In the present paper, the researcher provides a conceptual elucidation of Basel norms, analyzes the component-wise Capital to Risk-Weighted Asset Ratio (CRAR) of Indian Scheduled Commercial Banks (SCBs) and examines the CRAR position of SCBs during the COVID-19 pandemic. The study also evaluated the distribution of SCBs by CRAR and examined the capital ratios of public, private, and foreign sector banks from 2016 to 2022. The ANOVA analysis output revealed a significant difference in the CRAR of public, private, and foreign banks. The study concludes that adequate CAR levels help banks mitigate the risks that arise during pandemic crises and aid them in conducting their banking operations effortlessly. Further, it concludes that public sector banks (PSBs) still lag behind their counterparts in maintaining adequate CRAR, and hence, they need to reduce the accumulation of risk-weighted assets (RWA).

ANALYSIS OF THE INTEGRAL INDEX OF BANK CAPITALIZATION

Adequate capitalization is crucial for ensuring a bank’s financial stability and, by extension, the financial security of the entire country. This importance is especially evident in terms of both the quantity and quality of capital that a bank holds to cushion potential losses. Various indicators and ratios are employed to assess the level of bank capitalization, often subject to regulatory oversight. However, there is currently no standardized methodology for calculating and analyzing this indicator. This article aims to analyze the comprehensive index of bank capitalization levels. The calculation is based on statistical reports from 34 European countries spanning the years 2010 to 2020. The author explores the main direct and indirect factors influencing the level of bank capitalization. Direct indicators include return on equity, capital to assets ratio, and the ratio of regulatory capital to risk-weighted assets. Indirect factors include return on assets, the level of non-performing loans, the number of bank branches, the ratio of expenses to income of banks, and the ratio of bank deposits to GDP.

Share Price Increases the Opportunity of Indonesian Government Bank to Obtain High Profitability

This study aims to examine the effect of credit risk with the ratio of Non-Performing Loans (NPL), the level of capital adequacy with the ratio of Capital Abankdequancy ratio (CAR), and cash turnover with Cash Turn Over (CTO), on Profitability to Return On Assets (ROA) with stock prices as a moderating variable at Indonesian state banks for the 2018-2020 period. The population of this study was carried out by state banks using data on profit before tax, average total assets, non-performing loans, total credits, capital, risk-weighted assets, operating profit, average cash and stock price data. The type of data used in this study is secondary data. The data analysis technique in this study is using multiple linear regression analysis. From the results of multiple regression analysis partially, NPL has an insignificant effect on ROA, CAR has a significant effect on ROA, CTO has an insignificant effect on ROA. However, simultaneously all three have a significant effect on ROA. And, share prices strengthen NPL, CAR and CTO against state-run bank ROA.

ACTIVATION OF THE INFLUENCE OF THE BANKING BUSINESS ON ENSURING THE SUSTAINABLE DEVELOPMENT OF THE ECONOMY OF UKRAINE

At the present stage of socio-economic transformations of Ukraine, in the context of the need to strengthen the impact of the banking business on ensuring the sustainable development of the national economy, the issues of participation of the credit potential of banks are becoming relevant. The direct and indirect impact of banks on the economic growth of the country is highlighted. The role of banks in the formation of credit potential is analyzed by qualitative indicators during 2018-01.10.2023. It is determined that the main indicators of the efficiency of using the resource potential of the banking business are: the ratio of regulatory capital to risk-weighted assets, the rate of return on assets, the ratio of liquid assets to total assets, the ratio of customer deposits to total gross loans, the ratio of non-performing loans to total gross loans, the ratio of loans granted by banks to GDP, the standard of the total amount of investment in the banking system, according to which the study of the relationship between changes in the pace of economic development depending on the development of the banking business was carried out. It is proposed to expand a number of measures to stimulate the credit activity of the banking business of Ukraine in the context of European integration.

Does promoters’ holding influence the liquidity risk of banks?

PurposeThis paper aims to evaluate whether promoter holding influences a bank’s liquidity in India’s leading emerging market. Furthermore, it also evaluates the moderating role of risk-weighted assets (RWA) on the relationship between promoter holding and liquidity.Design/methodology/approachThe data consists of 24 banks for the period of 12 years from 2010 to 2021. Static panel data is used to analyze the relationship between the liquidity coverage ratio (LCR) as the dependent variable, the promoter used as an explanatory variable and RWA used as a moderating variable in this study.FindingsThis study concludes that an increase in promoter holding helps to improve the liquidity of Indian banks. Moreover, it also shows that using RWA as a moderating term enhances the relationship between promoter holdings and Indian banks’ liquidity.Research limitations/implicationsThis study evaluated the impact of promoter ownership solely on the LCR, a statistic used to measure the short-term liquidity of banks in the Indian setting. Additional corporate governance factors, such as the makeup of the board of directors, relevant ownership concentration factors and external factors with the potential to affect the liquidity position of banks, could potentially be the subject of future investigations.Practical implicationsThis paper has both managerial and policy-level implications. It shows that it is advantageous for banks’ ownership composition to include more enormous promoter holdings to enhance banks’ liquidity. Policymakers can, thus, formulate policies to encourage banks to have more extensive promoter holdings.Originality/valueThe impact of promoter ownership on bank liquidity has not been evaluated in earlier research projects. Furthermore, the use of RWA as a moderating variable to determine this link has not been fully investigated, particularly in the context of a developing country like India.

Islamic banks and capital buffer behavior: A view from the Gulf cooperation council markets

This study explores the determinants of the capital buffer behavior (CB) of Islamic banks (IBs) using a sample of 42 IBs in the Gulf Cooperation Council (GCC) markets during 2009–2018. We also investigate the transmission mechanism, efficacy of the macroprudential policies, relationships between these policies, and financial stability of these banks. Unlike previous research, this study considers certain peculiarities of IBs, including the effects of profit–loss-sharing investment accounts (PSIAs); the impact of capital adjustment costs; external factors such as market power and competition; and institutional influences such as the rule of law and the potential corruption perceptions index. Overall, our results show that CB is countercyclical, which is in line with Basel III requirements. Furthermore, CB is positively affected by bank size, level of profitability, and competition and negatively impacted by nonperforming loans, credit risk, and displaced commercial risk (DCR). The regulatory determinants are important as well, suggesting that strengthening the official macroprudential supervision encourages banks to strengthen their CBs. Conversely, although banks have adequate capital, regulatory tools increase the burden, increasing banks' capital costs and forcing them to limit risk-weighted asset expansion and credit growth. Furthermore, the regulatory pressure, proxied by a discretionary countercyclical buffer, is not binding and does not increase CBs as they are already moving countercyclically, making macroprudential tools redundant for IBs. Other important implications suggest that IBs do not require additional CBs to cover the DCR associated with PSIAs, as PSIAs' provisions, profit equalization reserves, and investment risk reserves already cover this risk. Additionally, the positive relationship between IB size and CB might indicate that the “too big to fail” hypothesis does not apply to large IBs in the GCC.

Back to the Roots of Internal Credit Risk Models: Does Risk Explain Why Banks’ Risk-Weighted Asset Levels Converge Over Time?

Back to the Roots of Internal Credit Risk Models: Does Risk Explain Why Banks’ Risk-Weighted Asset Levels Converge Over Time?

Banking Stability Multifactor Modelling Using Varma Methodology in the Republic of Armenia

The banking stability modelling with VARMA model has been conducted in the given research where 48 factors, representing different sectors of economy, have been selected. After that, by using RIDGE and Lasso regressions, as well as correlation coefficients with the dependent variable, only the most significant factors have been chosen. As the determinant of the banking stability, the banking Z-score has been selected, which is calculated as a country level measure, and not for individual banks. Using these factors, the VARMA model has been estimated, and the best model is identified as the VARMA(2,1). It is proven, that factors like Regulatory capital to riskweighted assets, dollarization rate, exchange rates, CPI, profitability of government bonds, nonperforming loans, ROA, ROC, liquid assets to demand deposits, and other factors selected in the result of model evaluation are good indicators for modelling the banking stability. The model prediction power is tested by splitting data into train and test parts and comparing predicted values with test dataset. The model shows quite small mean squared error and proves to be useful for modelling Armenian banking stability with existing dataset.

Interconnection between bank capitalization and macroeconomic stability in the countries of South-West Asia

The paper aims to define the specifics of the mutual interconnection between bank capitalization and indicators of macroeconomic stability. This is achieved by the following methods: grouping, analysis and synthesis, analysis of descriptive statistics, and canonical correlation analysis. The study was carried out based on eight bank capitalization indicators and five macroeconomic stability indicators in seventeen South-West Asian countries from 2010 to 2020. The information base of the research is the dataset from the World Bank. The selected list of indicators is determined by the availability of statistical information for the countries participating in the study. It was found that there is a close canonical correlation between the level of bank capitalization and the macroeconomic stability of the countries under investigation – 0.97 (2010) and 0.99 (2020). The variation of the investigated indicators of macroeconomic stability (68.95% (2010) and 70.64% (2020)) is determined by the change in bank capitalization indicators. On the other hand, the difference in macroeconomic stability indicators of countries by 48.66% (2010) and 42.79% (2020) is due to changes in bank capitalization indicators. Four indicators exert the most significant favorable influence on the level of bank capitalization: Bank return on assets – 0.303 (2010) and 13.033 (2020), Bank return on equity – 0.446 (2010) and 13.387 (2020), Bank regulatory capital to risk-weighted assets – 0.812 (2010), and Bank deposits to GDP – 1.580 (2020). The macroeconomic stability of countries is determined by two indicators: GNI – 3.311 (2010) and 3.461 (2020); GDP – 4.748 (2010) and 4.672 (2020).

The Relationship between Bank Capital, Risk-Taking and Profitability: Fresh Evidence from Panel Quantile Approach

This study aims to reveal the relationship between bank capital (BC), risk-taking, and profitability for commercial banks in Turkey using panel quantile regression models (QRPD) with non-additive fixed effects (NAFE). Accordingly, we consider the data of 18 commercial banks for 2012-2022. Firstly, we concluded a positive relationship between banks' risk-based capital (RBC) and traditional capital ratios (CR) and return on assets (ROA); in contrast there is a negative relationship between RBC and risk-weighted assets (RWATA) under all market conditions. Secondly, we found a positive relationship between the RBC and the provision for loan losses ratio (LLPTA) in other periods except for the contraction period; at the same time, there is a positive relationship between CR and LLPTA in other periods except for the expansion period. The findings also showed an inverted U-shaped relationship between RBC and the LLPTA and return on equity (ROE) and an N-shaped relationship between CR and ROE. Lastly, we discovered a positive relationship between RWATA and ROA and ROE in all market conditions, whereas a negative relationship exists between LLPTA and ROA. The findings provide valuable insights into the validity of the moral hazard and cost-skimping hypotheses, regulatory assumptions, agency, portfolio and risk-bearing profit theories in the commercial banking sector, and that risk, capital and profitability indicators are leading factors in banks' stability.

An axiomatic approach to default risk and model uncertainty in rating systems

In this paper, we deal with an axiomatic approach to default risk. We introduce the notion of a default risk measure, which generalizes the classical probability of default (PD), and allows to incorporate model risk in various forms. We discuss different properties and representations of default risk measures via monetary risk measures, families of related tail risk measures, and Choquet capacities. In a second step, we turn our focus on default risk measures, which are given as worst-case PDs and distorted PDs. The latter are frequently used in order to take into account model risk for the computation of capital requirements through risk-weighted assets (RWAs), as demanded by the Capital Requirement Regulation (CRR). In this context, we discuss the impact of different default risk measures and margins of conservatism on the amount of risk-weighted assets.

Back to the roots of internal credit risk models: Does risk explain why banks' risk-weighted asset levels converge over time?

The internal ratings-based (IRB) approach maps bank risk profiles more adequately than the standardized approach. After switching to IRB, banks' risk-weighted asset (RWA) densities are thus expected to diverge, especially across countries with different supervisory strictness and risk levels. However, when examining 52 listed banks headquartered in 14 European countries that adopted the IRB approach, we observe a convergence of their RWA densities over time. We test whether this convergence can be entirely explained by differences in the size of the banks, loss levels, country risk, and/or time of IRB implementation. Our findings indicate that this is not the case. Whereas banks in high-risk countries with lax regulation, reduce their RWA densities, banks elsewhere increase theirs. Especially for banks in high-risk countries, RWA densities underestimate banks' economic risk. Hence, the IRB approach enables regulatory arbitrage, whereby authorities only enforce strict supervision on capital requirements if they do not jeopardize bank viability.

Executive compensation: A justified reward or a mis-fortune, an empirical analysis of banks in Pakistan

The relationship between compensation, performance, and risk in a sample of Pakistani banks, using panel data for 20 banks from 2011 to 2021 has been examined in this research. To the best of researcher’s knowledge, this is one of the first study examining the relationship between performance, risk and employee compensation using panel data approach in the context of Pakistan and using data for longer period. To examine the influence of employee compensation on the performance and risk of banks, we employed three performance measures: return on assets, return on equity, and operating profits. Risk assessment was conducted using non-performing loans and risk-weighted assets. Findings of study suggest that employee compensation has no significant impact on performance and risk of banks in Pakistan; this means in Pakistan higher employee’s compensation does not enable banks to improve their performance or enable banks to take more risk.

Does the Performance of Banking Sector Promote Economic Growth? A Time Series Analysis

Purpose: In terms of stimulating the economy, banks play an essential role. These banks directly or indirectly influence the economic growth (GDP) of a country. This study analyses the association between banks' performance and GDP growth. Theoretical Framework: The banking sector acts as an effective mechanism that funds various projects all over the country. The majority of such studies focus on developed nations. Although there is a great deal of literature on this issue concerning developed markets, there is a lack of literature related to emerging and developing economies (Sensarma & Bhattacharyya, 2016). This study has been undertaken to analyse the influence of banks on India's economy, which is a developing economy Design/Methodology: The data of the study includes the independent variables that indicate banking performance. The proxies used for the bank's performance are: bank nonperforming loans to total gross loans (%) (NPL), domestic credit provided by the financial sector (% of GDP) (DC), Return on Equity (ROE), bank capital to assets ratio (%) (CAP), and regulatory capital to risk-weighted assets (CAR). At the same time, the substitute for economic growth is growth in domestic product (GDP). All organised banks operating in India form the sample of the study. The period of study is from 1990 to 2029. To test the hypotheses, simple regression, multicollinearity tests, and ordinary least square (POLS) are performed. Findings: The findings indicate that a few of the variables such as domestic credit, return on equity, and capital adequacy ratio, which are linked to the bank's operational and financial efficiency, are correlated with India's GDP growth. The study's empirical results recommend that this country's (India's) policymakers should assist the banking sector by laying down new growth and developmental policies that will strengthen the banking sector, which will in turn strengthen the economy. Research, Practical & Social Implications: This study shows that Indian banks have a major impact on Indian economic growth. It also identifies the primary banking attributes that influence GDP. Such a study will help policymakers and researchers understand the significant contributors to economic growth. Originality and Value: There are many studies that have studied the determinants of GDP. But this is the first study that has tried to establish the impact/relationship of banking variables on GDP growth.

Analysis of Financial Performance of Nepalese Commercial Banks using CAMEL Approach

Bank and financial institutions require a method for assessing performance, considering some crucial financial statistics, and identifying strengths and weaknesses. The "CAMEL" model is a effective tool for assessing the performance of bank and financial institution. This model studied Capital adequacy, Asset quality, Management quality, Earnings capacity, and Liquidity condition of sample banks. The study has made a modest attempt to use the CAMEL technique to examine the performance of three commercial banks in Nepal from 2011/12 to 2020/21. Rastriya Banijya Bank, a wholly government-owned, Nepal SBI Bank Limited (NSBIL) joint venture, and Prime Commercial Bank Limited (PCBL), privately owned, were considered as a sample banks for the analysis. The result explained that PCBL and NSBIL could keep their risk-weighted assets at more excellent Tier I and II capital levels, demonstrating their financial soundness. This also revealed that NSBIL could support a higher percentage of well-performing loans. RBBL, NSBIL, and PCBL, all BFIs maintained average returns on shareholder equity and returns on assets. It also found PCBL was first in terms of the ratio of liquid assets to total deposits, followed by NSBIL banks and RBBL. In light of this, this research will be tremendously instructive to academics, researchers, and bank management. They can utilize it to create a financial plan for the effectiveness of the bank performance as a whole.