Bank Net Interest Margins Research Articles

The impact of recapitalisations and bank competition on Greek bank net interest margins

PurposeThis study investigates the reasons behind the very high net interest margins in the Greek banking industry compared to the euro-area, focussing on the association between bank competition and recapitalisations.Design/methodology/approachThe author conducts a dynamic panel analysis covering the period from the early 2000s to 2021, that controls for possible endogeneity and treats for heterogeneity. The author also employs local projections impulse response functions that control for structural changes in Greek banking.FindingsThe author finds that low bank competition has contributed to high net interest margins in Greece. Interestingly, the impact of recapitalisations conditional to low bank competition has had a significant further impact on increasing net interest margins, which is a noteworthy case due to several Greek bank recapitalisations in the last ten years. The author’s findings are supported by local projections impulse response functions.Originality/valueTo mitigate distortions in bank competition, the author argues to accelerate steps toward the direction of the banking union and a common bank regulation framework in the euro-area.

Analisis Metode RGEC untuk Penilaian Kinerja pada PT Bank Mandiri (Persero) Tbk

This research aims to analysis the soundness level of banks using the RGEC method at PT Bank Mandiri (Persero) Tbk in 2018-2021. The data studied is in the form of financial statements of PT Bank Mandiri (Persero) Tbk for 2018-2021. The data collection technique used is the documentation technique. The data analysis technique used is a qualitative descriptive analysis technique using the RGEC method. The results of this research show that Bank Mandiri for 2018-2021 is viewed from the aspect of risk profile with two ratios, namely the ratio of Non-Performing Loans for banks in a healthy condition and the ratio of Loan to Deposit Ratio for banks in a fairly healthy condition. Aspects of Good Corporate Governance get the title of very healthy. Earnings aspect with two ratios, namely the ratio of the bank's Return on Assets in a very healthy condition and the ratio of the bank's Net Interest Margin in a healthy condition. Aspects of Capital with the ratio of Capital Adequacy Ratio of the bank is in very healthy condition.

The Impact of Developing Fintech on Banks

In recent years, the rapid development of financial technology (fintech) has greatly impacted the traditional banking industry, posing both challenges and opportunities for banks. In this study, we investigate the influence of fintech on the net interest margin and non-performing loan ratio of banks in China.To measure the level of fintech development in banks, we construct a Bank Fintech Development Index (BFDI) based on text analysis of annual reports. We then use a panel data regression model to analyze the impact of fintech development on the net interest margin and non-performing loan ratio of banks, controlling for other factors such as bank size, capital adequacy, and macroeconomic conditions.Our empirical results show that the development of fintech has a significant positive impact on the net interest margin of banks, indicating that banks that have adopted fintech are able to generate higher profits from their interest-bearing assets. We also find that the development of fintech has a significant negative impact on the non-performing loan ratio of banks, suggesting that fintech can help banks improve their risk management and reduce their credit losses.Therefore, banks should continue to embrace fintech and invest in new technologies to remain competitive in the rapidly evolving financial landscape.

Impact of Bank Efficiency on the Profitability of the Banks in India: An Empirical Analysis Using Panel Data Approach

This study aims to determine the impact of banking efficiency on the profitability of the Indian banking division. The ratios (key variables) used in the study are mentioned by the Reserve Bank of India—RBI (Central bank of India). Through a quantitative approach, pooled panel regression, univariate analysis, correlation, and descriptive statistics models are used by taking annual data of the Indian banking division from 2001 to 2020 available on the Thomson Reuters (Refinitiv) Database. Unbalanced cross-sectional data (panel data) comprising 527 bank-year observations for 33 Indian banks were studied. It was decided to evaluate the impact of efficiency (cost to income ratio and staff expenses to total expenses ratio) on the profitability (return on assets and net interest margin ratio) of the banks from the Indian banking division. The results revealed that the cost to income ratio has a significant negative impact on the bank return on assets and net interest margin ratio. The staff expenses to total expenses ratio has a significant positive impact on the bank return on assets and a positive nonsignificant impact on the bank net interest margin ratio.

Effect of Credit and Liquidity Risks on Bank Stability: Empirical Evidence from Afghanistan

This study investigates the effects of liquidity and credit risks on the stability of banks with empirical evidence from the Afghanistan banking sector over the period 2014–2020. The stability of a bank is measured through the dependent variable of its capital adequacy ratio. Credit risk (calculated by the ratio of impaired loans) is included as an independent variable along with liquidity risk. The bank specific factors, namely bank net interest margin, size of the bank, return on assets, loan growth rate, liquidity gap, return on equity, loan to asset and macro-economic factors, inflation and GDP growth rate are included as control variables. This study includes all 10 operationalized banks in Afghanistan, excluding the two branches of foreign banks. The panel dataset was collected from banks’ websites and the macroeconomic data was derived from World Bank reports. This study employed the simultaneous equation approach of a two-stage least square and a fixed effect panel regression model to investigate the affiliation between liquidity and credit risks and their effects on the stability of banks. The results of this study indicate that liquidity and credit risks don’t have a mutual relationship, while the interaction of both types of risks jointly impacts bank stability. It shows that NIM, loan assets, ROA, liquidity gap, loan growth rate, and ROE have positive impacts on bank stability, whereas the size of the bank has negative effects on bank stability. Among the macroeconomic variables, only the growth rate of GDP signifies a negative effect on the stability of banks. The finding under this paper recommends that the governance body of the banking sector drafts policies aimed at strengthening bank capital and taking liquidity measurement according to the best standards introduced by the Basel committee. Also, to create frameworks for measuring liquidity and capital standards.

How does financial performance affect financial inclusion for developing countries?

ABSTRACT This study aims to detect the relationship between financial inclusion and financial performance in the banking sector. Within this scope, firstly, we develop an index for financial inclusion which consists of various dimensions for 85 developing countries in the 2005–2017 time period. Then, we apply static and dynamic panel data analyses. Static panel data analysis findings indicate that financial performance indicators such as bank return on assets, bank return on equity, and bank net interest margin positively affect and bank lending-deposit spread negatively affects financial inclusion, but bank non-interest income to total income has a statistically insignificant coefficient. Also, as a robustness analysis, dynamic panel data analysis provides evidence that financial performance is important for financial inclusion. According to our findings, we can say that the increase in the profitability of the banking sector is one of the triggers of financial inclusion for developing countries.

The Impact of Indirect Competition on Bank Net Interest Margins: Microfinance Evidence from Pakistan

The study aims to investigate the impact of growth in microfinance initiatives on the net interest margins of commercial banks in Pakistan. Using data from the world bank MIX database and Thomson Reuters, we conducted a GLS random effect estimation on an unbalanced panel of Pakistani banks from 2010 to 2018. We find that credit quality, solvency, bank size, earning asset diversification, and market concentration impact banks' net interest margins. In addition, we find growth in development finance institutions to significantly affects commercial bank margins. Microfinance institutional growth is found to reduce net interest margins. Besides microfinance institutions, the growth of specialised microfinance banks is also found to impact the spread negatively. This indirect effect may be evidence of the improved efficiency derived from higher competition or the fact that microfinance institutions may be using conventional banks as a permanent source of funds to become financially sustainable. The role of microfinance growth is not considered in literature since microfinance institutions are very different from conventional banks regarding lending volume and size. This study contributes to the existing theoretical and empirical literature on net interest margins by showing a positive role of indirect competition on banks' net interest margins. Therefore, policymaking focusing on improving conditions that enhance competition to bring bank spreads closer to regional levels may be needed.

The Impact of Capital on Bank Profitability: Case of Tunisia

The capital adequacy ratio measures the ability of a financial institutions to meet its liabilities by comparing its capital with assets.
 This article studied the relationship between bank capital and bank profitability measured by (Return on assets; return on equity; net interest margin). We used a method of static panel for a sample of 11 banks in Tunisia between (2000…2018). We found that bank capital has a significant impact on ROA. But capital has a non significant effect on bank return on equity and not significant impact on bank net interest margin.

Bank Profitability Determinants: Comparing the United States, Nigeria and South Africa

This study investigates the determinants of banking sector profitability in South Africa, Nigeria and the United States. The findings reveal that cost efficiency, the size of non-performing loans and overhead cost ratio are significant determinants of the banking sector profitability. In the comparative analysis, the findings from South Africa show that the cost efficiency ratio, overhead cost to total asset ratio and non-performing loans are significant determinants of banking sector profitability. In the United States, capital adequacy ratio and the size of non-performing loans are significant determinants of banking sector profitability. In Nigeria, the overhead cost to total asset ratio and cost efficiency ratio are significant determinants of the banking sector profitability. The descriptive analysis reveal that bank net interest margin and return on asset are higher in Nigeria and lowest in the United States which suggests that the Nigerian banking sector is more profitable than the US banking sector. Return on equity is higher in South Africa and lowest in the United States.

BANK PROFITABILITY DETERMINANTS: COMPARING THE UNITED STATES, NIGERIA AND SOUTH AFRICA

This study investigates the determinants of banking sector profitability in South Africa, Nigeria and the United States. The findings reveal that cost efficiency, the size of non-performing loans and overhead cost to total asset ratio are significant determinants of the banking sector profitability. In the comparative analysis, the findings from South Africa show that the cost efficiency ratio, overhead cost to total asset ratio and non-performing loans are significant determinants of the banking sector profitability. In the United States, capital adequacy ratio and the size of non-performing loans are significant determinants of its banking sector profitability. In Nigeria, the overhead cost to total asset ratio and cost efficiency ratio are significant determinants of the banking sector profitability. The descriptive analysis reveal that bank net interest margin and return on asset are higher in Nigeria and lowest in the United States which suggests that the Nigerian banking sector is more profitable than the US banking sector. Return on equity is higher in South Africa and lowest in the United States.

Impact of internal and external factors on the net interest margin of banks in Indonesia

This study aims to assess the impact of bank-specific factors and macroeconomic indicators on the net interest margin (NIM) of commercial banks in Indonesia. Data from Indonesian commercial banks are used. Data are collected from the banks’ annual reports and the Financial Services Authority (OJK) for the period 2008 to 2018. A panel data regression model is used to estimate the effect of bank-specific and macroeconomic factors. The results prove that the variables of Non-Performing Loans (NPL), Loan to Deposit Ratio (LDR), Return on Assets (ROA), Interest Rate (SBI), and Exchange Rate (FOREX) affect NIM. The exchange rate variable has a predominant effect, while the NPL factor has a less strong influence on NIM. The empirical evidence from this research is important for commercial banks in Indonesia to improve operational efficiency through NIM performance. Internal and external factors of a bank should be subject of attention of bank managers.

Liquidity and Monetary Transmission: A Quasi-Experimental Approach

In the face of lower real interest rates, central bank balance sheets are likely to remain larger relative to pre-crisis levels, resulting in greater banking system liquidity. However, there is little evidence on the impact of higher liquidity on credit supply and the monetary transmission mechanism in the ‘new normal’. We exploit a novel dataset on bank liquidity positions arising from a unique regulatory regime and combine it with a highly-detailed, loan-level administrative dataset on UK mortgages. Using the design of quantitative easing auctions as an instrument for liquidity to address endogeneity, we find that more liquid banks charge slightly higher mortgage interest rates, and pass on significantly less changes in risk-free rates. We explain this through bank behaviour that attempts to preserve net interest margins in the face of holding low-yielding liquidity. Consistent with this, we find excess liquidity leads to reaching-for-yield responses in banks’ mortgage risk-taking. Additionally, the results shed light on the optimal mix between (un)conventional monetary policy tools. Policies that boost bank net interest margins are more likely to help the transmission of risk-free rates to lending rates.

Heterogeneity in Net-Interest Income Exposure to Interest Rate Risk and Non-Interest Expense Adjustment

In this paper I document two new facts. First, bank net-interest margins (NIM) are insensitive to the short rate on average but this masks substantial heterogeneity in the cross section. I find cross sectional variation ranging from a -30bp to +40bp change in one quarter NIM after a 100bp change in rates, which compounds over the following four quarters. I find that this cross sectional heterogeneity is driven by differences in bank business models. Second, bank NIM sensitivity to rate changes is muted by offsets in non-interest expenses, reducing ROA sensitivity by approximately 30% on average. The positive relationship between net-interest income and non-interest expenses is somewhat consistent with investment sensitivity to profitability, but is also consistent with the management of expenses in order to prop up earnings to meet executive performance targets. These findings have implications for understanding how the net-worth channel of monetary policy operates in the cross section and can help inform policy related to the existence of a ``reversal rate''.

Measuring Interest Rate Risk Considering Key Factors Affecting the Net Interest Margin (NIM) Ratio of Commercial Banks in Bangladesh

This paper attempts to reveal how the commercial banks operating in Bangladesh have measured interest rate risk using Interest sensitivity analysis along with considering the impact of key factors affecting the profitability measured with Net interest margin of banks under Bank specific as well as macro-economic environment. Interest sensitivity (IS) GAP analysis has been deployed to measure the degree of interest rate risk followed by a panel data regression model considering a comparative analysis among fixed effect within group, random effect GLS and Pooled OLS method adopted to measure the causation between Net interest margin and Bank specific along with Macroeconomic factor to accomplish the objective of this paper. In IS GAP along with relative IS GAP analysis, two banks are found to be liability sensitive posing a risk of reducing the net interest margin (NIM) if interest rate has been increased and rest of the banks are found to be asset sensitive again postulating risk of reducing the NIM if market rate interest has been decreased considering the ten years’ data regarding rate sensitive assets (RSA) and rate sensitive liabilities (RSL) of four commercial banks selected using convenience sampling approach. Moreover, Panel Data regression model depicts how several key factors such as degree of risk aversion, credit risk and quality of management, Average operating cost, size of banks, implicit interest payments may significantly affect this NIM ratio measuring the profitability of banks in Bangladesh followed by several diagnostic tests such as model specification test using hausman & LM test, multicollinearity test, heteroscadisticy test and unit root test conducted to check the validity of models. Keywords: IS GAP, NIM ratio, Relative IS GAP, Fixed effect, Random effect, OLS method. DOI: 10.7176/EJBM/12-15-08 Publication date: May 31 st 2020

Can good governance lower bank intermediation costs?

ABSTRACT This paper argues that better governance practices can reduce the costs, risks and uncertainty of financial intermediation. Our sample covers 100 high-, middle- and low-income countries during 1996 to 2015. Using panel regressions accounting for endogeneity and cross-sectional dependance, we find that net interest margins of banks are lower if various governance indicators are better. Governance indicators range from comprehensive indices on the rule of law to more narrow indicators like ethics of private firms. The global financial crisis seems not to have had a strong impact except via credit risk. Finally, we estimate that potential annual savings from lower net interest margins could average almost 0,3 percent of GDP, had the governance indicators been at the top decile. These simulations lend credence to the intuition that better governance practices should reduce costs, risks and uncertainty.

Financial freedom, market power and bank margins in sub-Saharan Africa

PurposeThis paper examines the effect of financial (banking) freedom and market power on bank net interest margins (NIM).Design/methodology/approachThe study uses data from 11 sub-Saharan African countries over the period, 2006-2012, and the system generalized method of moments to assess how financial freedom affects the relationship between market power and bank NIM.FindingsThe authors find that both financial freedom and market power have positive relationships with bank NIM. However, there is some indication that the impact of market power on bank margins is sensitive to the level of financial freedom prevailing in an economy. It appears that as competition intensifies, margins of banks in freer countries are likely to reduce faster than those in areas with more restrictions.Practical implicationsCompetition policies could be guided by the insight on how financial freedom moderates the effect of market power on bank margins.Originality/valueThis study provides new empirical evidence on how the level of financial freedom affects bank margins and the market power-bank margins relationship.

Firm-specific Variables and Net Interest Margin in Nepalese Banks

This paper examines the impact of firm-specific variables on net interest margin in Nepalese commercial banks for the period 2005/06-2018/19. Secondary source data were collected through NRB and data have been analyzed using descriptive and causal comparative research design. In this paper, net interest margin is used as dependent variable and bank-specific variables such as size of assets, deposit ratio, loan ratio, and capital ratio are considered as explanatory variables. The estimated correlation results of the paper reveal that equity capital, bank loans and deposits are positively related with net interest margin of Nepalese commercial banks. Moreover, the regression results of this paper indicate that equity capital, bank lending and deposits have significant impact on net interest margin of banks. Finally, this paper concludes that bank loans and deposit have strong explanatory power to explain net interest margin as profitability in Nepalese commercial banks. Policy makers are suggested to formulate sound bank policies and to adopt effective strategies to increase the size of bank deposits as well as bank lending to maximize the profitability (net interest margin) in Nepalese commercial banks.

The Effect of Financial Sector Reforms on Bank Net Interest Margins in Ghana

This paper examines the effect of financial sector reforms on net interest margin of Ghanaian banks during the period 1997-2006. Changes have taken place in Ghana as in other countries. However, net interest margins have not declined as much in Ghana as they have elsewhere due to the influence of the degree of risk aversion, high operating costs and uncompetitive nature of the market structure. Although banks have relied heavily on fee- and commission-based services as additional sources of income to lower margins, this paper argues that despite recent developments in the Ghanaian financial landscape, financial sector reforms have not yet succeeded in bringing about a major reduction in the operating costs of banks that would translate into substantially narrower margins. This is by far the major significant effect of relatively wide net interest margin in Ghana.

Profitability trends in the era of financialization: Notes on the U.S. economy

This article considers the evolution of financialization in the U.S. economy by examining the profitability and the volume of profits of the financial sector relative to general profitability and total profits in the economy. It is shown that financial profitability rose strongly from the early 1980s to the early 2000s. Similarly, the volume of financial profits reached extraordinary levels in the early 2000s. These phenomena occurred while interest rates and the net interest margin of banks were on a downward trend and, broadly speaking, reflect financial expropriation in the U.S. economy. The great crisis of 2007–2009 has acted as a threshold point beyond which both the profitability and the volume of profits of the financial sector have not recovered to previous levels. It is possible, but not certain, that a rebalancing of the productive and the financial sectors is under way in the financialized U.S. economy.

Bank Net Interest Margin Forecasting and Capital Adequacy Stress Testing by Machine Learning Techniques

The 2007-09 financial crisis revealed that the investors in the financial market were more concerned about the future as opposed to the current capital adequacy for banks. Stress testing promises to complement the regulatory capital adequacy regimes, which assess a bank's current capital adequacy, with the ability to assess its future capital adequacy based on the projected asset-losses and incomes from the forecasting models from regulators and banks. The effectiveness of stress-test rests on its ability to inform the financial market, which depends on whether or not the market has confidence in the model-projected asset-losses and incomes for banks. Post-crisis studies found that the stress-test results are uninformative and receive insignificant market reactions; others question its validity on the grounds of the poor forecast accuracy using linear regression models which forecast the banking-industry incomes measured by Aggregate Net Interest Margin. Instead, our study focuses on NIM forecasting at an individual bank's level and employs both linear regression and non-linear Machine Learning techniques. First, we present both the linear and non-linear Machine Learning regression techniques used in our study. Then, based on out-of-sample tests and literature-recommended forecasting techniques, we compare the NIM forecast accuracy by 162 models based on 11 different regression techniques, finding that some Machine Learning techniques as well as some linear ones can achieve significantly higher accuracy than the random-walk benchmark, which invalidates the grounds used by the literature to challenge the validity of stress-test. Last, our results from forecast accuracy comparisons are either consistent with or complement those from existing forecasting literature. We believe that the paper is the first systematic study on forecasting bank-specific NIM by Machine Learning Techniques; also, it is a first systematic study on forecast accuracy comparison including both linear and non-linear Machine Learning techniques using financial data for a critical real-world problem; it is a multi-step forecasting example involving iterative forecasting, rolling-origins, recalibration with forecast accuracy measure being scale-independent; robust regression proved to be beneficial for forecasting in presence of outliers. It concludes with policy suggestions and future research directions.