Net Stable Funding Ratio Research Articles

Commercial bank NSFR adjustment and risk: Evidence from China

The net stable funding ratio (NSFR) is a critical monitoring indicator of bank liquidity risk introduced under the Basel III accord in 2009. This study used the partial adjustment model to analyze the NSFR adjustment behavior of Chinese commercial banks, leading to the following four findings. First, banks have been undertaking active liquidity adjustment while exceeding global and Chinese minimum standards. Second, the NSFR’s target level and adjustment speed are significantly higher than those of foreign banks. Third, the target NSFR gap is essential to the NSFR’s positive adjustment. Fourth, a higher target level and steady adjustment speed help reduce loss from systemic risk. This paper suggests establishing three liquidity risk firewalls, providing an essential reference for understanding NSFR adjustment in Chinese commercial banks. The study also provides practical significance for policy-level assessments regarding the impact of implementing NSFR supervision and establishing liquidity risk firewalls.

Interbank Decisions and Margins of Stability: an Agent-Based Stock-Flow Consistent Approach

This study investigates the functioning of modern payment systems through the lens of banks' maturity mismatch practices, and it examines the effects of banks' refusal to roll over short-term interbank liabilities on financial stability. Within an agent-based stock-flow consistent framework, banks can engage in two segments of the interbank market that differ in maturity, overnight and term. We compare two interbank matching scenarios to assess how bank-specific maturity targets, dependent on the dictates of the Net Stable Funding Ratio, impact the dynamics of the interbank market and the effectiveness of conventional monetary policies. The findings reveal that maturity misalignment between deficit and surplus banks compromises the interbank market's efficiency and increases reliance on the central bank's standing facilities. Monetary policy interest-rate steering practices also become less effective. The study also uncovers a dual stability-based configuration in the banking sector, resembling the segmented European interbank structure. This paper suggests that heterogeneous maturity mismatches between surplus and deficit banks may result in asymmetric funding frictions that might precede credit- and sovereign-risk explanations of interbank tensions. Also, a combined examination of macroprudential tools and rollover-based interbank dynamics can enhance our understanding of how regulatory changes impact the stability of heterogeneous banking sectors.

Using machine learning for detecting liquidity risk in banks

The accurate classification of banks’ Liquidity Risk (LR) for regulatory supervision is hindered by limitations in the measures, such as Minimum Liquid Assets (MLA), Net-Stable Funding Ratio (NSFR), and Liquidity Coverage Ratio (LCR). This study addressed two limitations on data integrity vulnerabilities and the narrow composition of LR factors excluding practical LR determinants such as credit portfolio quality, market conditions, strategies of assets and funding. Theoretical gaps included the eight new LR factors in this study, benchmarking study results with measures to interpret the studies’ contributions and the selection of suitable prediction methods for non-linear, imbalanced, scaling, and near real-time data. We used data from 38 Tanzanian banks (2010-2021) from the Bank of Tanzania (BOT). Extensive factors experimentation using Random Forest (RF) and Multi-Layer Perceptron (MLP) models identified ten features for Machine Learning (ML) analysis and LR rating as output. A hybrid RF-MLP model with a 199-tree RF and 10-512-250-120-80-60-6 MLP was developed. It increased LR sensitivity and reduced RF and MLP model limitations through generalisation, and demonstrated statistical and practical performance. It minimised classification errors with Type I and II errors, and Negative Likelihood of 0.8%, 9.1%, and 1%; Discriminant Power of 2.61; and 90% to 96% Accuracy, Balanced Accuracy, Precision, Recall, F1 Score, G-mean, Cohen’s Kappa, Youden Index, and Area Under the Curve. Past LR scenarios confirmed RF-MLP performance improvement over MLA. The unavailability of LCR and NSFR data hindered a comprehensive evaluation. This study extended LR factors and proposed a model to complement LR classification.

The interactive impact of green supporting factors on bank credit creation: An agent-based stock-flow consistent approach

Low carbon transition requires prudential regulations to incentivize bank’s green financing behaviors. This paper performs a simple and original analysis on the impact of the green differentiated banking requirements on bank’s credit creation. Through a simplified bank balance sheet, this paper incorporates green supporting factors into the framework of prudential regulations, namely the risk-based capital adequacy ratio and the net stable funding ratio respectively, and theoretically quantifies the constraining effect rendered by the green differentiated requirements. By constructing an agent-based stock-flow consistent model of commercial banks, and conducting numerical experiments, we find that the green supporting factors exert interactive impacts on credit creation, which depends on bank’s balance sheet structure characterized by equity to reserve ratios. So that it is necessary to implement different combinations of green supporting factors in order to achieve the target of green credit issuance, thus serving for green economic transition. The results obtained in this paper might facilitate the understandings what financial regulators can do to promote low-carbon transition via the banking system.

Liquidity Risk And Basel III Implementation In Southeast Asia Banking

Purpose: The objective of this study was to determine the effect of liquidity coverage ratio, net stable funding ratio, net interest margin, and cost of funds on return on assets in Southeast Asian countries' banking services. Methodology/approach: This research was a quantitative research method. Secondary data was used and collected from stock exchanges in each country. Samples were banks in Indonesia, Malaysia, Cambodia, Philippines, Singapore and Thailand. The data testing technique uses multiple linear regression analysis. Findings: The study inform that net stable funding ratio, liquidity coverage ratio, net interest margin and cost of funds have a significant effect on return on assets. Practical implications: The practical implications were BASEL III implementation to manage liquidity risk and capital in each country have successfully and encourage compliance with bank liquidity and capital aspects according to the framework of BASEL III to enhance the financial performance of banks in Southeast Asian countries. Originality/value: Research on the application of BASEL III in Southeast Asian Countries as a framework that establishes international standards for bank capital adequacy, stress testing, and liquidity requirements is the originality of this research.

Empirical study of the impact of liquidity risk on the financial performance: A study of selected commercial banks in Bangladesh

As liquidity risk is affecting the banking industry of Bangladesh, the study aims to analyze the impact of liquidity risk on financial performance of selected commercial banks in Bangladesh. The study applied a descriptive research design and targeted 20 commercial banks in Bangladesh, with secondary data collected over the span of five years from 2014 to 2018 and analyzed by employing the panel regression analysis model. Nine factors affecting financial performance of selected commercial banks in Bangladesh were selected and investigated. In the study, Return on Asset (ROA) and Return on Equity (ROE) are used as bank performance measurement tools and Non-Performing Loan ratio (NPLR), Capital Adequacy ratio (CAR), Capital to Total Asset ratio (CTAR), Loan to Deposit ratio (LTD), Loan to Total Asset ratio (LTA), Deposit to Asset ratio (DTA), Cash to Deposit ratio (CDR), Liquidity Coverage ratio (LCR), and Net Stable Funding ratio (NSFR) are used as liquidity risk indicators. The result of panel data regression analysis showed that NPLR, CAR, LTD, and DTA had negative and statistically significant impact whereas, LTA, CTAR, and LCR had positive and statistically significant impact on the financial performance of selected commercial banks in Bangladesh. However, CDR and NSFR had no statistically significant impact on financial performance of the chosen banks for the sample period. Therefore, it has been identified that the liquidity risk is negatively affecting the financial performance of the selected commercial banks in Bangladesh.

Impact of Basel III liquidity and capital regulations on bank lending and financial stability: Evidence from emerging countries

AbstractWe examine the impact of Basel III's liquidity requirements, such as the liquidity coverage ratio (LCR), net stable funding ratio (NSFR), and capital adequacy, on bank lending and financial stability using data from 688 commercial banks of 10 developing economies from 2014 to 2021 using fixed effects panel estimation. The findings of the study support that bank lending is positively impacted by the regulatory capital and the short‐term liquidity requirement (LCR), but negatively impacted by the NSFR. We find that the bank's Z‐score benefits from achieving the required capital and liquidity requirements. Lending growth and bank stability are nonlinearly impacted by regulations governing bank capital and liquidity. Furthermore, we use the Generalized Methods of Moments‐Quantile Regression (GMM‐QR). Finally, our results indicate that regulators in these developing countries should support adequate capital and liquidity management to lessen adverse economic shocks' impact on banks' intermediation capabilities and stability.

BASEL III CAPITAL REGULATION FRAMEWORK AND ISLAMIC BANK’S RISK

Basel III modified the requirements for approving new regulatory capital norms to improve capital quality. Because bank liquidity problems were a defining feature of the crisis, Basel III established new requirement ratios while also tightened capital requirements. The Liquidity Coverage Ratio (LCR) was developed to safeguard banks' short-term liquidity, whereas the Net Stable Funding Ratio (NSFR) is being proposed to strengthen banks' medium- and long-term liquidity shock resilience. As a necessary consequence, Islamic financial institutions (IFIs) must issue instruments that satisfy both Basel III and Shari’ah requirements. This study aims to identify the regulatory requirements for Basel III and the Islamic Financial Services Board (IFSB)'s new capital and liquidity rules, as well as the implications for Islamic banks (IB). This study employs a mixed research methodologies approach which includes document analysis of primary and secondary sources, as well as the relevant regulations published by BCBS and IFSB. This study relies on the identification of Standards for each criterion before conducting a systematic review of the 23 publications that meet the study's requirements published between 2013 and 2022. There is a scarcity of Shari’ah-compliant research on capital buffers, tier 1 capital, and common equity tier 1 capital, according to certain findings. Furthermore, the empirical literature suggests that Basel III has a significant impact on the financial risk of the IB sector in the samples collected. However, there is still a significant gap in studies investigating the influence of Basel III/IFSB capital and liquidity regulations on Islamic bank risk, or more precisely, supportive data from empirical investigations. The wealth of research will provide new insights to standard-setters (BCBS and IFSB), regulators, researchers, and academicians.

Net Stable Funding Ratio (NSFR) and Bank Performance: A Study of the Indian Banks

The present study examines the impact of the Net Stable Funding Ratio (NSFR) on the performance of Indian commercial banks from 2010 to 2021. The study further investigates how the relationship between liquidity and performance varies under the influence of bank-specific factors such as ownership structure (Promoter vs. Institutional investors). Bank performance is evaluated using a two-fold approach—Profitability measures (NIMs and ROA) and NPA levels of banks. Using the Dynamic panel data regression technique, we find that the relationship between NSFR and NIMs is negative, implying that bank NIMs tend to decline as banks comply with NSFR regulation. Furthermore, the study demonstrates that the inverse relationship between NSFR and bank NIMs becomes more profound when promoters’ stakes are high. Finally, the results highlight that for banks with higher institutional holdings, NPA levels witness an upward trend as the NSFR ratio increases. From a policy perspective, study results will help policymakers understand how changes in liquidity levels impact the wider banking sector and guide them on the overall direction in which to progress with the reforms.

Based on Risk Indicator Analysis to Deal with Risk: A Case Study of Westpac Bank

Under APRA’s requirements, all Australian savings institutions need to develop risk appetite statements containing various risk indicators. This article will analyze Westpac’s various risk indicators based on Westpac’s annual report and risk appetite statement. There are six sections in this article. The first part is the background introduction. In the second part, by calculating and comparing the critical capital ratios of each quarter in 2020 and the preceding year, we analyze Westpac’s capital risk and the impact of CET1 on shareholders. The third part judges whether Westpac has achieved its credit risk target by comparing Westpac with the data of other banks in Australia. The fourth part is mainly about market risk. In this part, we analyze the most significant market risk Westpac faces. Westpac’s measurement and management methods of market risk and give Westpac improvement suggestions based on these data. The fifth part mainly studies the relationship between Bank’s Net Stable Funding Ratio, Liquidity Coverage Ratio and relevant risk appetite. In the last part, we summarize the article.

Impact of Basel III liquidity regulations on U.S. Bank performance in different conditional profitability spectrums

We study the impact of the Basel III liquidity constraints, represented by the liquidity coverage ratio (LCR) and the net stable funding ratio (NSFR), on bank profitability, by employing the simultaneous quantile regression framework with time fixed effects. We find a positive and significant relationship between the LCR and profitability and the NSFR and profitability over most quantiles. However, the small magnitudes of the coefficients on LCR and NSFR across all quantiles of profitability suggest that LCR and NSFR have a minor quantitative impact on bank profitability. We then test and find that the Basel III liquidity constraints have a significantly different impact on banks with very low profits compared to banks who enjoy high profitability, emphasizing the need to use a quantile approach. We plot the coefficients to illustrate the impact of liquidity constraints across different conditional profitability spectrums. Lastly, we find that small banks are more vulnerable to short term liquidity risks (LCR) and big banks are more susceptible to medium to long term liquidity risks (NSFR). This suggests that considerations should be given to tailoring liquidity regulations based on the bank size and the relative bank profitability. The quantitatively small impact of the constraints suggest that Basel III has successfully set liquidity requirements to minimize the impact on bank profitability and the likelihood of an industry-wide liquidity crisis.

How does bank equity affect credit creation? Multiplier effects under Basel III regulations

Both equity and regulation play key roles in determining the ability of banks to create credit. Equity varies endogenously, while regulations are exogenously imposed. This study proposes a banking model to investigate how changes in bank equity due to interest receipts and expenditures affect credit and money creation under Basel III regulations. Four Basel III regulations—the capital adequacy ratio, the leverage ratio, the liquidity coverage ratio, and the net stable funding ratio—are discussed. Their effect on credit creation are demonstrated by the changes that occur in the credit supply in response to the changes in equity arising from interest payments. This study identifies seven regulatory scenarios under these four regulations. In each scenario, there exists a multiplier that relates the change in equity to the resultant change in the credit supply. Correspondingly, there is a multiplier effect on the money supply. This study sheds new light on how bank equity and Basel III regulations affect credit and money creation.

Release of a liquidity regulation: What do we learn for credit and house prices?

This paper studies the effects of the release of a limit on banks’ maturity transformation – akin to the Net Stable Funding Ratio – for mortgage supply and house prices. After the regulatory easing, credit supply increased only for the banks that were previously constrained by the regulation and not for the others. We also show that the expansion in mortgages triggered by the deregulation accelerated house prices. The effect was channeled through higher demand for housing and the relaxation of borrowers’ financial constraints. Even though the impact of the credit supply shock persisted, the interaction between credit and house prices was not conducive to a housing market overheating.

A macro-financial perspective to analyse maturity mismatch and default

The Basel Committee proposed the Net Stable Funding Ratio (NSFR) to curb excessive maturity mismatch within the banking sector. However, it remains to be ascertained as to what are the financial and real effects of the NSFR on bank credit quality, investment, and the pass-through of monetary policy. This paper develops a nominal dynamic general equilibrium model featuring bank maturity mismatch and the moral hazard due to costly monitoring. First, I show that a tightening of the NSFR to move loan maturity towards the long-run capital investment cycle would only increase real investment if it sufficiently improved bank credit quality. Then in the numerical example calibrated with the US data, I show that such tightening of the NSFR can indeed increase real investment and also reduce the aggregate fluctuation of the economy. In the steady states, a 10% tightening in the NSFR can decrease net charge-offs of non-performing loans by about 0.06 pp annually, despite squeezing bank interest margins. Moreover, the moral hazard stemming from banks’ unobserved monitoring efforts impairs the pass-through of monetary policy. However, a 10% tightening in the NSFR improves the pass-through of a 20-bp policy rate reduction by around 17% annually. Finally, the model simulates the stochastic dynamic equilibrium path to study the propagation of shocks, demonstrating that the NSFR complements monetary policy in reducing financial frictions.

Net Stable Funding Ratio, Contingent Convertible Capital, Covid-19 and Bank Profitability: Evidence from Non-linear Panel Relationship

Net Stable Funding Ratio, Contingent Convertible Capital, Covid-19 and Bank Profitability: Evidence from Non-linear Panel Relationship

The Impact of Net Stable Funding Ratio (NSFR) Regulations of Basel-III on Financial Profitability and Stability: A Case of Asian Islamic Banks

The Impact of Net Stable Funding Ratio (NSFR) Regulations of Basel-III on Financial Profitability and Stability: A Case of Asian Islamic Banks

Bank asset allocation and finance structure under uncertainty in Vietnam

PurposeThe paper investigates the link between uncertainty and banks' balance sheet reactions.Design/methodology/approachThe study employs bank-level data in Vietnam during 2007–2019 to measure micro uncertainty in banking through the dispersion of bank-level shocks. Empirical regressions are performed by the two-step system generalized method of moments (GMM) estimator and then verified using the least squares dummy variable corrected (LSDVC) technique.FindingsBanks tend to reduce risky loans, hoard more liquidity and decrease financial leverage in response to higher uncertainty. The relationship between uncertainty and banks' balance sheet reactions is more pronounced for banks that suffer more credit risk and overall risk, thus supporting the precautionary motive of banks. Additionally, uncertainty also leads to a decline in the Net Stable Funding Ratio (NSFR) under Basel III, implying that banks may fail to find a more stable source of funding and be more subject to maturity mismatch during periods of higher uncertainty.Originality/valueThe paper is the first to explore comprehensively the relationship between uncertainty and banks' balance sheet aspects as simultaneously estimated by bank loans, bank liquidity and bank leverage. While many other uncertainty measures display aggregate uncertainty sources, an important contribution in this study is to anatomize uncertainty originating exclusively from banking at a disaggregate level. Besides, shedding light on how uncertainty drives bank funding liquidity as captured by the NSFR under Basel III is entirely novel in the literature.

The Basel III net stable funding ratio and a risk-return tradeoff: Bank-level evidence from Vietnam.

The Net Stable Funding Ratio (NSFR) liquidity rule under Basel III guidelines is designed to handle long-term liquidity risk, promoting the sustainable structures of bank funding. This study estimates the NSFR and analyses the impact of this liquidity ratio on banks according to a risk-return trade-off in Vietnam prior to the Basel III implementation. Using yearly data for commercial banks from 2007 to 2018, I find that banks with higher NSFR gain more potential benefits than banks with lower NSFR. Concretely, a rise in NSFR increases bank profitability and decreases bank funding costs, credit risks and liquidity creation, as evidenced by a comprehensive set of alternative measures. The findings of this study offer insightful implications on the bank policy framework advocating the Basel III liquidity regulation in Vietnam as well as other emerging markets.

Liquidity risk and regulation in the Organization of the Islamic Cooperation (OIC) banking industry

The recurring crises have evidenced poor liquidity risk management and ineffective regulation in banking. Consequently, banking regulations have undergone continuous reforms to bolster stability in the banking system. Nonetheless, theoretical and empirical evidence provide conflicting results that warrant comprehensive research, particularly for emerging Islamic banking. This study examines the role of banking regulation on the liquidity risk of 245 conventional banks and 68 Islamic banks from selected 14 Organization of the Islamic Cooperation (OIC) from 2000 to 2017 utilising the dynamic panel GMM (generalized method of moments) technique. We measure liquidity risk using the Net Stable Funding Ratio (NSFR) and the total financing-to-total deposits and short-term funding (LDEP). Meanwhile, the regulatory measures are asset restriction (AR), private monitoring (PM), supervisory power (SP) and capital requirements (CR). The findings suggest that regulation has a limited impact on bank liquidity risk. The CR supports the value creation of regulation through the reduction in banks’ liquidity risks, while PM and SP are agency costs of regulation that lead to higher liquidity risks. The impact of CR is lower on liquidity risk in Islamic banking than conventional ones, probably due to limited Islamic liquidity risk management facilities. Thus, regulators should strengthen Islamic liquidity risk instruments and markets to facilitate Islamic banking growth.

Basel III liquidity regulatory framework and bank liquidity creation in MENA countries

PurposeThis paper aims to investigate the potential impact of the Basel III liquidity requirements, namely, the net stable funding ratio (NSFR) and the liquidity coverage ratio (LCR), on bank liquidity creation.Design/methodology/approachThe authors developed a dynamic panel model using the Quasi-Maximum Likelihood estimation on an unbalanced panel dataset of 129 commercial banks operating in 10 Middle Eastern and North African (MENA) countries from 2009 to 2017.FindingsThe results show that the NSFR significantly negatively affects liquidity creation. Similarly, the LCR exerts a substantial negative impact on the liquidity creation of the sampled MENA banks. These findings suggest that complying with both liquidity requirements tends to curtail liquidity creation. Moreover, further regression analysis of large and small bank sub-samples uncovered results similar to the overall MENA sample.Research limitations/implicationsThe findings raise interesting policy implications and suggest a trade-off between the benefits of the financial resiliency induced by implementing liquidity requirements and the creation of liquidity essential for promoting economic growth in the region.Originality/valueMost empirical research focuses on the relationship between bank capital and liquidity creation. To the knowledge, this paper is the first to provide empirical evidence on the effect of both the NSFR and LCR regulatory liquidity standards on bank liquidity creation in the MENA region.