Search results

In a bid to enhance the stability of banks, supervisory authorities in sub-Sahara Africa (SSA) have also adopted international bank regulatory standards based on the Basel core principles. This paper aims to investigate the effectiveness of these regulations in mitigating Bank risk (instability) in SSA. The focus of empirical analysis is on examining the implications of four regulations (capital, activity restrictions, supervisory power and market discipline) on risk-taking behaviour of banks.

This paper uses two dimensions of financial stability in relation to two different sources of bank risk: solvency risk and liquidity risk. This paper uses information from the World Bank Regulatory Survey database to construct regulation indices on activity restrictions and the three regulations pertaining to the three pillars of Basel II, i.e. capital, supervisory power and market discipline. The paper then uses a two-step system generalised method of moments estimator to estimate the impact of each regulation on solvency and liquidity risk.

The overall results show that: regulations pertaining to capital (Pillar 1) and market discipline (Pillar 3) are effective in reducing solvency risk; and regulations pertaining to supervisory power (Pillar 2) and activity restrictions increase liquidity risk (i.e. reduce bank stability).

Given some evidence from other studies which show that market power (competition) tends to condition the effect of regulations on bank stability, it would have been more informative to examine whether this is really the case in SSA, given the low levels of competition in some countries. This study is limited in this regard.

The key policy implications from the study findings are three-fold: bank supervisory agencies in SSA should prioritise the adoption of Pillars 1 and 3 of the Basel II framework as an effective policy response to enhance the stability of the banking system; a universal banking model is more stability enhancing; and there is a trade-off between stronger supervisory power and liquidity stability that needs to be properly managed every time regulatory agencies increase their supervisory mandate.

This paper provides new evidence on which Pillars of the Basel II regulatory framework are more effective in reducing bank risk in SSA. This paper also shows that the way regulations affect solvency risk is different from that of liquidity risk – an approach that allows for case specific policy interventions based on the type of bank risk under consideration. Ignoring this dual dimension of bank stability can thus lead to erroneous policy inferences.

This study aims to test empirically the differences between Islamic and conventional banks in terms of impacts of the audit committees' quality on financial performance between Subprime and Corona crises.

The variables are articulated in four hypotheses tested by the GLS analysis. The data were collected via DATASTREAM and from banks' annual reports. The collected data covered four continents: America, Asia, Africa and Europe. The financial performance measures and audit committee's determinants of the conventional and Islamic banks concerned 112 banks of each type after the Subprime crisis and before the Corona crisis (2010–2019).

Results showed that the audit committee reduced the profitability of two bank types. Moreover, it harmed the conventional banks' efficiency, but reported an unclear effect within Islamic banks. Even so, the authors noticed that the audit committee had a positive impact for the conventional banks' liquidity, while the same effect was apparently ambiguous on the Islamic banks' liquidity. For solvency, the audit committee positively influenced conventional banks, while it affected that of Islamic banks.

Empirically, the authors’ results can serve as a reference for decision-makers allowing to clarify the data on the financial competitiveness of two bank types to facilitate the planning of strategic performance programs based on the audit committee quality. Theoretically, researchers found that the differences between the results are due to the audit committee quality of each bank type or to the financial performance evaluation method. However, there are further factors that are related to the research peculiarities, the methodology, the data and the interpretation.

Based on the comparative literature review between conventional and Islamic banks, this study is the first conditional and comparative research between the audit committee quality and the financial performance of conventional and Islamic banks in a specific period (after Subprime and before Corona crises).

While previous literature has emphasized the causal relationship from liquidity to capital, the impact of interbank network characteristics on this relationship remains unclear. By applying the interbank network simulation, this paper aims to examine whether the causal relationship between capital and liquidity is influenced by bank positions in the interbank network.

Using the sample of 506 commercial banks established in 28 European countries from 2001 to 2013, the author adopts the generalized method of moments simultaneous equations approach to investigate whether interbank network characteristics influence the causal relationship between bank capital and liquidity.

Drawing on a sample of commercial banks from 28 European countries, this study suggests that the interconnectedness of banks within interbank loan and deposit networks shapes their decisions to establish higher or lower regulatory capital ratios in the face of increased illiquidity. These findings support the implementation of minimum liquidity ratios alongside capital ratios, as advocated by the Basel Committee on Banking Regulation and Supervision. In addition, the paper underscores the importance of regulatory authorities considering the network characteristics of banks in their oversight and decision-making processes.

This paper makes a valuable contribution to the current body of research by examining the influence of interbank network characteristics on the relationship between a bank’s capital and liquidity. The findings provide insights that add to the ongoing discourse on regulatory frameworks and emphasize the necessity of customized approaches that consider the varied interbank network positions of banks.

In this paper, the authors study the failure of Russian banks between 2012 and 2019.

The authors analyze the entire population of Russian banks and combine a logit model with the survival analysis.

In addition to the usual determinants, the authors find that not-failed banks have higher levels of fulfillment of the Central Bank requirements of solvency, liquidity, provide fewer loans to their shareholders and own more shares of other banks. The results of this study suggest an asymmetric effect of the strategic orientation of banks: whereas the proportion of deposits from firms is negatively related to the probability of failure, the loans to firms are positively related to bankruptcies. According to this research, the fact of being controlled by a foreign bank has a significant negative relationship with the likelihood of failure and moderates the effect of bank size, performance and growth on the bankruptcy likelihood.

On the whole, the results of this study support the new Central Bank rules, but show that the thresholds imposed by the Russian regulator actually do not make a difference between failed and not failed banks in the short and medium term.

The authors specially focus on the effectiveness of new rules issued by the Central Bank of Russia in 2013.

This study empirically tests the use of loan loss provisions (LLPs) for earnings and capital smoothing when emphasis is laid on banks' riskiness and adoption of the International Financial Reporting Standards (IFRSs) in Nigeria.

Annual bank-level data are hand-extracted between 2007 and 2017 from annual reports of a sample 16 deposit money banks (DMBs), and analysed using appropriate panel regression models subsequent to a number of diagnostic tests including heteroscedasticity, autocorrelation and cross-sectional dependence. The use of both reported LLPs (TLLP) and discretionary LLPs (DLLP) for earnings and capital management is tested to advance the practice in the literature.

Generally, the study finds that Nigerian DMBs manage capital via LLPs, while mixed results are obtained for earnings smoothing. However, during IFRS, Nigerian DMBs' management of capital is identifiable with TLLP, while smoothing of earnings is peculiar to DLLP. Additionally, evidence of the improvement in loan loss reporting quality expected during IFRS for riskier Nigerian DMBs, could not be attained. This is corroborated by the study's findings of the use of both TLLP and DLLP for earnings and capital management during IFRS by DMBs in solvency crisis against the only use of TLLP to manage capital found for the entire period.

The evidential capital and earnings lopsidedness may subject Nigerian DMBs' going-concern to a lot of questions.

The study sets a foremost record in the empirical test of managerial opportunistic behaviour embedded in earnings and capital concurrently while accounting for loan losses by all categories of Nigerian DMBs in terms of riskiness, following accounting regime change.

This paper aims to study the impact of (regulatory and nonregulatory) liquidity on contingent convertible (CoCo) issuance and the relationship between CoCos and asset quality.

The analysis of this study comprises two stages. In the first stage, the authors used a logit model to test whether banks with riskier assets as well as lower solvency and (regulatory and nonregulatory) liquidity are more likely to issue CoCos. In the second stage, the authors used univariate analysis and fixed effects regression to measure the impact of Additional Tier 1 (AT1) CoCos on the quality of the issuer’s assets.

The study shows that regulatory liquidity ratios are negatively related to CoCo issuance. This study also finds that the likelihood to issue CoCo is higher when banks have lower regulatory capital or are less risky. Asset quality is found to not change significantly after the issuance. All in all, these results suggest that while solvency regulation is primarily regarded as the main motivation for CoCo issuance, liquidity regulation also matters.

Despite the fact that CoCos have been emerging as an alternative way to help banks meet regulatory capital requirements, the paper argues that the relation between liquidity regulation and CoCos should be taken into account.

This study presents an empirical analysis on the CoCos instrument, focusing on the relationship between AT1 CoCos and liquidity regulation. Therefore, it serves to fill a gap in the literature on the underlying forces behind CoCo issuance. Moreover, this study measures the impact of AT1 CoCos issuance on bank risk, particularly on the quality of the issuer’s assets.

This paper aims to empirically assess the performance of Islamic banks (IBs) and conventional banks (CBs) in Qatar before and after the imposition of the economic blockade on Qatar and the significance of the blockade’s subsequent impact.

This study focuses only on the domestic commercial banks comprising four IBs and five CBs operating in Qatar. The banks’ financial reports are used as a secondary source to generate data. A study period from 2015 to 2019, separated into pre-blockade and post-blockade periods and comprising data on a semi-annual basis, was examined. Financial ratios and t-tests are used to compare bank performance and test the significance level of the blockade, respectively.

Generally, the findings show that IBs slightly outperformed CBs. Solvency ratios show strong capitalization (measured by capital adequacy ratio, CAR) and external fund (measured by equity multiplier ratio, EMR) reliance of the banks, despite minor fluctuations. Yet, only the CAR of CBs has been significantly affected by the blockade. Profitability (measured by return on assets, ROA and return on equity, ROE) of both bank groups grew unsteadily over the period, but IBs remained more efficient (measured by operating efficiency, OEOI) than CBs. Liquidity ratios indicate almost similar depositor fund utilization (measured by loans to deposit ratio, LDR) and credit offering (measured by loans to assets ratio, LAR) by the banks. All three metrics were weakly impacted. In terms of asset quality, bad loans (measured by non-performing loans ratio, NPL) and provisions (measured by loan loss provisions, LLP) surged moderately post-blockade. The blockade affected both groups’ asset quality.

To the author’s knowledge, this is the first study to comparatively examine the performance of Qatari IBs and CBs during the latest economic embargo and their exposure to the crisis.

Financial health of a corporation is a great concern for every investor level and decision-makers. For many years, financial solvency prediction is a significant issue throughout academia, precisely in finance. This requirement leads this study to check whether machine learning can be implemented in financial solvency prediction.

This study analyzed 244 Dhaka stock exchange public-listed companies over the 2015–2019 period, and two subsets of data are also developed as training and testing datasets. For machine learning model building, samples are classified as secure, healthy and insolvent by the Altman Z-score. R statistical software is used to make predictive models of five classifiers and all model performances are measured with different performance metrics such as logarithmic loss (logLoss), area under the curve (AUC), precision recall AUC (prAUC), accuracy, kappa, sensitivity and specificity.

This study found that the artificial neural network classifier has 88% accuracy and sensitivity rate; also, AUC for this model is 96%. However, the ensemble classifier outperforms all other models by considering logLoss and other metrics.

The major result of this study can be implicated to the financial institution for credit scoring, credit rating and loan classification, etc. And other companies can implement machine learning models to their enterprise resource planning software to trace their financial solvency.

Finally, a predictive application is developed through training a model with 1,200 observations and making it available for all rational and novice investors (Abdullah, 2020).

This study found that, with the best of author expertise, the author did not find any studies regarding machine learning research of financial solvency that examines a comparable number of a dataset, with all these models in Bangladesh.

Using bank-level data over the 1994–2015 period, the authors aim to investigate the role of bank-specific factors on credit risk in Italy by considering two different groups of banks, namely, cooperative and non-cooperative (commercial and popular), in different local markets.

Relying on highly territorially disaggregated data at labour market areas’ level, the authors estimate the impact of the role of bank-specific factors on credit risk in Italy from the estimation of a fixed-effect estimator. Non-performing loans to total loans has been used as a proxy of credit risk; the bank-specific factors are as follows: growth of loans, reflecting credit policy; log of total assets, controlling for banks’ size; loans to total assets, reflecting the volume of credit market; equity to total assets, capturing the solvency of banks and reflecting their capital strength; return on assets, reflecting the profitability of banks; deposits to loans, reflecting the intermediation cost; cost of total assets, reflecting the banks’ efficiency or volume of intermediation cost.

The empirical findings suggest that regulatory credit policy, capitalisation, volume of credit and volume of intermediation costs are the main bank-specific factors affecting non-performing loans. Nevertheless, the present analysis suggests that the behaviour of cooperative banks’ behaviour seems to be in line with that of commercial rather than popular banks, casting doubts about the feasibility of their credit policies. It turns out that recent reforms involving popular and cooperative banks represent the first step toward the enhancement of the stability and efficiency of the Italian banking system. While the present study’s benchmark results are not particularly affected by the degree of competition in the banking sector and by banks’ size, it shows that both cooperative and non-cooperative banks have undertaken more prudent credit policies after the advent of the financial crisis and the introduction of the Basel regulation.

The relationship between bank-specific factors and credit risk has been analysed using a rich sample of cooperative, commercial and popular banks in Italy over the 1994–2015 period. The authors rely on labour market areas being sub-regional geographical areas where the bulk of the labour force lives and works. The contribution is motivated by the financial distress experienced after the 2008 financial crisis, which has significantly hit the Italian banking system and cooperative banks in particular.

This study aims to capture the “persistence effect” of credit risk in Indian banking industry using the bank-level data spanning over the period of 19 years from 1998/1999 to 2016/17. Alongside, the study explored how the bank-specific, industry-specific, macroeconomic variables alongside regulatory reforms, ownership changes and financial crisis affect the bank's asset quality in India.

Using two-step system generalized method of moment (GMM) approach, the study derives key factors that affect the bank's asset quality in India.

The empirical results confirm the time persistence of credit risk among Indian banks during study period. This reflects that bank defaults are expected to increase in the current year, if it had increased past year due to time lag involved in the process of recovery of past dues. Further, higher profitability, better managerial efficiency, more diversified income from nontraditional activities, optimal size of banks, proper credit screening and monitoring and adherence regulatory norms would help in improving the credit quality of Indian banks.

The practical implication drawn from the study is that nonaccumulation of nonperforming loans (NPLs), higher profitability, better managerial efficiency, more diversified income from nontraditional activities, optimal size of banks, proper credit screening and monitoring and adherence regulatory norms would help in improving the credit quality of Indian banks.

This study is probably the first one that identifies in addition to the current year, whether lag of bank industry-macroeconomic affects the level of NPLs of Indian banks. So far, such an analysis has received less attention with respect to Indian banking industry, especially immediate aftermath of the global financial crisis.