We analyze regulatory capital requirements where the amount of required capital depends on the level of risk reported by the banks. It is shown that if the supervisors have a limited ability to ...identify or to sanction dishonest banks, an additional, risk-independent leverage ratio restriction may be necessary to induce truthful risk reporting. The leverage ratio helps to offset the banks’ potential capital savings of understating their risks by (i) reducing banks’ put option value of limited liability
ex ante, and by (ii) increasing the banks’ net worth, which in turn enhances the supervisors’ ability to sanction banks
ex post.
Purpose
Market discipline is an important part of financial regulation, under Basel II and III. This paper aims to provide evidence on market discipline in Pakistan. Specifically, the authors have ...analyzed the impact of CAMEL variables on costs of funds and deposit switching.
Design/methodology/approach
This study has used panel data related to different banking and macroeconomic variables. The sample period is 2004–2017 so it has covered the changing regulations that became binding for banks under Basel II and III. Quarterly data has been collected from the financial disclosure of publicly listed banks. The total number of banks in the sample is 26. Among these, 24 are publicly listed. Foreign banks have not been included because their activities in Pakistan are quite limited.
Findings
It has been found that efficiency, liquidity, asset quality and capital adequacy are negatively related to costs of funds for banks. Capital adequacy, liquidity and profitability are negatively related to deposit switching.
Research limitations/implications
These results indicate the presence of market discipline and have generated valuable implications for bank managers and regulators.
Originality/value
In this study, the case of Pakistan is interesting. The country has experienced financial liberalization that sought to avoid government intervention and encourage a more “market-based” approach. This change in the system was made more pronounced by the privatization of nationalized banks, improvement in the market structure, reduction in barriers to entry and consolidation of smaller banks. As a result, the banking system has emerged as an important source of financing and it provides us motivation to look deeper into depositor discipline in banking sector.
The dataset presented in this article represents the pre-processed web server log file of the commercial bank. The source of data is the web server of the bank and keeps access of web users starting ...the year 2009 till 2012. It contains accesses to the bank website during and after the financial crisis. Unnecessary data saved by the web server was removed to keep the focus only on the textual content of the website. Many variables were added to the original log file to make the analysis workable. To keep the privacy of website users, sensitive information in the log file were anonymized. The dataset offers a way to understand the behavior of stakeholders during and after the crisis and how they comply with the Basel regulations. The behavior of users can be modeled using the multinomial logit model, which is in detail described in the research article 1 related to this data article.
•A fuzzy credibility model is proposed to estimate the Operational Value at Risk.•Estimating the operational value at risk combining internal and external data.•Determining the behaviuor of the OpVaR ...over time by using different risk profiles.•Integration of qualitative information, different risk profiles and databases.•Estimating the credibility of each external database with overlapping fuzzy sets.
Operational Risk (OpR) refers to the possibility of suffering losses resulting from inadequate or failure of processes and/or technology, inadequate behaviour of people or external events. OpR was one of the main risks that led to the 2008 global financial crisis. Limitations of the analytical models that are applied in estimating this risk surface when qualitative information, frequently associated with OpR events, is used. To determine the magnitude of OpR in financial organisations, qualitative data and also historical data from risk events can be used. Current research trends that focus on the development of analytical models, by using different databases, to estimate the Operational Value at Risk (OpVaR) still lack models based on qualitative information, risk management profiles and the ability to integrate different databases of OpR events. In this paper we present a fuzzy model to estimate the OpVaR of an organisation by working with two different databases that contain internal available data and external or observed data. The proposed model considers: (1) the intrinsic properties of the data as fuzzy sets related to the linguistic variables of the observed data (external) and the data from available databases (internal), and (2) a series of management profiles to mitigate the effect that external data usually causes in estimating the OpVaR of an organisation. The results obtained with the proposed model allow an organisation to estimate and determine the behaviour of the OpVaR over time by using different risk profiles. The integration of qualitative information, different risk profiles (ranging from weak to strong risk management), and internal and external databases contributes to the advancement of estimating the OpVaR in risk management .
Considering the fundamental role played by small and medium sized enterprises (SMEs) in the economy of many countries and the considerable attention placed on SMEs in the new Basel Capital Accord, we ...develop a distress prediction model specifically for the SME sector and to analyse its effectiveness compared to a generic corporate model. The behaviour of financial measures for SMEs is analysed and the most significant variables in predicting the entities’ credit worthiness are selected in order to construct a default prediction model. Using a logit regression technique on panel data of over 2,000 U.S. firms (with sales less than $65 million) over the period 1994–2002, we develop a one‐year default prediction model. This model has an out‐of‐sample prediction power which is almost 30 per cent higher than a generic corporate model. An associated objective is to observe our model's ability to lower bank capital requirements considering the new Basel Capital Accord's rules for SMEs.
Purpose
The purpose of this paper is to explore to what extent risk disclosure is associated with banks’ governance characteristics. The research also focuses on how the business environment and ...culture may create a bank’s awareness of risk management and its disclosure. This study is conducted in a setting where banks are not mandated to follow international standards for their risk disclosures.
Design/methodology/approach
Using 300 bank-year observations comprising hand-collected private commercial bank data, the study uses regression analysis to investigate the influence of risk governance characteristics on risk disclosure.
Findings
This paper reports a positive relationship between risk disclosure and banks’ governance characteristics, such as the presence of various risk committees and a risk management unit.
Practical implications
Because studies are lacking on risk disclosure and risk governance conducted in developing countries, it is expected that this research will make a significant contribution to the literature and provide a foundation for further research in this field.
Social implications
This study complements the corporate governance literature, more specifically the risk governance literature, by incorporating agency theory, institutional theory and proprietary cost theory to provide robust evidence of the impact of risk governance practices in the context of a developing economy.
Originality/value
Previous studies on risk disclosure and governance determinants primarily involve developed countries. This paper’s contribution is to examine risk disclosure and risk governance characteristics in a developing country in which reporting according to international standards is effectively voluntary.
•We investigate how global syndicate lenders react to borrowers’ rating changes.•The examination is centered around different conditions and regulatory regimes.•Downgrades lead to increased loan ...spreads and other non-price loan terms.•Upgrades do not elicit any effect.•The impact is stronger if downgrades raise risk weights for lenders post-Basel II.•The aggravating impact is mitigated in the presence of lending relationships.•Downgraded firms with strong previous performance and low debt are less affected.
This paper investigates how syndicated lenders react to borrowers’ rating changes under heterogeneous conditions and different regulatory regimes. Our findings suggest that corporate downgrades that increase capital requirements for lending banks under the Basel II framework are associated with increased loan spreads and deteriorating non-price loan terms relative to downgrades that do not affect capital requirements. Ratings exert an asymmetric impact on loan spreads, as these remain unresponsive to rating upgrades, even when the latter are associated with a reduction in risk weights for corporate loans. The increase in firm borrowing costs is mitigated in the presence of previous bank-firm lending relationships and for borrowers with relatively strong performance, high cash flows and low leverage.
This paper examines the diffusion of the Basel II Capital Accord into emerging markets (EMs). The literature on the diffusion of financial standards reinforces determinism: carefully derived ...standards such as those around financial liberalization are assumed to be applicable to all markets in an effort to promote stability and international harmonization. Attempts to use financial liberalization and macroprudential toolkits such as Basel II, however well intentioned, can increase rather than mitigate financial instability, due in part to unevenness in the adoption of financial standards. We analyse rich, action research data on the response of banks in 19 EMs in Asia, the Middle East, and Eastern Europe to the advent of Basel II. We find heterogeneous rather than universalistic responses, captured as four types of behavioural variations leading to differences in the intensity of diffusion: Reformist, Instigative, Disobliging and Cosmetic. The variations reflect regulatory neoliberalism. The typology contributes to our understanding of the interaction between bank behaviour, regulator stance and institutional context as determinants of the diffusion of global financial standards.
This paper introduces multi–period loan interest rate Nash game models in the banking sector under regulatory solvency constraints. By taking solvency constraint as Basel II and modelling economic ...condition as AR(1) process, we obtain results regarding the existence of loan interest rate equilibrium. A sensitivity analysis for the solvency constraint model and some numerical results are presented.
This article develops a methodology for quantifying model risk in quantile risk estimates. The application of quantile estimates to risk assessment has become common practice in many disciplines, ...including hydrology, climate change, statistical process control, insurance and actuarial science, and the uncertainty surrounding these estimates has long been recognized. Our work is particularly important in finance, where quantile estimates (called Value‐at‐Risk) have been the cornerstone of banking risk management since the mid 1980s. A recent amendment to the Basel II Accord recommends additional market risk capital to cover all sources of “model risk” in the estimation of these quantiles. We provide a novel and elegant framework whereby quantile estimates are adjusted for model risk, relative to a benchmark which represents the state of knowledge of the authority that is responsible for model risk. A simulation experiment in which the degree of model risk is controlled illustrates how to quantify Value‐at‐Risk model risk and compute the required regulatory capital add‐on for banks. An empirical example based on real data shows how the methodology can be put into practice, using only two time series (daily Value‐at‐Risk and daily profit and loss) from a large bank. We conclude with a discussion of potential applications to nonfinancial risks.
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