Basel II Research Papers - Academia.edu (original) (raw)

The new Basel II regulation contains a number of new regulatory features. Most importantly, internal ratings will be given a central role in the evaluation of the riskiness of bank loans. Another novelty is that retail credit and loans to small and medium-sized enterprises will receive a special treatment in recognition of the fact that the riskiness of such exposure derives to a greater extent from idiosyncratic risk and much less from common factor risk. Much of the work done on the differences between the risk properties of retail, SME and corporate credit has been based on parameterized models of credit risk. In this paper we present new quantitative evidence on the implied credit loss distributions for two Swedish banks using a non-parametric Monte Carlo re-sampling method following Carey [1998]. Our results are based on a panel data set containing both loan and internal rating data from the banks' complete business loan portfolios over the period 1997-2000. We compute the credit loss distributions that each rating system implies and compare the required economic capital implied by these loss distributions with the regulatory capital under Basel II. By exploiting the fact that a subset of all businesses in the sample is rated by both banks, we can generate loss distributions for SME, retail and corporate credit portfolios with a constant risk profile. Our findings suggest that a special treatment for retail credit and SME loans may not be justified. We also investigate if any alternative definition of SME's and retail credit would warrant different risk weight functions for these types of exposure. Our results indicate that it may be difficult to find a simple risk weight function that can account for the differences in portfolio risk properties between banks and asset types.

- by and +1
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- Monte Carlo, Panel Data, Economic Capital, Sampling methods

This paper discusses the issues about the stress testing of banks' credit portfolios. Currently there is no standard methodology to perform stress tests on banks' credit portfolios and no standard to evaluate self-reported stress testing results from banks. Some banks and bank supervisors have attempted to build econometrics models for macro stress tests. These models may provide inconsistent conclusions because of insufficient data available, unstable patterns of association, nonlinear behavior of credit loss in stress conditions, and the relevance of the historical data in calibrating the model parameters. These issues on econometrics models are illustrated with data of Hong Kong in 1997-2007. This period is an unusual stress period for Hong Kong economy, having Asian financial crisis in 1997, burst of internet bubble in 2001 and SARS outbreak in 2003. With the given data, we find that it is challenging to identify suitable models for forecasting. This paper proposes a methodology to estimate history-based stressed probability of default (PD) to complement the use of macro stress tests. By analyzing the default rates of the banking sector, bank supervisors can easily identify the stressed PD of individual banks' credit portfolios. These estimates are also very helpful for bank supervisors to verify those self-reported stressed PD and to compute the capital adequacy ratios of the banks under stress.

- by Michael C S Wong
- •
- Econometrics, Stress, Credit Risk, Financial Institutions

Due to recent financial crisis and regulatory concerns of Basel II, credit risk assessment is becoming one of the most important topics in the field of financial risk management. Quantitative credit scoring models are widely used tools for credit risk assessment in financial institutions. Although single support vector machines (SVM) have been demonstrated with good performance in classification, a single classifier with a fixed group of training samples and parameters setting may have some kind of inductive bias. One effective way to reduce the bias is ensemble model. In this study, several ensemble models based on least squares support vector machines (LSSVM) are brought forward for credit scoring. The models are tested on two real world datasets and the results show that ensemble strategies can help to improve the performance in some degree and are effective for building credit scoring models.

Purpose: This paper explores the factors that affected the voluntary risk-related disclosures in the individual annual reports for 2006 of Portuguese banks. We also explore the extent to which in those reports conformed to Basel II requirements in terms of the voluntary disclosure of operational risk and capital structure and adequacy matters.

- by Jonas Oliveira
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- Stakeholders, Content Analysis, Legitimacy, Capital Structure

Default probabilities (PDs) and correlations play a crucial role in the New Basel Capital Accord. In commercial credit risk models they are an important constituent. Yet, modeling and estimation of PDs and correlations is still under active discussion. We show how the Basel II one factor model which is used to calibrate risk weights can be extended to a model for estimating PDs and correlations. The important advantage of this model is that it uses actual information about the point in time of the credit cycle. Thus, uncertainties about the parameters which are needed for Value-at-Risk calculations in portfolio models may be substantially reduced. First empirical evidence for the appropriateness of the models and underlying risk factors is given with S&P data.

- by Thilo Liebig and +1
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- Credit Rating, Credit Risk, Value at Risk, Risk factors

The Basel II capital accord encourages financial institutions to develop rating systems for assessing the risk of default of their credit portfolios in order to better calculate the minimum regulatory capital needed to cover unexpected losses. In the internal ratings based approach, financial institutions are allowed to build their own models based on collected data. In this paper, a generic process model to develop an advanced internal rating system is presented in the context of country risk analysis of developed and developing countries. In the modelling step, a new, gradual approach is suggested to augment the well-known ordinal logistic regression model with a kernel based learning capability, hereby yielding models which are at the same time both accurate and readable. The estimated models are extensively evaluated and validated taking into account several criteria. Furthermore, it is shown how these models can be transformed into user-friendly and easy to understand scorecards. D

- by Jan Vanthienen and +1
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- Statistical Analysis, Modeling, Portfolio Management, Developing Countries

The Centre for Planning and Economic Research (KEPE) was established as a research unit, under the title Centre of Economic Research, in 1959. Its primary aims were the scientific study of the problems of the Greek economy, the... more

- by Prodromos Vlamis
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- Real Estate, Financial System, Banking Crisis, BanK Lending

Credit risk analysis is an important topic in the financial risk management. Due to recent financial crises and regulatory concern of Basel II, credit risk analysis has been the major focus of financial and banking industry. An accurate estimation of credit risk could be transformed into a more efficient use of economic capital. In this study, we try to use a triple-phase neural network ensemble technique to design a credit risk evaluation system to discriminate good creditors from bad ones. In this model, many diverse neural network models are first created. Then an uncorrelation maximization algorithm is used to select the appropriate ensemble members. Finally, a reliability-based method is used for neural network ensemble. For further illustration, a publicly credit dataset is used to test the effectiveness of the proposed neural ensemble model.

- by varun Satish
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- Economic Capital, Credit Risk, Basel II, Financial Risk

The 2004 Basel Committee on Banking Supervision Accord (known as Basel II) provides a common framework for banks to determine their minimum capital requirements for solvency purposes. For credit risk (the most important one for banking) Basel II uses an asymptotic single risk factor (ASRF) model and, as we demonstrate in the paper, assumes two fundamental hypotheses: Firstly, that there is only one risk factor common to all banks; and secondly, that the number of debtors in bank portfolios is high enough to ensure that no single debtor's behaviour can have a significant impact on the portfolio value as a whole. This allows capital requirements to be estimated by using a model based on the percentage of defaulting borrowers (x).

- by Jose Beltran
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- Applied Mathematics, Credit Risk, Risk factors, Basel II

In order to manage model risk, financial institutions need to set up validation processes so as to monitor the quality of the models on an ongoing basis. Validation can be considered from both a quantitative and qualitative point of view. Backtesting and benchmarking are key quantitative validation tools, and the focus of this paper. In backtesting, the predicted risk measurements

- by Bart Baesens and +1
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- Statistics, Risk Management, Mathematical Sciences, Case Study

El crecimiento de los microcréditos a nivel mundial, junto con la normativa internacional sobre requerimientos de capital (Basilea II), están impulsando a las instituciones de microfinanzas (IMFs) a una mayor competencia con las entidades bancarias por este segmento de negocio. La banca tradicionalmente ha contado con adecuados modelos de credit scoring para analizar el riesgo de incumplimiento, pero esto no ha sido así en las IMFs supervisadas. El objetivo de esta investigación es diseñar un modelo de credit scoring para una institución sometida a supervisión y especializada en microcréditos, como es la Entidad de Desarrollo de la Pequeña y Micro Empresa (Edpyme) del sistema financiero del Perú. El resultado de la investigación muestra la metodología y fases necesarias para diseñar el modelo, así como el proceso de valoración y validación para que pueda ser aplicado en el área de negocio, especialmente para establecer la política de tasas de interés con clientes. Por último, también se muestra cómo puede utilizarse el modelo para desarrollar una gestión del riesgo de crédito en el marco de los métodos IRB de Basilea II.

- by Juan Rubio
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- Credit Scoring, Peru, Financial System, Credit Risk

- by Salvador Rayo Canton
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- Credit Scoring, Financial System, Credit Risk, Basel II

In banking sector risk management is a key issue connected to the financial system stability.
Banking activities is becoming more complex, compounded by exploding technological capabilities, expanding product offerings and deregulation of competition. In other words, banking is a business of risk. For this reason, efficient risk management is extremely required. In this connection, banks have been moving towards the use of sophisticated models for measuring and managing risks. The Indian banking system is better prepared to adopt Basel II than it was for Basel I due to better risk awareness. The Basel II Accord had led the banks to new prudential norms like capital adequacy and identification of bad debts. Recently many banks have appointed senior managers to oversee a formal risk management function. The effective risk management lies with the ability to gauge the risks and to take appropriate measures. In the light of this, an analysis was carried out to highlight the NPAs position of Public and Private Sector Banks in India. The trend of NPAs in public and private sector banks in the last nineteen years shows that the level of NPAs in relation to the total assets has declined. The extent of NPA is comparatively higher in public sector banks compare to the private sector and foreign banks. The study also focuses on the risk management practices of Public and Private Sector Banks after the implementation of Basel II with the help of capital adequacy ratio for a period of 2007 to 2012. Hence an efficient risk management system is
needed.

- by IAEME Publication
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- Risk Management, Financial System, Basel II, Capital Adequacy Ratio

Micro, small and medium enterprises (MSMEs) are declared very capable of playing a crucial role for a region, specifically as one of the drivers of regional economic growth. Micro, small and medium enterprises (MSMEs) are defined as a means to introduce regional creative products and provide business opportunities for enterprise actors in the regions. In addition, the role of micro, small and medium enterprises (MSMEs) actors is considered very vital in order to increase per capita income and improve the economy of a region. Consequently, micro, small and medium enterprises (MSMEs) are required to actively participate in developing the country’s economy. The results of the study showed that 90.1% of MSMEs provided significant effects on the rate of economic growth.

- by SRI JUMINAWATI
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- Business, Islamic Economics, Economic Growth, Risk Management In Banking

The credit value-at-risk model underpinning the Basel II Internal Ratings-Based approach assumes that idiosyncratic risk has been diversified away fully in the portfolio, so that economic capital depends only on systematic risk contributions. We develop a simple methodology for approximating the effect of undiversified idiosyncratic risk on VaR. The supervisory review process (Pillar 2) of the new Basel framework offers a potential venue for application of the proposed granularity adjustment (GA).

- by Michael Gordy
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- Economic Capital, Value at Risk, Basel II, Systematic Risk

Credit risk concentration is one of the leading topics in modern finance, as the bank regulation has made increasing use of external and internal credit ratings. Concentration risk in credit portfolios comes into being through an uneven distribution of bank loans to individual borrowers (single-name concentration) or in a hierarchical dimension such as in industry and services sectors and geographical regions (sectorial concentration).To measure single-name concentration risk the literature proposes specific concentration indexes such as the Herfindahl–Hirschman index, the Gini index or more general approaches to calculate the appropriate economic capital needed to cover the risk arising from the potential default of large borrowers.However, in our opinion, the Gini index and the Herfindahl–Hirschman index can be improved taking into account methodological and theoretical issues which are explained in this paper.We propose a new index to measure single-name credit concentration risk and we prove the properties of our contribution.Furthermore, considering the guidelines of Basel II, we describe how our index works on real financial data. Finally, we compare our index with the common procedures proposed in the literature on the basis of simulated and real data.

- by Silvia Figini
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- Finance, Data Mining, Data Analysis, Regulation

يعتبر موضوع كفاية رأس المال المصرفي و اتجاه البنوك إلى تدعيم مراكزها المالية ، أحد الاتجاهات الحديثة في إدارة البنوك ، و في إطار سعي الجهاز المصرفي في معظم دول العالم إلى تطوير القدرات التنافسية في مجال المعاملات المالية ، و في ظل... more

- by Alia Ellafi
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- Banking, Basel II, رأس المال الفكري, Basel III

Ines dr. Informatike i računarstva UVOD U konačnici uspješnost jedne organizacije se ogleda u učinkovitosti, djelotvornosti ovisi od funkcioniranja informacijskog sistema, iz tih razloga neophodno se bazirati na njegovom upravljanju, kontroli, i reviziji. Revizija informacionih sistema ili još poznata kao Information system audit, omogućuje neovisnu i objektivu procjenu rizika rada informacionih sistema, testiranje modula, te da bi se na taj način došlo do procjene kako za unutrašnje, tako i za vanjske saradnike, zadovoljava li informacioni sistem ciljevima poslovanja organizacije, omogućuje li neometano rad, te da li je oprema zaštićena, a kao rezultat se dobije pohvala ili moguća eventualna preporuka za poboljšanje. Dugi niz godina su se tražili profesionalni standardi koji se opisivali i propisivali najbolje načine za reviziju informacionih sistema. U današnje vrijeme svjetski najčešće korišteni standardi i norme su ITIL, CobiT, ISO 27001, Val IT, Basel II, Sarbanes-Oxley, CMMI, i sl. čiji cilj je usklađivanje informatike i poslovanja. Najvažniji i najčešće korišteni standardi, norme i metodologije koje se koriste su navedene u tabeli.

- by Ines Isakovic
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- Basel II, ISO/IEC 27001, COBIT Analysis

Harmonization plays an important role in organizations that are seeking to resolve manifold needs at their different hierarchical levels through multiple models such as CMMI, ISO 90003, ITIL, SWEBOK, COBIT, amongst others. A great diversity of models involves a wide heterogeneity not only about structure of their process entities and quality systems, but also with regards to terminology. This article presents an ontology which: provides the main concepts related to harmonization of multiple models; is supported by a web tool and; has been applied for the harmonization of COBIT 4.1, Basel II, VAL IT, RISK IT, ISO 27002 and ITIL.

- by César Pardo
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- Computer Software, Software Process Improvement, Standard Model, Basel II

Both Andreas Libavius and Heinrich Khunrath graduated from Basel Medical Academy in 1588, though the theses they defended reveal antithetical approaches to medicine, despite their shared interests in iatrochemistry and transmutational alchemy. Libavius argued in favour of Galenic allopathy while Khunrath promoted the contrasting homeopathic approach of Paracelsus and the utility of the occult doctrine of Signatures for medical purposes. This article considers these differences in the two graduates' theses, both as intimations of their subsequent divergent notions of the boundaries of alchemy and its relations with medicine and magic, and also as evidence of the surprisingly unstable academic status of Paracelsian philosophy in Basel, its main publishing centre, at the end of the sixteenth century.

- by Peter J Forshaw
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- Homeopathy, Alchemy, Iatrochemistry, Allopathy

The study aims to ascertain the effect of risks on the profit efficiency of Ghanaian banks. Ratio analysis is used to measure risk while the mean of ratios is used to test the returns to scale property of the industry. The non-parametric data envelopment analysis profit efficiency scores are estimated using the ratio of cost and revenue approach and using the bootstrapped truncated regression the nexus is ascertained. Data from 2000-2015 of 32 Ghanaian banks was used. The study found significant impacts on profit efficiency, negative and positive for liquidity risk and market risk respectively. Credit risk, insolvency risk, and operational risk have a negative and insignificant impact on profit efficiency and capital risk, positive and insignificant. In the absence of insolvency risk, capital risk has a negative impact and in the absence of regulation, operational risk has a positive impact all of which are insignificant. A pooled industry data exhibited a variance returns to scale property. There is comparatively high-profit efficiency at 68% calculated based on each year’s returns to scale over the study period which shows the closeness of the banks to the benchmark efficiency frontier. Regulation and diversification respectively have a negative and positive impact while intermediation, return on asset and concentration in the absence of size, has a positive and significant impact on profit efficiency. This paper is the first risk-efficiency study of its kind that investigates the nexus between various risk types with profit efficiency. It has also covered all key risk types specified in the Basel Accord (credit, liquidity, market and operational risk) and this will provide relevant knowledge to the government, regulatory supervisory bodies, policy makers, practitioners as well as academics. Theories have also been aligned to the study of risk profit efficiency nexus.

Risk management plays an important role in ensuring the safety and survival of banking institutions. Basel II Accord is an international regulatory attempt aimed at strengthening the risk management practices in the internationally active banks. The Basel II Accord is the framework developed in 1999 by the Central Banks of G10 countries to regulate the risk management process in large internationally active banks in their domains and in the Organization for Economic Cooperation and Development (OECD) member countries. The framework was issued principally to address the issue of the minimum capital requirements that have to be kept aside by banks, to be able to face any economic stress, and for protecting the international financial system from financial crises that could lead to the collapse of banks. This research examines the impact and challenges of Basel II on the risk management practices in Nigerian banks, and the extent of progress the banks have made in implementing the Accord within the milieu of the Central Bank of Nigeria’s guidelines. The sample population comprised all the banking institutions in Nigeria, including commercial banks, mortgage banks, finance houses and merchant banks. A random sample of 15 commercial banks was taken from which sampling units of 60 respondents with risk and control functions were purposively selected from each of the sampled banks. What informed the choice of the commercial banks as the sample source was because the Central Bank of Nigeria appeared to have considered the commercial banks as the centre focus of Basel II implementation for a start. Four hypotheses were formulated to validate the observations that necessitated the study. All the hypotheses were tested at 0.05 level of significance using the ANOVA, regression and t-test models. The following findings were made from the study after testing the hypotheses formulated for the study: All the Nigerian banks face almost the same sets of challenges in implementing Basel II requirements; the Basel II Accord caused significant change in capital measurement and allocation; the Accord has improved the risk management practices in Nigerian banks, and Nigerian banks have made some progress in Basel II implementation project. At the end of the research, it was recommended that the Central Bank of Nigeria increase the level of awareness on Basel Accord; that the CBN should immediately enforce the Basel II regulations on all operators in the banking industry rather than focusing on commercial banks; that the banks should enlighten their Boards and senior management staff on the implications of Basel Accord on the banks’ businesses, and finally that the banks should find smarter ways to raise further capital in response to Basel II requirement.

- by Sikiru Salami
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- Finance, Banking, Corporate Finance, Risk Management

Globalisation necessitates drastic changes in the banking sector across countries. The regulation of banking in the developed industrial countries has increasingly focused on attaining financial stability. The Basel Committee on Banking Supervision provides a platform for regular cooperation on banking supervisory matters. Its objective is to enhance understanding of key supervisory issues and improve the quality of banking supervision worldwide. Basel I focus more on credit risks, not on operational risks, by establishing a direct link between capital of a bank and its credit risk. The risk identified by Basel I does not express the multiple risks banks can be faced. Basel II addresses the gap by establishing rigorous risk and capital management requirements designed to ensure that a bank maintains capital reserves appropriate to its risk exposures. The Nigerian financial sector has performed well in Basel I implementation. Nigeria is set to implement the Basel II to ensure that better risk management is adopted in the nation's banking system. The study examines Basel II Accord implementation in Nigeria, explores its implications for the Nigeria banking system and issues with the Accord, and highlights recommendations for implementation of the Accord in Nigeria.

- by IOSR Journals
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- Finance, Corporate Governance, Banking, Risk Management

The Basel II Accord requires that banks and other Authorized Deposit-taking Institutions (ADIs) communicate their daily risk forecasts to the appropriate monetary authorities at the beginning of each trading day, using one or more risk models to measure Value-at-Risk (VaR). The risk estimates of these models are used to determine capital requirements and associated capital costs of ADIs, depending in part on the number of previous violations, whereby realised losses exceed the estimated VaR. McAleer, Jimenez-Martin and Perez-Amaral (2009) proposed a new approach to model selection for predicting VaR, consisting of combining alternative risk models, and comparing conservative and aggressive strategies for choosing between VaR models. This paper addresses the question of risk management of risk, namely VaR of VIX futures prices. We examine how different risk management strategies performed during the 2008-09 global financial crisis (GFC). We find that an aggressive strategy of choosing the Supremum of the single model forecasts is preferred to the other alternatives, and is robust during the GFC. However, this strategy implies relatively high numbers of violations and accumulated losses, though these are admissible under the Basel II Accord.

- by Michael McAleer and +1
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- Risk Management, International Finance, Global Financial Crisis, Managerial Finance
- by Vitthal Rathod
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- Econometrics, Statistics, Data Mining, Emerging Economies

Based on UK data for major retail credit cards, we build several models of Loss Given Default based on account level data, including Tobit, a decision tree model, a Beta and fractional logit transformation. We find that Ordinary Least Squares models with macroeconomic variables perform best for forecasting Loss Given Default at the account and portfolio levels on independent hold-out data sets. The inclusion of macroeconomic conditions in the model is important, since it provides a means to model Loss Given Default in downturn conditions, as required by Basel II, and enables stress testing. We find that bank interest rates and the unemployment level significantly affect LGD.

- by Jonathan Crook
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- Marketing, Econometrics, Forecasting, Decision Tree

The intensity of recent turbulence in financial markets has surprised nearly everyone. This paper searches out the root causes of the crisis, distinguishing them from scapegoating explanations that have been used in policy circles to divert attention from the underlying breakdown of incentives. Incentive conflicts explain how securitization went wrong, why credit ratings proved so inaccurate, and why it is

- by edward kane
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- Sociology, Financial Regulation, Emerging Market, Access to Finance

The introduction of the Basel II Accord has had a huge impact on financial institutions, allowing them to build credit risk models for three key risk parameters: PD (probability of default), LGD (loss given default) and EAD (exposure at default). Until recently, credit risk research has focused largely on the estimation and validation of the PD parameter, and much less on LGD modeling. In this first large-scale LGD benchmarking study, various regression techniques for modeling and predicting LGD are investigated. These include onestage models, such as those built by ordinary least squares regression, beta regression, robust regression, ridge regression, regression splines, neural networks, support vector machines and regression trees, as well as two-stage models which combine multiple techniques. A total of 24 techniques are compared using six real-life loss datasets from major international banks. It is found that much of the variance in LGD remains unexplained, as the average prediction performance of the models in terms of R 2 ranges from 4% to 43%. Nonetheless, there is a clear trend that non-linear techniques, and in particular support vector machines and neural networks, perform significantly better than more traditional linear techniques. Also, two-stage models built by a combination of linear and non-linear techniques are shown to have a similarly good predictive power, with the added advantage of having a comprehensible linear model component.

- by Bart Baesens
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- Marketing, Econometrics, Data Mining, Prediction

The Basel II capital adequacy framework constitutes a very comprehensive regulatory approach to risk assessment in banks. It is far more detailed and sophisticated than the first Basel accord. A special feature is that the new accord is not only targeting banks' financial risk exposures in terms of credit risks and market risks. The scope has been widened to also explicitly incorporate banks' exposure to operational risks in the capital adequacy requirement. For banks this novelty means a major change. Unless they choose to use the highly unsophisticated ‗basic indicator approach' or the ‗standardized approach' proposed in the new Basel accord, it will put significant pressure on them to develop and design appropriate internal risk information models and systems. In this paper we explore banks' operational risk assessment under Basel II in Sweden, where all banks-regardless of size-have to comply with the new regulatory framework. The overall aim is to provide deeper insights into the capability of banks to identify and measure exposures to operational risk and their choice of method for calculating regulatory capital against such exposures.

- by Renzo Chavez Chavez
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- Risk assessment, Operational Risk, Credit Risk, Basel II

This paper investigates the issues, challenges and implication of Basel II implementation for developing countries with a focus on Pakistan. The main objective of this paper is to identify the problems confronted by the regulators in their journey to Basel II implementation. The paper shows that the right balance between regulation, supervision and market discipline requires the mutual cooperation and assistance amongst the central Banks. The paper also emphasizes the role of educational institutions, banks training institution in developing the human resources in this regard. Our findings highlight the need for home and host supervisors of internationally active banking organization to develop and enhance the pragmatic communication and cooperation with regard to banks' Basel II implementation plans. This is necessary to reduce the burden on the banking industry and making it more efficient.

- by Safia Qamar Minhaj
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- Human Resource, Developing Country, Basel II, Market Discipline

This paper develops a dynamic stochastic general equilibrium model with interactions between an heterogeneous banking sector and other private agents. We introduce endogenous default probabilities for both firms and banks, and allow for bank regulation and liquidity injection into the interbank market. Our aim is to understand the importance of supervisory and monetary authorities to restore financial stability. The model is calibrated against real data and used for simulations. We show that liquidity injections reduce financial instability but have ambiguous effects on output fluctuations. The model also confirms the partial equilibrium literature results on the procyclicality of Basel II.

- by Gregory de Walque
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- Economics, Money, DSGE, Default Risk

A risk management strategy is proposed as being robust to the Global Financial Crisis (GFC) by selecting a Value-at-Risk (VaR) forecast that combines the forecasts of different VaR models. The robust forecast is based on the median of the point VaR forecasts of a set of conditional volatility models. This risk management strategy is GFC-robust in the sense that maintaining the same risk management strategies before, during and after a financial crisis would lead to comparatively low daily capital charges and violation penalties. The new method is illustrated by using the S&P500 index before, during and after the 2008-09 global financial crisis. We investigate the performance of a variety of single and combined VaR forecasts in terms of daily capital requirements and violation penalties under the Basel II Accord, as well as other criteria.

- by Juan-angel Jimenez-martin and +1
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- Risk Management, Applied Economics, Global Financial Crisis, Financial Crisis

The Basel Committee released in April 2016 its new directive d368 Interest Rate Risk in the Banking Book (IRRBB). This directive finally replaces the former text of July 2004 which was no more adapted from a methodological point of view but which was rich in recommendations and already included the fundamental principles to follow for managing interest rate risk in the banking book. Indeed, the new text does not appear as a break away from but rather as a continuation on an area that was neglected during the crisis. Where the text is revolutionary is that the regulator moved significantly away from a position of general but often vague principles to a much more demanding quality of management and modeling of IRRBB. Indeed, this text appears fundamental and raises the bar at the highest technical level, requiring banks to improve their methodologies, their expertise and to review their setup in a very short period of time. It also reassesses the responsibility of the management, a repeating leitmotiv since the crisis which should lead inevitably to the granting of licensing for executive officers of banks in the EU (and their removal in case of resolution). The text is complex, dense and still includes some grey areas. It is based on the latest improvements made in ALM, it requires to value almost “marked to model” the full balance sheet and it definitely deserves comments.

In , a robust risk management strategy to the Global Financial Crisis (GFC) was proposed under the Basel II Accord by selecting a Value-at-Risk (VaR) forecast that combines the forecasts of different VaR models. The robust forecast was based on the median of the point VaR forecasts of a set of conditional volatility models. In this paper we provide further evidence on the suitability of the median as a GFC-robust strategy by using an additional set of new extreme value forecasting models and by extending the sample period for comparison. These extreme value models include DPOT and Conditional EVT. Such models might be expected to be useful in explaining financial data, especially in the presence of extreme shocks that arise during a GFC. Our empirical results confirm that the median remains GFC-robust even in the presence of these new extreme value models. This is illustrated by using the S&P500 index before, during and after the 2008-09 GFC. We investigate the performance of a variety of single and combined VaR forecasts in terms of daily capital requirements and violation penalties under the Basel II Accord, as well as other criteria, including several tests for independence of the violations. The strategy based on the median, or more generally, on combined forecasts of single models, is straightforward to incorporate into existing computer software packages that are used by banks and other financial institutions.

Regulatory authorities pay considerable attention to setting minimum capital levels for different kinds of financial institutions. Solvency II, the European Commission's planned reform of the regulation of insurance companies is well underway. One of its consequences will be a shift in focus to internally based models in determining the regulatory capital needed to cover unexpected losses. This evolution emphasises the importance of credit risk assessment through internal ratings. In light of this new prudential regulation, this paper suggests a Basel II compliant approach to predicting credit ratings for non-rated corporations and evaluates its performance compared to external ratings. The paper provides an interesting modelling of non-financial European companies rated by S&P. In developing the model, broad applicability is set as an important boundary condition. Even though the model developed is fairly simple and maintains a high level of granularity, it gives high rates of accuracy and is very interpretable.

- by Bart Baesens
- •
- Economics, Credit Scoring, European Commission, Credit Rating

It is well known that the Basel II Accord requires banks and other Authorized Deposit-taking Institutions (ADIs) to communicate their daily risk forecasts to the appropriate monetary authorities at the beginning of each trading day, using one or more risk models, whether individually or as combinations, to measure Value-at-Risk (VaR). The risk estimates of these models are used to determine capital requirements and associated capital costs of ADIs, depending in part on the number of previous violations, whereby realised losses exceed the estimated VaR. McAleer et al. (2009) proposed a new approach to model selection for predicting VaR, consisting of combining alternative risk models, and comparing conservative and aggressive strategies for choosing between VaR models. This paper addresses the question of risk management of risk, namely VaR of VIX futures prices, and extends the approaches given in McAleer et al. (2009) and Chang et al. (2011) to examine how different risk management strategies performed during the 2008-09 global financial crisis (GFC). The empirical results suggest that an aggressive strategy of choosing the Supremum of single model forecasts, as compared with Bayesian and non-Bayesian combinations of models, is preferred to other alternatives, and is robust during the GFC. However, this strategy implies relatively high numbers of violations and accumulated losses, which are admissible under the Basel II Accord.

- by Michael McAleer and +1
- •
- Risk Management, Global Financial Crisis, Mathematical Sciences, Model Selection

- by Jorge Daniel Navarro
- •
- Finance, Regulation, Multidisciplinary, Concentration

This paper examines two major forces that may soon increase competition in the U.S. secondary conforming mortgage market: 1) the expansion of Federal Home Loan Bank mortgage purchase programs, and 2) the adoption of revised risk-based capital requirements for large U.S. banks (Basel II). We argue that this competition is likely to reduce the growth and relative importance of Fannie Mae and Freddie Mac and hence their franchise values and effective capital. Such developments could, in turn, lead to more risky behaviors by these two GSEs. It is this last consequence that warrants greater regulatory awareness. JEL Classification Numbers: G21, G28

- by Mac White
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- Risk Taking, Moral Hazard, Risk Based Capital, Basel II

The objective of this research is to develop a structural form probability of default model for small and medium-sized enterprises, dealing with the methodological issues which arise in the modelling of small commercial loan portfolios. Other motivations are to provide an extensive overview of the characteristics of SMEs, and to provide a list of characteristics for an SME PD model, e.g. time and cost efficiency, broad applicability, limited data requirements, and powerful in predicting default. The structural form model is developed and tested on a unique dataset of private firm's bank loans of a Dutch bank. The results are promising; the model output differs significantly between defaulted and non-defaulted firms. The structural form model can be used on its own, or as an additional variable in a credit risk model. A second PD model is developed using logistic regression with a number of financial ratios, including the structural form measure. This variable is significant in default prediction of SMEs and has some additional predictive power, next to the popular financial ratios. Overall, the results indicate that the structural form model is a good indicator for default of SMEs. (JEL: C51, C52, G21, G28, G33)

- by André Thibeault
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- Logistic Regression, Credit Risk, Prediction Model, Basel II

The Internal Ratings Based (IRB) approach for capital determination is one of the cornerstones in the proposed revision of the Basel Committee rules for bank regulation. We evaluate the IRB approach using historical business loan portfolio data from a major Swedish bank for the period 1994 to 2000. First, we estimate a duration model that takes into account both company, loan related and macroeconomic variables. Next, we obtain a Value-at-Risktype (VaR) credit risk measure, by model-based simulations. Moreover, we study how both the bank's credit risk and buffer capital changes over time (had the bank been subject to the proposed rules). This approach allows us to (i) make individual forecasts of default risk conditional on company, loan and macro variables, (ii) study portfolio credit risk over time, (iii) assess to what extent the new Accord will achieve its main objective of increasing credit risk sensitivity in minimal capital charges, and (iv) compare current capital requirements to those under the proposed system. Our results show that macro conditions have great explanatory power in predicting default risk and calculating credit risk. The IRB approach, although sensitive to the choice of some horizon parameters, is an achievement in the intended direction.

- by Kasper Roszbach
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- Credit Risk, Value at Risk, Default Risk, Basel II

Bankruptcy prediction has been a topic of research for decades, both within the financial and the academic world. The implementations of international financial and accounting standards, such as Basel II and IFRS, as well as the recent credit crisis, have accentuated this topic even further. This paper describes both regularized and non-linear kernel variants of traditional discriminant analysis techniques, such as logistic regression, Fisher discriminant analysis (FDA) and quadratic discriminant analysis (QDA). Next to a systematic description of these variants, we contribute to the literature by introducing kernel QDA and providing a comprehensive benchmarking study of these classification techniques and their regularized and kernel versions for bankruptcy prediction using 10 real-life data sets. Performance is compared in terms of binary classification accuracy, relevant for evaluating yes/no credit decisions and in terms of classification accuracy, relevant for pricing differentiated credit granting. The results clearly indicate the significant improvement for kernel variants in both percentage correctly classified (PCC) test instances and area under the ROC curve (AUC), and indicate that bankruptcy problems are weakly non-linear. On average, the best performance is achieved by LSSVM, closely followed by kernel quadratic discriminant analysis. Given the high impact of small improvements in performance, we show the relevance and importance of considering kernel techniques within this setting. Further experiments with backwards input selection improve our results even further. Finally, we experimentally investigate the relative ranking of the different categories of variables: liquidity, solvency, profitability and various, and as such provide new insights into the relative importance of these categories for predicting financial distress.

- by Bart Baesens
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- Engineering, Financial Distress, Logistic Regression, Discriminant Analysis

Rating agency default studies provide estimates of mean default rates over multiple time horizons but have never included estimates of the standard errors of the estimates. This is due at least in part to the challenge of accounting for the high degree of correlation induced by their cohort-based methodologies. In this paper, we present a method for estimating confidence intervals for corporate default rates derived through a bootstrapping approach. The work extends research in the academic literature on oneyear default rates ] to the multi-year horizon case. Our results indicate that historical mean speculative-grade default rates are generally measured fairly precisely, with standard errors less the 10% of the estimated means. Investment-grade default rates, however, are measured much less precisely, particularly for issuers rated single A or above. Precision increases at longer horizons. Of practical importance, the results indicate that Moody's long-term ratings satisfy the Basel II criteria for effectively distinguishing relative credit risk. This is true even for "lowdefault portfolio" portion of the rating scale -letter ratings Aaa, Aa, and single Abecause the default rates associated with these rating categories are significantly different from one another at the two-year and longer investment horizons.

- by Richard Cantor
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- Time Series, Credit Risk, Default Risk, Basel II

CENGİZ,Efsane, Basel I-II-III Capital Accord, Thesis of Master Degree, Ankara, 2013 In 1988, the Basel Committee, issued the Basel I Accord, in order to strengthen the structure of the banks .This consensus of the world's banking... more

- by Efsane Cengiz
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- Finance, Banking, Risk Management, Basel II

In 1988, an agreement was reached in Basel to set the common requirements of bank capital towards promoting the soundness and stability of the international banking system. Banks are required to hold capital in proportion to their perceived credit risks. In
June 2006 Basel Committee on Banking Supervision issued a comprehensive document on New Capital Adequacy Framework to replace the 1988 Basel Accord and to foster a strong emphasis on risk management and to encourage ongoing improvements in banks’ risk assessment capabilities. The paper examines the potential impact of Basel II on the banking sector of Bangladesh. A survey is conducted to find out the present status of the implementation of Basel II and their possible impact and reaction of the banking community. The result shows that the banking sector of Bangladesh is taking necessary steps to comply with Basel II requirement under the guidelines of Bangladesh Bank. The capital requirement under Basel II regime increased due to additional burden of capital from Market Risk and Operational Risk. There are many possible negative impacts of an unchecked implementation of Basel II. However, Basel II is here to stay and the competitive forces will compel banks to follow the example. The option here is to decide what form of the Basel II norms should be applied and to what extent to ensure the survival and growth for the developing economies. Ultimately, the norms are for strengthening the banking systems globally and this objective should not be lost. Bangladesh Economies need to be prepared and to adapt to the changing global conditions and to adapt the norms to their own advantage.

- by Dr. Mohammad Tariq Hasan
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- Basel II, Risk Management in Banks

Over the last two decades, many large banks have developed advanced quantitative credit risk models for allocating economic capital, measuring risk-adjusted returns at the businessline and individual credit level, and improving overall risk management. The advent of these new models and their incorporation into bank credit risk management were an important impetus for the effort to reform the Basel Committee's standards for regulatory capitalV Basel IIVand, in turn, the Basel II proposal is encouraging banks to upgrade their credit risk management approaches. 1 Under the Basel II proposal, banks with sufficiently sophisticated risk measurement and management systems can use their own internal systems to estimate key risk parameters that determine regulatory capital minimums.

- by Stijn Claessens
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- Credit Risk, Financial Services, Basel II, Consumer credit

In this paper we develop a model of the economic value of credit rating systems. Increasing international competition and changes in the regulatory framework driven by the Basel Committee on Banking Supervision (Basel II) called forth incentives for banks to improve their credit rating systems. An improvement of the statistical power of a rating system decreases the potential effects of adverse selection, and, combined with meeting several qualitative standards, decreases the amount of regulatory capital requirements. As a consequence, many banks have to make investment decisions where they have to consider the costs and the potential benefits of improving their rating systems. In our model the quality of a rating system depends on several parameters such as the accuracy of forecasting individual default probabilities and the rating class structure. We measure effects of adverse selection in a competitive one-period framework by parameterizing customer elasticity. Capital requirements are obtained by applying the current framework released by the Basel Committee on Banking Supervision. Results of a numerical analysis indicate that improving a rating system with low accuracy to medium accuracy can increase the annual rate of return on a portfolio by 30-40 bp. This effect is even stronger for banks operating in markets with high customer elasticity and high loss rates. Compared to the estimated implementation costs banks could have a strong incentive to invest in their rating systems. The potential of reduced capital requirements on the portfolio return is rather weak compared to the effect of adverse selection.

- by Walter Schwaiger
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- Applied Mathematics, Numerical Analysis, Adverse Selection, Credit Rating

To meet the Basel II regulatory requirements for the Advanced Measurement Approaches, the bank's internal model must include the use of internal data, relevant external data, scenario analysis and factors reflecting the business environment and internal control systems. Quantification of operational risk cannot be based only on historical data but should involve scenario analysis. Historical internal operational risk loss data have limited ability to predict future behaviour moreover, banks do not have enough internal data to estimate low frequency high impact events adequately. Historical external data are difficult to use due to different volumes and other factors. In addition, internal and external data have a survival bias, since typically one does not have data of all collapsed companies. The idea of scenario analysis is to estimate frequency and severity of risk events via expert opinions taking into account bank environment factors with reference to events that have occurred (or may have occurred) in other banks. Scenario analysis is forward looking and can reflect changes in the banking environment. It is important to not only quantify the operational risk capital but also provide incentives to business units to improve their risk management policies, which can be accomplished through scenario analysis. By itself, scenario analysis is very subjective but combined with loss data it is a powerful tool to estimate operational risk losses. Bayesian inference is a statistical technique well suited for combining expert opinions and historical data. In this paper, we present examples of the Bayesian inference methods for operational risk quantification.

- by Pavel Shevchenko
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- Risk Management, Low Frequency, Internal Control, Bayesian Inference

In order to promote financial stability, regulatory authorities pay a lot of attention in setting minimum capital levels. In addition to these requirements, financial institutions calculate their own economic capital reflecting the unexpected losses and true risk according to the specific characteristics of their portfolio. The current Basel I framework pays little or no attention to the creditworthiness of a borrower in deciding on the regulatory capital requirements. As a result, a lot of banks remove low-risk assets from their balance sheets and only retain relatively high risk assets on balance. The recently introduced Basel II framework should result in a further convergence between regulatory and economic capital. However, recent papers argue that also under Basel II, regulatory and economic capital will have different determinants. This paper first gives an overview of capital adequacy and then further describes the differences and similarities between economic and regulatory capital based on a literature review.

- by André Thibeault
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- Literature Review, Economic Capital, Financial Institutions, Bank Capital