Risk Management In Financial Institutions Research Articles

Environmental Credit Risk Management in Banks and Financial Service Institutions

ABSTRACTHow do Canadian banks integrate environmental risks into corporate lending and where are they located compared with their global peers? In this paper we report a mixed method analysis of the integration of environmental risks into the credit management. The qualitative and quantitative analyses suggest that all analyzed Canadian commercial banks, credit unions and Export Development Canada manage environmental risks in credit management to avoid financial risks. Some of the institutions even connect environmental and sustainability issues with their general business strategies. Compared with other countries, Canadian banks are best in class, as all six Canadian commercial banks, comprising over 90 percent of Canadian assets, systematically examine environmental risks for credits, loans and mortgages. We conclude that Canadian banks are proactive regarding environmental examinations of loans and that there is a need for a more accountancy related reporting on environmental risk management in financial institutions. Further research is needed to be able to calculate costs and benefits of integrating environmental and sustainability issues into the credit risk management. Copyright © 2011 John Wiley & Sons, Ltd and ERP Environment.

IS/IT Risk Management in Banking Industry

The paper makes a survey of current trends in business risk management focusing on IS/IT risk management in financial institutions. Special attention is paid to frameworks and regulations available for both financial and non-financial risk management and their relation to IS/IT risk management. The relationship and common and different features between IS/IT risk management and operational risk management are discussed on the basis of a short introduction to the specifics of risk management in financial institutions. The advantages and challenges of those different frameworks are summarized together with the possibility to incorporate some IT/IS risk management tools and methods into operational risk management in practice. Basel II is the main framework covering the area of operational risk management, therefore the paper focuses on the assessment of the impact and integration of the Basel II framework with IS/IT risk management ones.

Underwriting and investment risks in the property-liability insurance industry: evidence prior to the 9–11 event

Underwriting and investment are two important and related business activities of insurance companies. However, studies on the interrelation between underwriting and investment risks of Property-Liability (P-L) insurance companies are sparse in the literature. Using a sample of US P-L insurers, this article conducts an empirical investigation of how these two risks are associated with each other in the 1994–2000 period (before the September 11th terrorist attack in 2001). Our results, robust to various estimations, suggest that there is no significant relationship between the underwriting and investment risks among our sample firms. Such results based on pre 9–11 event period provide some support for the conjecture of Achleitner et al. (Geneva Pap Risk Insur Issues Pract 27:275–282, 2002) that many insurance companies may have failed to take an integrated approach to risk management. This resulted in a heavy loss due to dual exposures in both underwriting and investment in the 9–11 event. In the aftermath of the recent global financial crisis, risk taking and risk management of financial institutions have received more attention and increasing scrutiny. We believe the current paper provides some useful insights in this vein.

Knowledge level modeling for systemic risk management in financial institutions

The current subprime mortgage crisis is a typical case for systemic risk in financial institutions. In order to further our understanding and communication about systemic risk management (SRM) in financial institutions, this paper proposes a knowledge level model (KLM) for systemic risk management in financial institutions. There are two parts considered in the proposed KLM: ontologies and problem solving method (PSM). Ontologies are adopted to represent a knowledge base of KLM, which integrates top level ontology and domain level ontologies. And then the problem solving method is given to show the reasoning process of this knowledge. The symbol level of KLM is also discussed which integrates OWL, SWRL and JESS. Further, the discussion about Lehman Brother’s Minibonds case in 2008 is provided to illustrate how proposed KLM is used in practice. With these, first, they will enhance the interchange of information and knowledge sharing for SRM within a financial institution. Second, they will assist knowledge base development for SRM design, for which a prototype of financial systemic risk management decision support system is given in this study. Third, they will support coordination among different institutions by using standardized vocabularies. And finally, from the design science perspective, the whole proposed framework could be meaningful to models in other domains.

The current demand for the insurability of liability for damage to the natural environment

Since 2004, the basic document which has governed liability for damage to the natural environment in the European Union is the Environmental Liability Directive No. 2004/35/EC, as amended by the subsequent regulation No. 2006/21/EC. The main purpose of the legislation was to ensure that the entity responsible for the damage pays all costs for rectifying its consequences. If it concerns damage to natural environment, the operator must undertake measures for rehabilitation, replacement and regeneration of the damaged natural resources. The primary replacement, which returns the damaged natural resources to their original state, may be differentiated from complementary replacement as compensation in the case in which the primary replacement has not provided an adequate reparation, and finally compensatory replacement – compensation for the temporary loss of natural conditions. This paper aims at an analysis of the possible means for eliminating risks due to the liability for environmental damage caused by the actions of an operator whose activities potentially threaten natural environment and may cause the biodiversity damage. Risks are assessed with regard to the risk insurability criteria for potential damage to the natural environment. The importance of risk management is stressed in the sophisticated form known as the Enterprise Risk Management. Risk management is becoming increasingly important as a part of the Solvency II concept, currently in preparation, whose first and second pillars accentuate risk management in financial institutions and the consistent quantification of the obvious, hidden and potential risks.

FINANCIAL REFORMS IN AN EMERGING ECONOMY: THE CASE OF MALAYSIA

This paper traces the financial reforms that were introduced to stabilise and strengthen the financial system in Malaysia after the 1997 East Asian Financial crisis. It begins with a discussion of the causes of the crisis and the subsequent institution of capital controls and a fixed exchange rate regime and the efforts to introduce reforms behind the shelter of controls. Reform measures to reduce the ratio of non‐performing loans, to improve the balance sheet of banks and corporations, and to protect depositors are then evaluated, together with attempts to merge banks and strengthen the prudential regulation, corporate governance, and the risk management of financial institutions. The discussion is in the context of two forward‐looking master plans to reform and strengthen Malaysia's financial sector and the capital market. The paper ends with a discussion of the positive effects of the reform on economic recovery after the crisis. However, it is noted that the financial system persists as a relationship‐based system rather than a market‐based system in view of the Government's insistence on directed lending and the continued implementation of the New Economic Policy.

Bankruptcy prediction modeling with hybrid case-based reasoning and genetic algorithms approach

One of the most important research issues in finance is building effective corporate bankruptcy prediction models because they are essential for the risk management of financial institutions. Researchers have applied various data-driven approaches to enhance prediction performance including statistical and artificial intelligence techniques, and many of them have been proved to be useful. Case-based reasoning (CBR) is one of the most popular data-driven approaches because it is easy to apply, has no possibility of overfitting, and provides good explanation for the output. However, it has a critical limitation—its prediction performance is generally low. In this study, we propose a novel approach to enhance the prediction performance of CBR for the prediction of corporate bankruptcies. Our suggestion is the simultaneous optimization of feature weighting and the instance selection for CBR by using genetic algorithms (GAs). Our model can improve the prediction performance by referencing more relevant cases and eliminating noises. We apply our model to a real-world case. Experimental results show that the prediction accuracy of conventional CBR may be improved significantly by using our model. Our study suggests ways for financial institutions to build a bankruptcy prediction model which produces accurate results as well as good explanations for these results.

Measuring the coupled risks: A copula-based CVaR model

Integrated risk management for financial institutions requires an approach for aggregating risk types (such as market and credit) whose distributional shapes vary considerably. The financial institutions often ignore risks’ coupling influence so as to underestimate the financial risks. We constructed a copula-based Conditional Value-at-Risk (CVaR) model for market and credit risks. This technique allows us to incorporate realistic marginal distributions that capture essential empirical features of these risks, such as skewness and fat-tails while allowing for a rich dependence structure. Finally, the numerical simulation method is used to implement the model. Our results indicate that the coupled risks for the listed company’s stock maybe are undervalued if credit risk is ignored, especially for the listed company with bad credit quality.

Modelo de classificação de risco de crédito de empresas

O processo de gerenciamento de risco de crédito em instituições financeiras vem passando por uma revisão ao longo dos últimos anos. Nesse contexto, diversas novas técnicas de mensuração de risco de crédito e tomadores têm sido desenvolvidas e implementadas por grandes Bancos. O objetivo desta pesquisa é desenvolver um modelo de classificação de risco para avaliar o risco de crédito de empresas no mercado brasileiro. O modelo foi construído com base em uma amostra de empresas de capital aberto classificadas como solventes ou insolventes no período entre 1994 e 2004. A técnica estatística utilizada no desenvolvimento do modelo foi a regressão logística. As variáveis independentes são índices financeiros calculados a partir das demonstrações contábeis e utilizados para representar a situação econômico-financeira das empresas. A validação do modelo foi efetuada utilizando o método Jackknife e uma Curva ROC. Os resultados do estudo indicam que o modelo de classificação de risco desenvolvido prevê eventos de default com um ano de antecedência com bom nível de acurácia. Os resultados, também, indicam que as demonstrações contábeis contêm informações que possibilitam a classificação das empresas como prováveis solventes ou prováveis insolventes.

Operational risk management in financial institutions: Process assessment in concordance with Basel II

AbstractThe improvement of banks' operational risk management frameworks concerns new requirements addressed in the Basel II Framework, a new capital adequacy regulation proposed by the Basel Committee on Banking Supervision (BCBS). Basel II will apply to internationally active banks and to all banks and investment firms in the EU via transposition of a new Directive into national regulations.By doing so, the national financial supervisory authority, Commission de Surveillance du Secteur Financier (CSSF) in Luxembourg, and a public research centre, Centre de Recherche Public Henri Tudor (CRPHT), have engaged in a joint research project that investigates solutions conformant to ISO/IEC 15504 for assessing operational risk management frameworks implemented in banks.The ISO/IEC 15504 requirements can meet the CSSF's expectation on consistent, transparent and sound risk assessments, as well as the expectation on promoting enhancements in institutions' risk management practices without dictating the form or operational detail of their policies and practices.Moreover, although the domain is largely outside the scope of software and systems engineering, the ISO/IEC 15504 process assessment standard provides for an adequate solution to the so‐called supervisory review process. This adequacy is validated through the structure of Basel II and financial domain requirements. Last but not least, we will show that ISO/IEC 15504 provides an adequate approach to assessing institutions in two sub‐domains, namely, the domain of credit operational risk management and the domain of IT risk management (including IT security risks management). Copyright © 2007 John Wiley & Sons, Ltd.

Is There a Link Between Foreign Exchange Market Stability and Stock Market Correlations? Evidence from Canada

The link between foreign exchange and stock markets has numerous practical business implications. If international diversification strategies are to be successful, these markets should display low levels of correlation. In addition, understanding the determinants of asset volatilities, as well as their international correlations, are important parameters for the day to day risk management of financial institutions, the risk management of firms operating internationally, and the pricing of contingent claims. This paper examines whether there is a link between exchange rate stability and stock market volatility and correlations. I find that the connection between exchange rates and stock market correlations and volatilities extends beyond periods of extreme crisis.

Structure, performance, and risk management of financial institutions

The performance, management, and risk exposure of financial institutions operating in rural and agricultural markets determine the cost of agriculture’s ongoing access to financial capital. The evolution of general banking and agricultural finance research contributions in the structure, performance, and risk management of financial institutions lending to agriculture and providing financing to rural markets is described and discussed in this paper. A summary of future research priorities in each of these areas is also provided. Ongoing regulatory change, institution consolidation, financial innovations, and the changes occurring in the agricultural sector drive research opportunities in this area. Ongoing research will be critical to maintain efficient rural financial markets that can provide consistent and competitively priced credit for rural America.

A general approach to integrated risk management with skewed, fat-tailed risks

Integrated risk management for financial institutions requires an approach for aggregating risk types (market, credit, and operational) whose distributional shapes vary considerably. We construct the joint risk distribution for a typical large, internationally active bank using the method of copulas. This technique allows us to incorporate realistic marginal distributions that capture essential empirical features of these risks such as skewness and fat-tails while allowing for a rich dependence structure. We explore the impact of business mix and inter-risk correlations on total risk. We then compare the copula-based method with several conventional approaches to computing risk.

Exposure-Based Cash-Flow-at-Risk: An Alternative to VaR for Industrial Companies

Cash-Flow-at-Risk (CFaR) is the cash flow equivalent of Value-at-Risk (VaR), a measure widely used as the basis for risk management in financial institutions. Whereas VaR-based systems specify the maximum amount of total value a firm is expected to lose under most foreseeable conditions (for example, with a 99% confidence level), CFaR-based systems determine the maximum shortfall of cash the firm is willing to tolerate. CFaR is gaining in popularity among industrial companies for much the same reasons VaR has succeeded with financial firms: it sums up all the company's risk exposures in a single number that can be used to guide corporate risk management decisions. The authors describe a six-step process for calculating a measure they call “exposure-based CFaR” and then demonstrate its application to Norsk Hydro, the Norwegian industrial conglomerate. Exposure-based CFaR involves the estimation of a set of exposure coefficients that provide information about how various macroeconomic and market variables are expected to affect the company's cash flow, while also accounting for interdependencies among such effects. The resulting model enables management to estimate the variability in corporate cash flow as a function of various risks, and to predict how a hedging contract or a change in financial structure will alter the company's risk profile.

Practical Volatility and Correlation Modeling for Financial Market Risk Management

What do academics have to offer market risk management practitioners in financial institutions? Current industry practice largely follows one of two extremely restrictive approaches: historical simulation or RiskMetrics. In contrast, we favor flexible methods based on recent developments in financial econometrics, which are likely to produce more accurate assessments of market risk. Clearly, the demands of real-world risk management in financial institutions - in particular, real-time risk tracking in very high-dimensional situations - impose strict limits on model complexity. Hence we stress parsimonious models that are easily estimated, and we discuss a variety of practical approaches for high-dimensional covariance matrix modeling, along with what we see as some of the pitfalls and problems in current practice. In so doing we hope to encourage further dialog between the academic and practitioner communities, hopefully stimulating the development of improved market risk management technologies that draw on the best of both worlds.

Operational risk management for financial institutions

I have been a regulator now for nine years. But for many years before that, in an explicitly non‐regulatory career at the Bank of England, I was very conscious of the efforts being made ‐ especially between the Bank and the Federal Reserve ‐ to get a dialogue under way in what bankers now know as the Basel Committee. Founders of that Committee, such as George Blunden, no doubt watched in a mixture of awe and horror at the subsequent growth of the animal they helped to create. When Basel 1 was being formulated in the mid‐1980s, there was, of course, a widespread recognition that there were many different reasons why a bank could fail. But there was a general and accurate perception that credit risk was the primary threat. An ‘adequate’ amount of capital and the division of assets into a relatively modest number of credit risk buckets were seen as a truly significant step forward. And as to what was ‘adequate’ capital, I am told that 8 per cent was arrived at as the highest number they dared to think they could get agreement on. It did not fall out (nor could it have fallen out) of any complicated mathematical formula or extensive historical research.

Effective risk management in financial institutions: the turnbull approach

Risk management is more important in the financial sector than in other parts of the economy. But it is difficult. The basis of banking and similar financial institutions is taking risk in conditions of uncertainty. Describes how the Turnbull report, for which the author was project director, created a new underlying approach to risk. Provides a guide to the way in which the various Turnbull ideas have become the bedrock of risk management and suggests how they can be developed.

Risk Management for Financial Institutions and Applicability of Extreme Value Theory

Risk Management for Financial Institutions and Applicability of Extreme Value Theory

Genetic algorithms applications in the analysis of insolvency risk

This study analyses the comparison between a traditional statistical methodology for bankruptcy classification and prediction, i.e. linear discriminant analysis (LDA), and an artificial intelligence algorithm known as Genetic Algorithm (GA). The study was carried out at Centrale dei Bilanci, in Turin, Italy, analysing 1920 unsound and 1920 sound industrial Italian companies from 1982–1995. This paper follows our earlier examination of neural networks (NN) (see Altman et al., 1994. Corporate distress diagnosis: Comparisons using discriminant analysis and neural network. Journal of Banking and Finance XVIII, 505–529). The experiments on GA were oriented along two different lines: the genetic generation of linear functions and the genetic generation of scores based on rules. The two types of experiments showed GA to be a very effective instrument for insolvency diagnosis, even if the results obtained with LDA analysis perhaps proved to be superior to those obtained from GA. Of particular interest, it should be noted that the results of GA were obtained in less time and with more limited contributions from the financial analyst than the LDA. Of additional interest is the relevance for credit risk management of financial institutions.

Risk Management in Financial Institutions

Risk Management in Financial Institutions