An integrated framework for competency development: perspectives of risk managers in banks

Koh, Eric H. Y.; Avvari, Mohan V.; Tan, Kim Hua

doi:10.1007/s11628-015-0283-0

Cited by 5 publications

(6 citation statements)

References 32 publications

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“…The board size (BS) is the number of directors on the board. A larger board size may reduce a bank's risk-taking behavior because of better assets and diversified risks not just because of the higher number of directors involved but also because of their wider range of expertise (Blanchard and Dionne, 2004;Adams and Mehran, 2008) and multitude of views (Koh et al, 2015b). Hence, we expect larger board size to help lower the risk-taking behavior.…”

Section: Explanatory Variablesmentioning

confidence: 99%

The Chinese banks’ directors and their risk-taking behavior

Chan

Koh

Karim

2016

CMS

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Purpose The purpose of this paper is to examine the impact of the directors’ socioeconomic backgrounds on the risk-taking behavior of the listed commercial banks in China. Design/methodology/approach The generalized least square method and Arellano and Bover’s (1995) generalized method of moment were used to study the relationship between the directors’ socioeconomic backgrounds and bank risk-taking behavior. The sample studied consists of 16 listed commercial banks in China from 2003 to 2011. Findings It was found that smaller board sizes and higher percentage of independent directors contribute to lower risk-taking. The results also indicate that banks are better off with boards that have gender diversity, government affiliation and higher average age because they enhance problem-solving and market insights facilitate adherence to government or regulatory policies and help reduce the banks’ risks. Research limitations/implications Future studies may consider including non-public-listed banks, pre-2003 data and analyses of the agencies to which the government-affiliated directors are or were attached. Practical implications The paper suggests that corporate governance reform initiatives with closely monitored implementation and phased liberalization contributed toward the banking industry’s resilience. Implications for management include that boards of directors with better quality, sufficient independence, gender diversity, government affiliation and maturity will help reduce risks. Social implications This study may facilitate the decision-making for the bank management and policymakers on the selection of best directors in the Chinese banking sector. The Chinese banking system serves as a plausible role model for consideration, given that four of its banks have now leapfrogged to be among the top ten largest banking institutions after the global financial crisis. Originality/value The study covers a wide range of socioeconomic backgrounds of the board of directors which are crucial in influencing the behavior of the board in banking operations.

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Section: Explanatory Variablesmentioning

confidence: 99%

The Chinese banks’ directors and their risk-taking behavior

Chan

Koh

Karim

2016

CMS

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“…The culture should encourage the virtues of prudence, conservatism, crisis avoidance and long-term steady financial results rather than short-termism, greed and herding (copying the strategies of other financial institutions) (Ashby, 2011, 334-339). Koh et al (2015) suggest a more integrated approach to the development of risk management competency by integrating three inter-related concepts, namely, competencies, QRFM 15,3 dynamic competencies and the learning organisation. They identified operational risk indicators from Malaysian literature and re-affirmed these during interviews with ten leading chief risk officers of banks in Malaysia.…”

Section: Research About Risk Management Competenciesmentioning

confidence: 99%

“…“Organisations face a shortage of competent risk management professionals despite this function’s increasing importance” (Koh et al , 2015, 1).…”

Section: Introductionmentioning

confidence: 99%

An interactive qualitative analysis of academics’ views of a competency-based undergraduate qualification in risk management

Marx

Swardt

2023

QRFM

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Purpose The purpose of this research was first to determine the competencies mandatory of risk managers, and second, to consider the implications of such competencies in determining modules appropriate for inclusion in any prospective undergraduate qualification with specialisation in risk management. Design/methodology/approach A qualitative research approach was followed, involving academics teaching risk management in a focus group and making use of interactive qualitative analysis (IQA). Findings The competencies identified were business management skills, financial knowledge, an understanding of the risk management process, governance and compliance, people management and technical skills. These will be explained in greater detail in the paper. Research limitations/implications The implications for teaching are that an undergraduate curriculum in risk management will have to combine majors such as business management, financial management, risk management, industrial psychology and communication. These majors need to be complemented by modules in governance and compliance management, as well as information and communication technology. Practical implications The implication for practice is that risk management professionals and members of the Institute of Risk Management of South Africa need to avail themselves to serve on an advisory board of academic departments offering risk management qualifications. Risk management is a developing science and requires inputs about research and the curriculation of qualifications. Social implications The implication for public policy is that the South African Qualifications Authority and the Council for Higher Education should reconsider their requirements for designators (specialised qualifications). The implications for research are that IQA provides clarity on the knowledge and skills required to develop a competency-based qualification in risk management. Further research should benchmark qualifications and propose a curriculum for a bachelor’s degree in risk management. Originality/value The use of IQA is a novel way of ensuring rigour and objectivity in arriving at a description of the required knowledge, skills, values and attributes of risk managers. This paper will assist in the compilation of a new curriculum for an undergraduate qualification in risk management; thus, ensuring such qualification will provide a competency-based qualification that will meet the needs of the profession.

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“…Most data mining software includes online analytical processing, traditional statistical methods, such as cluster analysis, discriminant analysis, and regression analysis, and non-DOI: 10.31695/IJASRE.2022.8.10.2 traditional statistical analysis such as neural networks, decision trees, link analysis, and association analysis. This wide range of techniques is not surprising because data mining is derived from three different disciplines, database management, statistics, and computer science, including the use of artificial intelligence and machine learning [8].…”

Section: Data Mining and Knowledge Discovery (Kdd)mentioning

confidence: 99%

Development of a Model for the Prediction of Diabetes Using Data Mining Technology

U¹,

Ukamaka²,

Shehu³

2022

IJASRE

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One of the most powerful technologies which are of high interest in the computer world is data mining. However, it is a comparatively new field of research whose major objective is to acquire knowledge from huge amounts of data. The motive of this study is to design a model which can forecast the likelihood of diabetes in patients with maximum accuracy. Therefore two main machine learning classification algorithms namely Decision Tree and Naive Bayes are used in this experiment to detect diabetes at an early stage. Experiments are performed on Pima Indians Diabetes Database (PIDD) which is sourced from the UCI machine learning repository. The performances of the two algorithms are evaluated on various measures like Precision, Accuracy, F-Measure, and Recall. Accuracy is measured over correctly and incorrectly classified instances. The filtering is done by comparing the group value to the class value followed by applying the Naïve Bayes classification algorithm for predicting diabetes. Significant attribute selection was done via the principal component analysis method. Results obtained show Naive Bayes outperforms with the highest accuracy of 76.30% compared to the decision tree which has 73.82%.

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An integrated framework for competency development: perspectives of risk managers in banks

Cited by 5 publications

References 32 publications

The Chinese banks’ directors and their risk-taking behavior

The Chinese banks’ directors and their risk-taking behavior

An interactive qualitative analysis of academics’ views of a competency-based undergraduate qualification in risk management

Development of a Model for the Prediction of Diabetes Using Data Mining Technology

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