Hussein A. Abdou

Genetic programming for credit scoring: The case of Egyptian public sector banks

Credit scoring has been widely investigated in the area of finance, in general, and banking sectors, in particular. Recently, genetic programming (GP) has attracted attention in both academic and empirical fields, especially for credit problems. The primary aim of this paper is to investigate the ability of GP, which was proposed as an extension of genetic algorithms and was inspired by the Darwinian evolution theory, in the analysis of credit scoring models in Egyptian public sector banks. The secondary aim is to compare GP with probit analysis (PA), a successful alternative to logistic regression, and weight of evidence (WOE) measure, the later a neglected technique in published research. Two evaluation criteria are used in this paper, namely, average correct classification (ACC) rate criterion and estimated misclassification cost (EMC) criterion with different misclassification cost (MC) ratios, in order to evaluate the capabilities of the credit scoring models. Results so far revealed that GP has the highest ACC rate and the lowest EMC. However, surprisingly, there is a clear rule for the WOE measure under EMC with higher MC ratios. In addition, an analysis of the dataset using Kohonen maps is undertaken to provide additional visual insights into cluster groupings.

An evaluation of alternative scoring models in private banking

Purpose - This paper aims to investigate the efficiency and effectiveness of alternative credit-scoring models for consumer loans in the banking sector. In particular, the focus is upon the financial risks associated with both the efficiency of alternative models in terms of correct classification rates, and their effectiveness in terms of misclassification costs (MCs). Design/methodology/approach - A data set of 630 loan applicants was provided by an Egyptian private bank. A two-thirds training sample was selected for building the proposed models, leaving a one-third testing sample to evaluate the predictive ability of the models. In this paper, an investigation is conducted into both neural nets (NNs), such as probabilistic and multi-layer feed-forward neural nets, and conventional techniques, such as the weight of evidence measure, discriminant analysis and logistic regression. Findings - The results revealed that a best net search, which selected a multi-layer feed-forward net with five nodes, generated both the most efficient classification rate and the most effective MC. In general, NNs gave better average correct classification rates and lower MCs than traditional techniques. Practical implications - By reducing the financial risks associated with loan defaults, banks can achieve a more effective management of such a crucial component of their operations, namely, the provision of consumer loans. Originality/value - The use of NNs and conventional techniques in evaluating consumer loans within the Egyptian private banking sector utilizes rigorous techniques in an environment which merits investigation.

Credit scoring and decision making in Egyptian public sector banks

Purpose - The main aims of this paper are: first, to investigate how decisions are currently made within the Egyptian public sector environment; and, second, to determine whether the decision making can be significantly improved through the use of credit scoring models. A subsidiary aim is to analyze the impact of different proportions of sub-samples of accepted credit applicants on both efficient decision making and the optimal choice of credit scoring techniques. Design/methodology/approach - Following an investigative phase to identify relevant variables in the sector, the research proceeds to an evaluative phase, in which an analysis is undertaken of real data sets (comprising 1,262 applicants), provided by the commercial public sector banks in Egypt. Two types of neural nets are used, and correspondingly two types of conventional techniques are applied. The use of two evaluative measures/criteria: average correct classification (ACC) rate and estimated misclassification cost (EMC) under different misclassification cost (MC) ratios are investigated. Findings - The currently used approach is based on personal judgement. Statistical scoring techniques are shown to provide more efficient classification results than the currently used judgemental techniques. Furthermore, neural net models give better ACC rates, but the optimal choice of techniques depends on the MC ratio. The probabilistic neural net (PNN) is preferred for a lower cost ratio, whilst the multiple discriminant analysis (MDA) is the preferred choice for a higher ratio. Thus, there is a role for MDA as well as neural nets. There is evidence of statistically significant differences between advanced scoring models and conventional models. Research limitations/implications - Future research could investigate the use of further evaluative measures, such as the area under the ROC curve and GINI coefficient techniques and more statistical techniques, such as genetic and fuzzy programming. The plan is to enlarge the data set. Practical implications - There is a huge financial benefit from applying these scoring models to Egyptian public sector banks, for at present only judgemental techniques are being applied in credit evaluation processes. Hence, these techniques can be introduced to support the bank credit decision makers. Originality/value - Thie paper reveals a set of key variables culturally relevant to the Egyptian environment, and provides an evaluation of personal loans in the Egyptian public sector banking environment, in which (to the best of the authors knowledge) no other authors have studied the use of sophisticated statistical credit scoring techniques.

Executive Pay and Performance: The Moderating Effect of CEO Power and Governance Structure

Abstract This paper examines the crucial question of whether chief executive officer (CEO) power and corporate governance (CG) structure can moderate the pay-for-performance sensitivity (PPS) using a large up-to-date South African data-set. Our findings are threefold. First, when direct links between executive pay and performance are examined, we find a positive, but relatively small PPS. Second, our results show that in a context of concentrated ownership and weak board structures; the second-tier agency conflict (director monitoring power and opportunism) is stronger than the first-tier agency problem (CEO power and self-interest). Third, additional analysis suggests that CEO power and CG structure have a moderating effect on the PPS. Specifically, we find that the PPS is higher in firms with more reputable, founding and shareholding CEOs, higher ownership by directors and institutions, and independent nomination and remuneration committees, but lower in firms with larger boards, more powerful and long-tenured CEOs. Overall, our evidence sheds new important theoretical and empirical insights on explaining the PPS with specific focus on the predictions of the optimal contracting and managerial power hypotheses. The findings are generally robust across a raft of econometric models that control for different types of endogeneities, pay, and performance proxies.

Determinants Of Capital Structure In The Uk Retail Industry: A Comparison Of Multiple Regression And Generalized Regression Neural Network

Firms need to rely on different financing sources, but the question is how capital structure is determined for a particular industry. Our aim is to undertake an investigation into the factors which determine capital structure in the UK retail industry. Our initial sample consists of 163 (final sample: 100) UK retail companies, using data from 2000 in order to analyse capital structure from 2002 to 2006. Nonlinear models tend to be unduly neglected in capital structure research, and so we apply generalized regression neural networks (GRNNs), which are compared with conventional multiple regressions. We utilize a hold-out sample for the multiple regressions to make them comparable with the GRNNs. Stability of the data is also confirmed. Our main findings are: net profitability and the depreciation-to-sales ratio are key determinants of capital structure based on GRNNs, while two more variables are added in the multiple regressions, namely size and quick ratio; there is strong support for the pecking-order theory; both root-mean-square errors and mean absolute errors are much lower for the GRNNs than those for the multiple regressions for overall, training and testing datasets. The potential benefit of this research to financial managers and investors in the UK retail sector is the identification of the overriding role of net profitability in reducing the financial risk from high levels of gearing. Copyright

Corporate Boards, Ownership Structures and Corporate Disclosures: Evidence from a Developing Country

Purpose The purpose of this paper is to investigate the effect of corporate board attributes, ownership structure and firm-level characteristics on both corporate mandatory and voluntary disclosure behaviour. Design/methodology/approach Multivariate regression techniques are used to estimate the effect of corporate board and ownership structures on mandatory and voluntary disclosures of a sample of Libyan listed and non-listed firms between 2006 and 2010. Findings First, the authors find that board size, board composition, the frequency of board meetings and the presence of an audit committee have an impact on the level of corporate disclosure. Second, results indicate that ownership structures have a non-linear effect on the level of corporate disclosure. Finally, the authors document that firm age, liquidity, listing status, industry type and auditor type are positively associated with the level of corporate disclosure. Research limitations/implications Future research could investigate disclosure practices using other channels of corporate disclosure media, such as corporate websites. Useful insights may be offered also by future studies by conducting in-depth interviews with corporate managers, directors and owners regarding these issues. Practical implications The evidence relating to the important role that corporate governance mechanisms play in shaping the expectations relating to the level of corporate voluntary and/or mandatory disclosures may be useful in informing investor decisions, as well as future policy and regulatory initiatives. Originality/value This paper contributes to the existing literature by examining the governance-disclosure nexus relating to both mandatory and voluntary disclosures in both listed and non-listed firms operating in a developing country setting.

Islamic Governance, National Governance, and Bank Risk Management and Disclosure in MENA Countries

We examine the relationships among religious governance, especially Islamic governance quality (IGQ), national governance quality (NGQ), and risk management and disclosure practices (RDPs), and consequently ascertain whether NGQ has a moderating influence on the IGQ–RDPs nexus. Using one of the largest data sets relating to Islamic banks from 10 Middle East and North Africa (MENA) countries from 2006 to 2013, our findings are threefold. First, we find that RDPs are higher in banks with higher IGQ. Second, we find that RDPs are higher in banks from countries with higher NGQ. Finally, we find that NGQ has a moderating effect on the IGQ–RDPs nexus. Our findings are robust to alternative RDP measures and estimation techniques. These results imply that the quality of disclosure depends on the nature of the macro-social-level factors, such as religion that have remained largely unexplored in business and society research, and, therefore, have important implications for policy makers.

Degree and Higher Level Apprenticeships: an empirical investigation of stakeholder perceptions of challenges and opportunities

ABSTRACT The aim of this paper is to explore the challenges and opportunities of designing and delivering Degree and Higher Level Apprenticeships (D&HLAs) at levels 4–7 from a multi-stakeholder perspective namely employers, Universities, independent training organisations and professional bodies. Twenty-seven face-to-face interviews were undertaken and thematic content analysis was used to analyse the data. The following three themes emerged from the data analysis: programme design; programme delivery; and graduate attributes. We conclude that whilst there are increasing numbers of trailblazer groups developing higher level standards, the uptake of apprenticeships at these levels remains relatively low. Although stakeholders support the principle of D&HLAs, we identify a number of challenges and opportunities facing those who seek to successful introduction of these programmes. Our policy recommendations include the need for all stakeholders to work collaboratively to co-create a flexible system to support the validity and relevance of D&HLAs. This will include streamlining and mapping the variety of qualifications currently available in order to promote a platform for parity of both esteem and opportunity for those achieving degree qualifications through the apprenticeship route.

Risk Management Practices in the Republic of Yemen: Are Islamic Banks Different?

The main aims of this paper are, firstly, to investigate the extent to which Yemen’s banks, in particular its Islamic banks, are applying Risk Management Practices (RMPs) and related techniques to deal with various types of risk, and secondly, to compare and distinguish between the RMPs used in Islamic, national and foreign banks. Semi-structured interviews were conducted to identify the current RMPs in Yemen. The main research instrument was a questionnaire, divided into two sections. The first section covered the following five aspects: understanding risk and risk management, risk identification and analysis, risk monitoring, RMPs, and credit risk analysis. The second section consisted of four aspects: methods of risk identification, risk management, credit risk management, and types of risk. Multinomial regressions and other statistical tools were applied to determine whether there are differences between Islamic banks and other banks in Yemen. Our results revealed that there are significant differences between Islamic and national banks in terms of their understanding of risk and risk management, risk identification and analysis and credit risk analysis. However, there are no major differences found between national and Islamic banks in terms of risk management and RMPs. For Islamic and foreign banks, however, there are significant differences in terms of understanding risk and risk management and risk identification and analysis, but no differences between their risk management, RMPs and credit risk analysis.

Perceived person-organization fit and turnover intention in medical centers: The mediating roles of person-group fit and person-job fit perceptions

Purpose The purpose of the paper is to fill gaps in the existing fit and turnover intention (TI) literature by investigating a more comprehensive model, in which TI is proposed to be influenced by the interplays of three multidimensional types of fit including, person-organization (P-O) fit, person-group (P-G) fit, and person-job (P-J) fit. Design/methodology/approach Participants were selected from different specializations within Mansoura University medical centers, where each medical center was represented proportionately within the sample. Data were collected using self-administered questionnaires. Questionnaires were provided to 850 employees who agreed to participate. Of the 850 questionnaires distributed, 385 were valid and complete (n=385). Partial least squares analysis was utilized for the analyses. Findings Results showed that P-O fit, P-G fit, and P-J fit were positively related to each other and negatively related to TI. Furthermore, the negative relationship between P-O fit and TI is partially mediated by P-G fit and P-J fit. Originality/value The present study simultaneously examines the multidimensional effects of different fit perceptions on TI. In doing so, we identify which of the fit perspectives influence TI more intensely. Moreover, the authors advance current insights by investigating the mediating roles of P-G fit and P-J fit in the relationship between P-O fit and TI.