Feature selection in credit risk modeling: an international evidence

This paper aims to discover a suitable combination of contemporary feature selection techniques and robust prediction classifiers. As such, to examine the impact of the feature selection method on classifier performance, we use two Chinese and three other real-world credit scoring datasets. The utilized feature selection methods are the least absolute shrinkage and selection operator (LASSO), multivariate adaptive regression splines (MARS). In contrast, the examined classifiers are the classification and regression trees (CART), logistic regression (LR), artificial neural network (ANN), and support vector machines (SVM). Empirical findings confirm that LASSO’s feature selection method, followed by robust classifier SVM, demonstrates remarkable improvement and outperforms other competitive classifiers. Moreover, ANN also offers improved accuracy with feature selection methods; LR only can improve classification efficiency through performing feature selection via LASSO. Nonetheless, CART does not provide any indication of improvement in any combination. The proposed credit scoring modeling strategy may use to develop policy, progressive ideas, operational guidelines for effective credit risk management of lending, and other financial institutions. The finding of this study has practical value, as to date, there is no consensus about the combination of feature selection method and prediction classifiers

Does Financial Flexibility foster Investment Efficiency? Evidence from an Emerging Market

This research aims to examine the relationship between financial flexibility and investment efficiency empirically, i.e., how financial flexibility effects suboptimal investments and efficiency. To attain the research objectives, we used panel data for 18 years (2000-2017) obtained from the CSMAR database; and also used the GMM estimation technique for research outcome. Our empirical results reveal that financial flexible firms can reduce the suboptimal investment by increasing investments compared to the inflexible firms and increases the investment efficiency. Also, financially flexible firms generate additional power to borrow external finance by showing a significant positive relationship with current and expected leverage. This research considers China as an emerging economy that is in the transition of being a developed country with a unique set of corporate governance, which ensures the independence of independent directors by providing authority to disclose important board decisions to the public. Besides, the governance system is highly monitored by the government, which in turn reduces and information asymmetry and enact to provide investment efficiency. Thus, the outcome of this research offers several conceptions for researchers and managers, which may be useful for both emerging and advanced countries. The results indicate that financial flexibilities lead to excess debt capacity, and this capacity can be used in the bad time when external financing is challenging to fund profitable projects, and also financial flexibility can be used to exploit lucrative projects and reduce the underinvestment or overinvestment entailing investment effectiveness. Previous research addresses the issue related to cost and benefit, information asymmetry, ownership concentration, and firms’ propensity to financial flexibility. A little research conducted on financial flexibility and investment efficiency in the developed market (in Europe and USA), and thus the issue of and financial flexibility measured in unused debt capacity and investment efficiency, is one of the fundamental research in the emerging economy

A descriptive study of Forcefully Displaced Myanmar Nationals (FDMN) presenting for care at public health sector hospitals in Bangladesh

Background In 2017 hundreds of thousands of ‘Rohingya’ fled to camps for Forcefully Displaced Myanmar Nationals (FDMN) in Cox’s Bazar, Bangladesh. Objective To describe the FDMNs presenting for care at public health facilities in Bangladesh so as to understand the health problems faced by the FDMNs and the burden on these public health facilities. Methods This study combined a retrospective review of existing hospital and clinic data with prospective surveillance in government health care centres. Findings The retrospective data showed a 26% increase in the number of consultations at the Kutupalong community clinic, the primary health facility closest to the camps, from 19,567 in 2015 to 26,309 in 2019. There was a corresponding 11% increase in admissions to health facilities in the area, from 80,991 in 2017 to 91,424 in 2019. Prospective surveillance of 9,421 FDMNs seeking health care from July 2018 to December 2019 showed that 29% had an infectious disease, 20% nutritional problems, 12% pregnancy-related conditions and 7% trauma or injury. Conclusions Great uncertainty remains regarding the return of FDMN to their home country of Myanmar. The current on-going protests following the military coup adds further insecurity to the status of the Rohingya. The presence of a large migrant population relative to a smaller host community burdens the limited facilities and resources of the public health sector. Continued support by the international public health community and civil society organizations is needed

Potential risks of liquidity and credit affecting the efficiency of Islamic banks in Bangladesh

AbstractRecently worldwide Islamic finance has gained considerable attention. However, Islamic financial institutions face multiple risks to sustaining and growing further. Against this backdrop, the paper examines the impact of both liquidity and credit risk on the efficiency of Islamic banks (IBs) operating in Bangladesh. This paper uses IB’s data from 2007 to 2018 and offers a two-stage assessment. In the first stage, it uses data envelopment analysis (DEA), and in the second stage regression models to assess the impact of both liquidity and credit risk on the efficiency of the IBs. Efficiency scores confirm that IBs are operating with an 86% efficiency level through a 68% share in the constant returns to scale (CRS). Our results also confirm that both liquidity risk (LR) and credit risk (CR) have a significant impact on the efficiency of the IBs in Bangladesh. A higher score for efficiency is shown by a higher liquidity risk, whereas mixed results are confirmed by credit risk indicators. Moreover, the Z-score (a bank stability measurement) and number of branches (a measurement of the bank’s network coverage), have a positive impact on efficiency. On the other side, the size of the bank and the financial crisis period show a negative relationship with the bank’s efficiency. The findings of our paper significantly contribute to the Islamic banking sector, especially for the policymakers and academic researchers