Board Independence, Risk Management and Financial Performance of Financial Institutions in Bangladesh

2018 ◽  
Author(s):  
Syed Abdulla Al Mamun, PhD, FCMA ◽  
Mohammad Azhar Hossain
2019 ◽  
Vol 19 (6) ◽  
pp. 1344-1361
Author(s):  
Isaiah Oino

Purpose The purpose of this paper is to examine the impact of transparency and disclosure on the financial performance of financial institutions. The emphasis is on assessing transparency and disclosure; auditing and compliance; risk management as indicators of corporate governance; and understanding how these parameters affect bank profitability, liquidity and the quality of loan portfolios. Design/methodology/approach A sample of 20 financial institutions was selected, with ten respondents from each, yielding a total sample size of 200. Principal component analysis (PCA), with inbuilt ability to check for composite reliability, was used to obtain composite indices for the corporate governance indicators as well as the indicators of financial performance, based on a set of questions framed for each institution. Findings The analysis demonstrates that greater disclosure and transparency, improved auditing and compliance and better risk management positively affect the financial performance of financial institutions. In terms of significance, the results show that as the level of disclosure and transparency in managerial affairs increases, the performance of financial institutions – as measured in terms of the quality of loan portfolios, liquidity and profitability – increases by 0.3046, with the effect being statistically significant at the 1 per cent level. Furthermore, as the level of auditing and the degree of compliance with banking regulations increases, the financial performance of banks improves by 0.3309. Research limitations/implications This paper did not consider time series because corporate governance does not change periodically. Practical implications This paper demonstrates the importance of disclosure and transparency in managerial affairs because the performance of financial institutions, as measured in terms of loan portfolios, liquidity and profitability, increases by 0.4 when transparency and disclosure improve, with this effect being statistically significant at the 1 per cent level. Originality/value The use of primary data in assessing the impact of corporate governance on financial performance, instead of secondary data, is the primary novelty of this study. Moreover, PCA is used to assess the weight of the various parameters.


2021 ◽  
Vol 14 (2) ◽  
pp. 79
Author(s):  
Gratiela Georgiana Noja ◽  
Eleftherios Thalassinos ◽  
Mirela Cristea ◽  
Irina Maria Grecu

This paper empirically evidences the role played by board characteristics (skills, diversity, structure, independence) in supporting risk management disclosure and shaping the financial performance of European companies operating in the financial services sector. We exploit data selected from Thomson Reuters Eikon database in 2020 for the last fiscal year 2019 (FY0) on a longitudinal sample of 144 companies with the head offices in Europe (25 countries). Following an original empirical approach based on two modern financial econometric techniques, namely structural equation modelling (SEM) and network analysis through Gaussian graphical models (GGMs), the research endeavor outlines the decisive importance of an optimal board size, enhanced management skills, upward gender diversity (encompassed by women participation on board management), and structure (mainly a two-tier type, one management board, and a distinctive supervisory board) as fundamentals of risk management strategies, leading to improved financial achievements and a higher profitability for the analyzed companies.


2007 ◽  
Vol 12 (4) ◽  
pp. 321-330 ◽  
Author(s):  
B. Di Renzo ◽  
M. Hillairet ◽  
M. Picard ◽  
A. Rifaut ◽  
C. Bernard ◽  
...  

2018 ◽  
Vol 2018 ◽  
pp. 1-9
Author(s):  
Jia Liu ◽  
Shiyong Li ◽  
Xiaoxia Zhu

In recent years, internet development provides new channels and opportunities for small- and middle-sized enterprises’ (SMEs) financing. Supply chain finance is a hot topic in theoretical and practical circles. Financial institutions transform materialized capital flows into online data under big data scenario, which provides networked, precise, and computerized financial services for SMEs in the supply chain. By drawing on the risk management theory in economics and the distributed hydrological model in hydrology, this paper presents a supply chain financial risk prediction method under big data. First, we build a “hydrological database” used for the risk analysis of supply chain financing under big data. Second, we construct the risk identification models of “water circle model,” “surface runoff model,” and “underground runoff model” and carry on the risk prediction from the overall level (water circle). Finally, we launch the supply chain financial risk analysis from breadth level (surface runoff) and depth level (underground runoff); moreover, we integrate the analysis results and make financial decisions. The results can enrich the research on risk management of supply chain finance and provide feasible and effective risk prediction methods and suggestions for financial institutions.


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