i Gusau Journal of Accounting and Finance (GUJAF) Vol. 4 Issue 2, October, 2023 ISSN: 2756-665X A Publication of Department of Accounting and Finance, Faculty of Management and Social Sciences, Federal University Gusau, Zamfara State -Nigeria ii © Department of Accounting and Finance, 2023 Vol. 4 Issue 2 October, 2023 ISSN: 2756-665X A Publication of Department of Accounting and Finance, Faculty of Management and Social Sciences, Federal University Gusau, Zamfara State -Nigeria All Rights reserved Except for academic purposes no part or whole of this publication is allowed to be reproduced, stored in a retrieval system or transmitted in any form or by any means be it mechanical, electrical, photocopying, recording or otherwise, without prior permission of the Copyright owner. Published and printed by: Ahmadu Bello University Press Limited, Zaria Kaduna State, Nigeria. Tel: 08065949711, 069-879121 e-mail: abupress2013@gmail.com abupress2020@yahoo.com Website: www.abupress.com.ng mailto:abupress2013@gmail.com iii EDITORIAL BOARD Editor-in-Chief: Prof. Shehu Usman Hassan Department of Accounting, Federal University of Kashere, Gombe State. Associate Editor: Dr. Muhammad Mustapha Bagudo Department of Accounting, Ahmadu Bello University Zaria, Kaduna State. Managing Editor: Umar Farouk Abdulkarim Department of Accounting and Finance, Federal University Gusau, Zamfara State. Editorial Board Prof.Ahmad Modu Kumshe Department of Accounting, University of Maiduguri, Borno State. Prof Ugochukwu C. Nzewi Department of Accounting, Paul University Awka, Anambra State. Prof Kabir Tahir Hamid Department of Accounting, Bayero University, Kano, Kano State. Prof. Ekoja B. Ekoja Department of Accounting, University of Jos. Prof. Clifford Ofurum Department of Accounting, University of PortHarcourt, Rivers State. Prof. Ahmad Bello Dogarawa Department of Accounting, Ahmadu Bello University Zaria. Prof. Yusuf. B. Rahman Department of Accounting, Lagos State University, Lagos State. Prof. Suleiman A. S. Aruwa Department of Accounting, Nasarawa State University, Keffi, Nasarawa State. iv Prof. Muhammad Junaidu Kurawa Department of Accounting, Bayero University Kano, Kano State. Prof. Muhammad Habibu Sabari Department of Accounting, Ahmadu Bello University, Zaria. Prof. Okpanachi Joshua Department of Accounting and Management, Nigerian Defence Academy, Kaduna. Prof. Hassan Ibrahim Department of Accounting, IBB University, Lapai, Niger State. Prof. Ifeoma Mary Okwo Department of Accounting, Enugu State University of Science and Technology, Enugu State. Prof. Aminu Isah Department of Accounting, Bayero University, Kano, Kano State. Prof. Ahmadu Bello Department of Accounting, Ahmadu Bello University, Zaria. Prof. Musa Yelwa Abubakar Department of Accounting, Usmanu Danfodiyo University, Sokoto State. Prof. Salisu Abubakar Department of Accounting, Ahmadu Bello University Zaria, Kaduna State. Prof. Isaq Alhaji Samaila Department of Accounting, Bayero University, Kano State. Dr. Fatima Alfa Department of Accounting, University of Maiduguri, Borno State. Dr. Sunusi Sa'ad Ahmad Department of Accounting, Federal University Dutse, Jigawa State. Dr. Nasiru A. Ka’oje Department of Accounting, Usmanu Danfodiyo University Sokoto State. v Dr. Aminu Abdullahi Department of Accounting, Usmanu Danfodiyo University Sokoto, State. Dr. OnipeAdebenege Yahaya Department of Accounting, Nigerian Defence Academy, Kaduna State. Dr. Saidu Adamu Department of Accounting, Federal University of Kashere, Gombe State. Dr. Nasiru Yunusa Department of Accounting, Ahmadu Bello University Zaria. Dr. Aisha Nuhu Muhammad Department of Accounting, Ahmadu Bello University Zaria. Dr. Lawal Muhammad Department of Accounting, Ahmadu Bello University Zaria. Dr. Farouk Adeza School of Business and Entrepreneurship, American University of Nigeria, Yola. Dr. Bashir Umar Farouk Department of Economics, Federal University Gusau, Zamfara State. Dr Emmanuel Omokhuale Department of Mathematics, Federal University Gusau, Zamfara. State vi ADVISORY BOARD MEMBERS Prof. Kabiru Isah Dandago, Bayero University Kano, Kano State. Prof A M Bashir, Usmanu Danfodiyo University Sokoto, Sokoto State. Prof. Muhammad Tanko, Kaduna State University, Kaduna. Prof. Bayero A M Sabir, Usmanu Danfodiyo University Sokoto, Sokoto State. Prof. Aliyu Sulaiman Kantudu, Bayero University Kano, Kano State. Editorial Secretary Yazid Ibrahim Kabir Department of Accounting and Finance, Federal University Gusau, Zamfara State. vii CALL FOR PAPERS The editorial board of Gusau Journal of Accounting and Finance (GUJAF) is hereby inviting authors to submit their unpublished manuscript for publication. The journal is published in two issues of April and October annually. 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PAYMENT DETAILS Bank: FCMB Account Number: 7278465011 Account Name: Gusau Journal of Accounting and Finance FOR INQUIRY The Head, Department of Accounting and Finance, Federal University Gusau, Zamfara State. elfarouk105@gmail.com +2348069393824 FOR MORE INFORMATION, CONTACT The Editor-in-Chief on +2348067766435 The Associate Editor on +2348036057525 OR visit our website on www.gujaf.com.ng or journals.gujaf.com.ng http://www.gujaf.com.ng/ http://www.gujaf.com.ng/ ix CONTENTS Board Characteristics and Financial Performance: Evidence from Listed Deposit Money Banks in Nigeria 1 Abdullahi Bala Ado, Norfadzilah Nik Mohd Rashid, Sa’adatu B. Adam, Binta Abubakar Nuhu, Hassanat Salawu Salihu and Tariro Masunda Welfare, Inflation, and Pension Income Inequality Among the Bottom and Top Income Quintiles and Decile: An Implication of Kaduna State Pension Reform 18 Prof. Salamatu I. Isah, Ibrahim Kekere Sule (PhD) Political Connection, Audit Fees, Audit Quality, and Tax Avoidance 31 Novita Dwi Damayanti, M KhoiruRusydi, WuryanAndayani Firm Attributes and Shareholder’s Wealth of Listed Deposit Money Banks in Nigeria 47 A.A. Mustapha, Prof. M.S. Tijjani, S. Salami PhD Financial Determinants of Entrepreneurship in Nigeria 67 Precious Adukwu, Hyeladi Stanley Dibal Work Environment, Remuneration and Accounting Lecturers’ Performance in Polytechnics in North West, Nigeria 88 Dr. Aliyu Abdullahi Ahmed, Rabiatu Ahmed Relative Efficiency of the Capital Market Over the Money Market in a Growth-Financing Economy 110 Adedeji Daniel Gbadebo Board Education, Director's Age and Earnings Management of Listed Deposit Money Banks in Nigeria 131 Idris IbrahimPhD, Prof. Luka Mailafia, Salami Suleiman PhD Ownership Concentration’s Moderating Effect on Dividend Payout And Tobin’s Q in the Nigerian Consumer Goods Sector. 149 Ovbe Simon Akpadaka x Foreign Direct Investment, Renewable Energy and Economic Growth: An Empirical Analysis from South Africa. 167 Ahmed Oluwatobi Adekunle Impact of Digital Financial Services on Savings Development in Nigeria 182 Iro, Onyinyechi Adanna, Eke, Patrick Omoruyi, Yunisa, Simon Amodu, Shekoni, Nurudeen Adebayo Account Receivable Management and Financial Performance of Listed Consumer Goods Firms in Nigeria 209 Umar Suleiman Abubakar Dabai, Biyai Shepnaan, Hajara Abubakar Jimoh, Haruna Halimah Sani Sambo PhD Stable Dividend Policy and Value of Listed Healthcare Firms in Nigeria 227 Maimuna Adamu Salihu, Aminu Danladi Ahmad, Zaharaddeen Salisu Maigoshi, Naja'atu Bala Rabiu The Impact of Monetary Policy on Small and Medium Scale Enterprises (SMES) in the Period of Economic Crises. 240 Ahmed Oluwatobi Adekunle. CEO Age and Gender on Financial Distress Likelihood of Listed Deposit Money Banks in Nigeria: Moderated by Risk Committee Gender 254 Idris Mohammed, Joshua Okpanachi, OnipeAdabenege Yahaya, Suleiman Tauhid 254 CEO ATTRIBUTES AND FINANCIAL DISTRESS LIKELIHOOD OF LISTED DEPOSIT MONEY BANKS IN NIGERIA: MODERATED BY RISK COMMITTEE GENDER Idris Mohammed Department of Accounting Faculty of Management Sciences Nigerian Defence Academy Kaduna, Nigeria idrisu02@gmail.com; +234 8063234829 Joshua Okpanachi PhD Department of Accounting Faculty of Management Sciences Nigerian Defence Academy Kaduna, Nigeria Onipe Adabenege Yahaya PhD Department of Accounting Faculty of Management Sciences Nigerian Defence Academy Kaduna, Nigeria Suleiman Tauhid PhD Department of Accounting Faculty of Management Sciences Nigerian Defence Academy Kaduna, Nigeria Abstract Despite the series of reform policies initiated by financial authorities to create good atmosphere for effective and standard banking operation in Nigeria which could ensure their growth and survival, yet some of the bank suffered financial distress over the years due to some likelihood factors. Thus, this study examines the moderating role of risk committee gender on the effect of CEO age and gender on financial distress likelihood of listed deposit money banks in Nigeria for the period of fifteen years between 2007-2021. The population of this study consists of fourteen listed deposit money banks in Nigeria. Correlational research design was adopted to analyze the secondary data extracted from the annual audited financial statement of the banks, using logistic regression technique, based on Multi Discriminant Analysis approach of a modified Althman Z score model. The result depicted that CEO age, CEO gender and risk committee gender significantly influence financial distress likelihood negatively. Furthermore, risk committee gender significantly moderated the effect of CEO age and gender on financial distress likelihood. Thus, it is recommended that the board of the deposit money banks in Nigeria should initiate policy that will specifically; consider average aged bracket or young people in managing the affairs of their banks, which by implication will increase the survival tendency of the listed deposit money banks in Nigeria. On the hand, the mailto:idrisu02@gmail.com DOI: https://doi.org/10.57233/gujaf.v4i2.15 255 board of the listed deposit money banks should also, give priority to female in carrying out the affairs of the banks particularly at the top-ranking management positions considering their risk appetite on financial management. This will go a long way in reducing the rate or tendency for financial distress among the listed deposit money banks in Nigeria. Keywords: CEO age, gender, risk committee gender, financial distress likelihood 1. Introduction It is imperative to note that the survival and growth of an organization will certainly be considered as part of major concern of the organizations’ stakeholders. In that regard, the management deemed it necessary to protect their organization against financial distress through coherent and integrated management policy for effective decision making. Although, Enyew et al., (2019)viewed financial distress as a circumstance that an entity cannot settle its creditors’ debt obligations which in turn leading to bankruptcy or restructuring. Other scholars like Miglani and Ahmed (2020) posited and considered financial distress as financial turnaround while, examining the relationship between corporate governance and financial distress. Nevertheless, financial distress can be attributed to various issues associated to some micro and macro-economic factors in an ordinary business operation(Egbo, 2012). But, Rono(2018) simply attributed corporate financial distress to the corporate governance mechanism failure to achieve the targeted objective of the business long and short term objective on part of CEO. Accordingly, some scholars like, (Brigham & Gapenski, 1994; Outecheva, 2007; Kazemian et al., 2017; Khan et al., 2020; Sunday & Innocent, 2021) among others, attempted to predict the financial distress likelihood of some organizations from various sector of different environment using different models and approach. Similarly, the banking industry like any other industry experiences serious financial distress over few decades particularly in Nigeria. Hence, considering the significant role and contribution of banks to the nation ‘s economic growth and development, Nigerian government have deemed it necessary to safeguard the banking operation through the regulatory bodies of the banks such as Central Bank of Nigeria (CBN), Nigerian Deposit Insurance Corporation (NDIC), Security Exchange Commission (SEC) etc. It is pertinent that series of policy reformation were initiated as part of the government effort to restructure and also revitalize the general financial institutions in Nigeria. Therefore, one among the major contribution of the government was the recapitalization policy of banks in year 2004. The recapitalization policy has 256 attributed to consolidation or merger and acquisition exercise among banks from 68 to 25 where the surviving banks extended their branches in year 2005 from 2,900 to 5,500 in mid of year 2009 respectively. Recall that the recapitalization of the banks was made to address the persistence corporate financial distress around the banking industry which were seen to be emanated from numerous ranges of issues surrounding the banking operations in the country such as; poor corporate governance, poor asset quality, inaccurate reporting and none-compliance with regulatory requirements, falling ethics and de- marketing of other banks in the industry, gross insider abuses resulting in huge non- performing insider related credits, oligopolistic structure with 10 of the 89 banks controlling more than 50 per cent of the industry assets and liabilities, lack of capacity to support the real sector of the economy, and lack of competition by banks in savings mobilization to boost the level of deposits(Sunusi, 2010). Although, recapitalization policies of the banks cannot guarantee the survival of the banks particularly in situation where acquisition has taken place between banks (Hambrick, 2014). At the aftermath of economic meltdown CBN and NDIC in June 2009 initiated an exercise towards accessing the financial well-being of 24 banks. 9 nine out of the 25 banks could not meet up with the 10% minimum capital adequacy ratio, and 25% liquidity ratio beside the higher nonperforming which led to the dismissal of their CEOs of the banks (Vanguard, 2009).Therefore, in an effort to comply with the requirement of the financial policy and operational reforms, some of the banks resorted to merger and acquisition. For example, (Plantinum Habib bank Plc, Africa Bank and Spring Banks Plc) were merged to form Tier 2 capital and thereafter nationalized among others. It was also reported how Skye bank of Nigeria Plc was taken over by Polaris as initiated by the CBN, and subsequently, Diamond Bank of Nigeria Plc was merged with Access bank of Nigeria Plc(Punch, 2018&Guardian, 2018). Recently, Union banks was reported to be taken over by Titan trust (Premium Time, 2022). Nevertheless, over three decades some classical studies such as Beaver (1966),Altman (1983),Andrade (1998),Asquith(1994),Chen(1997),Opler and Pinkowitz (1999) among others, came up with some relevant models for organizations financial distress predictions. Likewise, this study adapts the logistic regression technique in determining the measurement of the financial distress, which will be used as dependent variable in the second model of the study. Although, few studies have been conducted in an effort to examine the relation 257 between CEOs attributes and financial distress likelihood from different context such as, (Muien, et al., 2022; Chowdhury& Doukas, 2022; Lawrence, et al., 2021; Yao, 2020; Kolias, et al., 2019; Rono,2018; Zahra, et al., 2018; Gottardo & Moisello, 2017; Boyallian & Ruiz-Verdu, 2017; Bhaiyat& Garrow, 2015). However, the studies came up with divergence views from their findings. Moreover, corporate financial distress has remained an unresolved issue in the banking sector particularly amongst the developing countries of the world today, considering the few numbers of studies that were conducted in relation to CEO ‘s attributes and financial distress. Thus, to the best of the researcher ‘s knowledge no study has moderated the relationship between CEOs attributes and financial distress likelihood using risk management committee on basis of gender diversity focusing on listed DMBs in Nigeria covering the periods of fifteen years. In that regard, this study seeks to examine the moderating effect of risk management committee gender on the effect of CEOs attributes (CEO age and gender) on financial distress likelihood of listed DMBs in Nigeria between, 2007 to 2021. Where the independent variable will be represented by CEOs attributes and proxied by (CEO age and gender) and dependent variable of the study will be represented by financial distress and measured by modified Altman‘s Z score by (Ohlson, 1980), Also, study will use firms size and firms age as control variable of the study. The first model of the study is analyzed to predict the financial distress of the listed DMBs in Nigeria. And to further use the result as the measurement of the dependent variable of the second model. This contribution is informed by the inconsistences in the literature on the relationship between the CEOs attributes and financial distress likelihood. Also, this study employed Organizational Life Cycle Theory which to the best of the researcher ‘s knowledge it has not been used in any of the related subject matter. Hence, this will also serve as a contribution to knowledge. Ultimately, the inclusion of the moderator (RMCG) will enable the researcher fill the existing gap as explained, where the changes in the straight and direction of the relation between the independent variable (CEOs attributes) and dependent variable (financial distress likelihood) will contribute to the existing knowledge and literature of accounting and finance. Therefore, it is against this backdrop the following questions shall be raised and answered: i. How does CEO age influence the financial distress likelihood of listed DMBs in Nigeria? 258 ii. Does CEO gender influence the financial distress likelihood of listed DMBs in Nigeria? iii. How does risk committee gender affect financial distress likelihood of listed DMBs in Nigeria? iv. How dose risk committee gender moderates the effect of CEO age on financial distress likelihood of listed DMBs in Nigeria? v. Does risk committee gender moderate the effect of CEO gender on financial distress likelihood of listed DMBs in Nigeria? Meanwhile, the main objective of this study is to examine the moderating role of risk committee gender on the effect of CEO attributes (CEO age and gender) on financial distress likelihood of listed DMBs in Nigeria. Considering the objective of the study the following hypothesis are formulated in null form: H01: CEOs age has no significant effect on financial distress likelihood of listed DMBs in Nigeria H02: CEOs gender has no significant effect on financial distress likelihood of listed DMBs in Nigeria H03: Risk committee gender has no significant effect on moderating CEOs age on financial distress likelihood of listed DMBs in Nigeria H04: Risk committee gender has no significant effect on moderating CEOs gender on financial distress likelihood of listed DMBs in Nigeria. H05: Risk committee gender has no significant effect on financial distress likelihood of listed DMBs in Nigeria The outcome of this study could pave way for further related studies. Similarly, the outcome may serve as guide to the managers of the listed DMBs in Nigeria particularly in decision making. Accordingly, the result of the study could be use full to all relevant financial regulators in Nigeria like CBN, SEC, NDIC among others. Likewise, other financial stakeholders may utilize the outcome for effective policy. Conclusively, the paper is divided into five parts namely: introduction, literature review, methodology, result discussion, discussion of findings as well the policy implications. 2. Literature Review The section focused on reviewing literature and concepts on CEO Age, CEO Gender and Financial Distress Likelihood. 2.1 CEO Age and Financial Distress 259 It is imperative to note that scholars have attempted to examine the effect of CEOs on financial distress likelihood of different context with different outcomes. Hence, certain group of scholars discovered that CEO age has a positive and significant effect on financial distress likelihood. For instance a study was conducted in Kenya by Rono (2018) on a topic titled CEO attributes and financial distress during 2016, using secondary data based Altman Z score model approach of prediction, as CEOs age was considered as independent variable and financial distress was considered as dependent variable, found CEOs age to be positive and significantly influencing financial distress. On the other hand, both studies could not cover wide periods as shown from the studies. Hence, there is need to conduct a similar study with more wider periods on same subject matter in order to come up with a different outcome. Similarly, Naafs (2019)discovered that there is a positive and significant link between the CEOs age and financial crisis among 1500 non-financial firms during the 2004 – 2009, based on regression analysis, where the explanatory and explained variable of the study were represented by CEOs age and financial crisis respectively. Considering the differences in the outcome of both studies there is needs to initiate a moderating variable to address the divergence views from the outcome of both studies. More so, Li et al. (2020) discovered that CEOs positively and significantly influence the financial distress risk tendency while predicting risk tendency of financial distress based on corporate governance measures for the period of 17 years around China and Asia, where dynamic discrete-time survival analysis was employed model. Also, Muien et al. (2022) found that there is a positive and significant relationship between CEOs age and financial distress in their study conducted on CEOs reputation in relation to firm‘s financial distress in Pakistan for the period of 2006 to 2017, with the aim of investigating the relation between CEOs reputation and financial distress based on Upper echelon theory. But, other scholars discovered that CEO age has a negative effect on financial distress likelihood from different sector and environment. Dewandono (2018) discovered that CEOs age have negative relationship significantly with the firms ‘default risk in there studied on impact of top managers attributes in an effort to examined the management ‘s characteristics in relation to default risk of SMEs around UK from 2013 to 2016, using the 3,692 firms as population. The research considered CEOs age and default risk as independent and dependent variable respectively, where the study employed multivariate regression analysis on Altman Z Score model in measuring the default risk control prediction. Accordingly, Rehmana et al. (2021) in their study in Pakistan during 2010-2019, discovered a 260 negative a significant effect between CEOs age and financial crisis, as CEOs age represented the explanatory variable while the financial crisis represented dependent variable in the research. But if a similar study would be conducted with different models for predicting the financial distress the outcome would have been different. On the other hand, a regional study was conducted by Gerasimova (2021) on CEOs characteristics and bank risk-taking of listed commercial banks in North America, Europe and Asia- Pacific region in relation to CEOs characteristics and bank risk- taking of listed commercial banks between (2014-2018). The study discovered that CEOs age has no significant impact on the financial risk of the organization, using multiple regression technique based on ordinary least OLS to analyses the secondary data obtained from financial statement of the banks. Therefore, the mixed or divergence views among from the findings of the studies this study necessitate the need to the employing moderating variable in the study. In view of that there is need to conduct a similar study with a moderating variable which will be represented by RMCG on the relationship between CEOs attributes and financial distress among listed DMBs in Nigeria. Conclusively, the reviewed literatures cover the period of 2014-2022. Finally, none of the study used organizational life cycle theory as an underpinning theory 2.2 CEOs Gender and Financial Distress Considering the role of gender in the administration of finance in an ordinary business operation studies were conducted to examine the effect of gender on financial distress likelihood in various part of the world an came up with different views. Rono (2018) revealed that there is a positive but insignificant relationship between CEO gender and financial distress, upon investigating the relationship between CEOs attributes and financial distress in commercial banks during the period of 2016 in Kenya. Similarly in a work done by Dewandono (2018)CEOs gender was discovered to have contributed negatively on financial distress following the outcome of findings where multivariate regression analysis was employed based on Altman Z Score approach in analyzing the secondary data obtained from the sample of 3,692 SMEs in UK. On the other hand, another study conducted in Nigeria by Lawrence et al (2021) concluded that CEOs gender has a negative effect on financial distress likelihood of 59 listed manufacturing firms. CEOs gender is considered as one of the proxies of CEOs attributes as independent variable and financial distress likelihood 261 represented dependent variable. And logistic regression technique was suitable used to enable the researcher analyzed the secondary panel data. Thus, there is a need to conduct a similar study particularly in baking industry using a moderating variable under a different range of time. However, in another study conducted by Gerasimova (2021) on the relationship between CEOs characteristics and bank risk-taking of listed commercial banks amongst 28 different counties of the world between 2014 to 2018. Secondary data is obtained from the annual financial statement of 121 sampled commercial banks across different regions namely: North America, Europe and Asia- Pacific region respectively. The analysis was done based on the Ordinary Least Square OLS panel multiple regression techniques of analysis. It was revealed that CEOs gender has no significant connection with the banks financial risk-taking. Sequel to the mixed results from the reviewed literature as far as the relationship between CEOs age and financial distress is concerned; there is need to moderate risk committee gender on the effect of CEO gender on financial distress likelihood of listed DMBs in Nigeria. 2.3 Risk Committee Gender and Financial Distress Numerous studies have confirmed the link between risk committee gender and financial distress likelihood conducted and discovered mixed results. Meanwhile, Yousaf et al. (2020) in their study titled can board diversity predict the risk of financial distress among listed Chinese companies between 2007-2016, with the aim of 42 investigating how different diversity attributes in relation to risk financial distress likelihood considering general board diversity dimension of age, gender expertise and experience as independent variable while, financial distress risk tendency as dependent variable. The study employed a machine learning models in determining the risk of financial distress among the sampled firms. The study considered logistic regression as techniques to analyze data extracted from annual financial statement of the listed sampled Chinese companies. It was discovered that board diversity attributes gender has a significant positive relationship in predicting the financial distress of firms. Nevertheless, if a similar study is conducted in Nigerian context under a different period with a different model or theory, the outcome of the study would have been different. But, in a study conducted EU by Farag and Mallin(2016) on Board Diversity and Financial Fragility: Evidence from European Banks for the periods covered 2004- 2012. 99 banks located across 17 countries of EU namely: Austria, Belgium, 262 Denmark, Finland, France, Germany, Greece, Cyprus, Italy, Ireland, Netherlands, Poland, Portugal, Spain, Sweden, Switzerland and UK. The study considering proportion of female directors in the board as independent variable where financial fragility as vulnerability to financial distress representing the dependent variable. It was discovered that the number of female representations have a negative and significant influence on financial crisis among the banks which implies that female representation absolutely reduce bank vulnerability to financial distress. Therefore, the gender diversity in the board was encouraged. Donker and Santen (2009) conducted study on board diversity in relation to financial distress in Netherlands during the period of 1993-2003, using logit analysis in predicting the financial distress in binary form. It was discovered. Where board gender was considered among the independent variable and financial distress is considered as dependent variable. The outcome of 43 the study revealed that there is no significant relationship between the board gender and the financial distress of the firms. Also, Jia (2019) examined the relationship between risk management committee (RMC) gender diversity and a firm‘s likelihood of financial distress of 300 non- listed Australian firms from 2007 to 2014. Panel multiple regression technique was employed to analyze the secondary data collected from the annual financial statement of the sampled firms. The risk committee gender represented the independent variable of the study and financial distress likelihood represented the dependent variable of the study. It was concluded that risk committee gender has a negative relationship with financial distress likelihood. Therefore, this study deemed it necessary to use risk management committee gender (RMCG) as moderating variable following the mixed findings in the existing studies, which will serve as an important literature gap as it is evident that n none of the reviewed literatures used a moderating variable. RMCG as moderating variable will essential be examined on the interaction between the independent and dependent variables of the study. The independent variable of the study will be represented by COEs attributes and financial distress represented by dependent variable. Consequently, the variables of the study have been anchored by organizational life cycle theory as is considered relevant to the subject matter of the study. 3. Methodology and Data 263 Correlational research design has been used in line with the objective of the study. The population and the study consist of fourteen (14) listed DMBs in Nigeria. And census sampling technique was suitable for the study. The review. Population and Sample Size of the Study S/ N Study Population (14) Sample Selected (14) Date of Listin g 1 Access Bank Nig Plc. Access Bank Nig Plc. 1998 2 Eco Bank of Nig Plc. Eco Bank of Nig Plc. 2006 3 First City Monument Bank Nigeria Plc First City Monument Bank Nigeria Plc 2004 4 Fidelity Bank Nig Plc. Fidelity Bank Nig Plc. 2005 5 First Bank Nig Plc. First Bank Nig Plc. 1971 6 Guarantee Trust Bank Plc. Guarantee Trust Bank Plc. 1996 7 Stanbic IBTC. Stanbic IBTC. 2012 8 Sterling Bank Nig Plc. Sterling Bank Nig Plc. 1993 9 Union Bank of Nig Plc. Union Bank of Nig Plc. 1971 10 Unity Bank of Nigeria Plc. Unity Bank of Nigeria Plc. 1971 11 United Bank for Africa Plc. United Bank for Africa Plc. 1970 12 Wema Bank Nig Plc. Wema Bank Nig Plc. 1990 13 Zenith Bank Nig Plc. Zenith Bank Nig Plc. 2004 14 Jaiz Bank Nig Plc. Jaiz Bank Nig Plc. 2012 Sources: Field Work (2022) Secondary data were extracted from annual audited financial statement of the listed DMBs sample of the study, through Nigerian group exchangefor the year (2012- 2021). The study employed logistic regression technique, based on Multi Discriminant Analysis MDA approach of a modified Althman Z score model to analyze the unbalanced panel with the aid of STATA version 13. 3.1 Model Specifications This study relied on two different models in explaining the data of this study. First, is the adapted modified Althman Z score (Ohlson, 1980a) using a binary logit 264 regression model based multi discriminant analysis MDA approach which encapsulate: This model can be showed as: Pi E(y = 1/X1i, X2i, X3i, X4i) = 1_____ 1 + e-zi Where Pi= Probability of distressed for firm iY = 1 distressed company E(Y) = cumulative probability function that take value between 0 and 1 e = exponent and Zi = β0 + β1 X1+ β2 X2+ β3 X3 + β4 X4 + μi …………………………………(i) Where: β0 = Constant β1-β2 = Coefficients of parameters X1 = Working capital/total assets; X2 = Retained earnings/total assets; X3 = Earnings before interest and taxes/total assets; X4 = Equity value/ total debt μ = error term = discriminant residuals = corporate failure CF Second, is multiple regression model that encapsulate the interaction of the moderating variable with independent with the contribution control variables of the study, having explained how FD will be measured, then the FD will now become the DV of the second model: FDit= β0 + β1CAGit + β2CGNit + β3RCGit + β4CAG*RCGit + β5CGN*RCGit + β6FZit + β7FAGit + µit ……..….…….……………………………………………………. (ii) Where: FD = Financial distress (Dependent variable) β0 = Constant β1 –β7 = Coefficient of the parameters CAG = CEO age (Independent variable) CGN = CEO gender (Independent variable) RCG = Risk committee gender (Moderating variable) CAG*RCG = CEO age as moderated by risk committee gender CGN*RCG = CEO gender as moderated by risk committee gender FSZ = Firm size (Control variable) 265 FAG = Firm age (Control variable) µ = error term i = firm t = time 4. Results and Discussion This focuses on descriptive statistics, correlation matrix result, and interpretation of the summarized regression results, policy implications and recommendations based on the findings. Descriptive Statistics This describes the character of the data obtained based on the variables of the study. Below is the outcome shown in the descriptive statistics table. Table 3: Descriptive Statistics of the variable Variable Min Max Mean Std. Dev. Obs FD -12.9219 5.1728 -0.0209 1.1403 205 CAG 35 60 51.561 4.7848 205 CGN 1 0 1.0878 0.2837 205 RCG 1 6 0.1798 0.1678 205 FAG 1 127 44.4634 31.1063 205 FSZ 0.0127 0.1357 0.0968 0.0218 205 Source: STATA Output (2023) Table 2 shows the descriptive statistic for variables of the study comprising of the (financial distress (FD), CEO age (CAG), CEO gender (CGN), risk committee gender (RCG), CEO age moderated by risk committee gender (RCG), CEO gender moderated by risk committee gender (CGR), firm age (FAG) and firm size (FSZ). It is clearly shown that the average value of the financial distress stood at -0.0209 with minimum value -12.9219 and maximum value of 5.1728, while the mean and standard deviation value stood at -0.0209 and 1.1403 respectively. Also, CAG maintained the mean value of 51.561, which further ranges between the minimum of 35 and 60. This is simply showing that out of the CEOs of all the banks there was no body below the age of 35 and also above the age of 60 during the period covered by the study. It is also shown that CGN have an average value of 1.0878 with the minimum value of 0 and maximum value of 1 where 1 always represent male gender and 0 represent female gender. 266 Correlation Matrix This focuses on correlation between dependent variable financial distress (FD) and other variables that comprise of the proxies of the independent variables; CEO age (CAG) and CEO gender (CGN) as well as control variables firms’ age (FAG) and firms’ size (FSZ). Table. 4 Correlation Matrix Table. 2 Variables Definition and Measurement Variables Definitions Measurement Sources Dependent Variable Financial Distress (FD) The inability of a firm to finance its debt obligation as at when due Probability function of 1 and 0 drawn from Working capital ratio, Retained earnings ratio, Earnings b/4 interest & tax ratio and equity to debt ratio based on Logistic Regression Technique Ohlson (1980a) Independent Variables CEOs Age (CAG) The age of the CEO differences between the CEOs Date of birth & year of the study Alqatamin, Aribi and Thankom (2017) CEOs Gender (CGN) The category of the CEOs’ sex Value of 1 if CEO is male and 0 if female Gorts, 2016 andAlqataminetal (2017) Moderating Variable Risk Management Committee Gender (RMCG) Female concentration in the Board Risk Committee Number of female directors on the RMC divided by the RMC's Size Jia (2019b) Control Variable Firm Size (FSZ) The measure of firm capacity based on its total assets Natural Logarithm of Total Assets Opoku, Adu and Anarfi (2013) Rajha and Alslehat (2014) 267 Variables 1 2 3 4 5 6 FD 1 CAG -0.1359 0.0519* 1 CGN 0.1986 -0.0502 0.0043* 0.4747 1 RCG 0.0485 0.1629* -0.1143 0.4894 0.0196 0.1028 1 FAG -0.0822 0.1698* 0.0602 0.1531* 0.2413 0.0149 0.3914 0.0284 1 FSZ -0.0621 0.0957 0.1409* 0.1195* 0.0917 0.3768 0.1723 0.0438 0.0879 0.1666 1 Source: STATA Output (2023) Table 3 revealed that the correlations between FD with CGN and RCG were positively weak at coefficient value of 0.1986 and 0.0487 respectively. Except that the correlation between FD and CGN is significant at 1%. On the other hand, FD maintained negative weak correlations with CAG, FAG and FSZ with coefficient value of -0.1359, -0.0822 and 0.0621 respectively, except that the FD correlation with CAG is significant at 5%. Accordingly, the correlations among the independent variables themselves were relatively weak. This implies that there is no sign of multicollinearity effect among the independent variables of the study. Table. 5 Summary of Regression Result Variables Coefficient t- values P-Values VIF Tolerance Value CAG -0.0463 -2.22 0.028 1.06 0.9448 CGN -3.3851 -6.07 0.000 1.05 0.9553 RCG -18.5410 -3.24 0.001 1.07 0.9315 CAR 0.017 2.34 0.02 CGR -0.3793 -2.56 0.011 R2 0.20 Adj R2 0.17 F- Start 6.91 F- Sig 0.000 Firm Age (FAG) The measure of firm duration based on its date of incorporation Difference between the year of incorporation and present year of operation. Opoku, Adu and Anarfi (2013) Rajha and Alslehat (2014) Sources: Field Work (2023) 268 Hettest Chi 2 0.000 Hausman Chi 2 0.84 Breusch Pagan 1.00 Sources: STATA output (2023) The study has been subjected to post regression analysis to ensure the best fit model to be used in used to interpret the result of study on the basis of best linear unbiased estimators “BLUE” for valid inferences. In that regards, heteroskedasticity test conducted revealed Chi2 value of 0.000 that shows that evidence of an unequal spread of data in the model of the study and it was corrected using robust OLS to ensure “BLUE” as shown in the summary of the result of the study. This was determined through the Hausman specification test conducted that yield Chi 2 Value of 0.84, which suggested for Breusch and Pagan Lagrangian Multiplier Test (L.M-Test) for random effects. And the outcome revealed P- Value of 1.000, hence, OLS regression model was considered suitable for the study. But, following the outcome of the study the research resorted to robust the OLS. Furthermore, Variance Inflation Factor (VIF) and corresponding Tolerance Value have been displayed on the basis of rule of thumb of VIF and the Tolerance Value. Where the VIF consistently displaying smaller values less than ten (10) and the corresponding tolerance value consistently sowing smaller values less than one (1) which ultimately indicating the absence of multicollinearity effect within independent variables of the study. Also, cumulative R- Squared of (0.20) as the multiple coefficients of determination which indicate the percentage of total variation in the dependent variable as jointly explained by the all the independent variable, moderating variable and control variables used in the study. This means, that 20% of the variation in dependent variable is determined by the independent variable, moderating variable and control variables jointly. This outcome is validated by the outcome of the F- Stat and F- Sig of (6.91) and (0.000) respectively, which further signified the fitness of the model of the study by 1%. Hypothesis One (CEO Age and Financial Distress Likelihood) From Table 5 CEO age with negative coefficient value of -0.0463 yield a P- value of 0.028 which significant at 1%, implies that CEO age has a negative and significant influence on the financial distress likelihood of the listed DMBs in Nigeria. This shows that for every one unit increase of CEO age there will be less or reduction in the financial distress likelihood of the listed DMBs in Nigeria. This will serve as evidence for refusing to accept the null hypothesis which states that CEO age has no significant effect on financial distress likelihood, but to accept the alternate hypothesis. In the same vein, this study corresponded with the study of 269 Dewandono (2018) and Rehmana et al. (2021) and contradicts the study of Rono (2018), Naafs (2019) and Li et al. (2020). This further justified the underpinning theory of the study. Hypothesis Two (CEO Gender and Financial Distress Likelihood) CEO gender has shown a negative and significant relationship on financial distress likelihood with coefficient value of -3.3851and P- value of 0.000 respectively, which suggested a change in CEO gender has a significant effect on financial distress likelihood of the listed DMBs in Nigeria negatively, particularly if there is additional unit increase in the number of females as CEO there will be serious reduction in the financial distress likelihood of the listed DMBs in Nigeria by 338%. Therefore, the result suggests for not accepting the null hypothesis which states that CEO gender has no significant effect on financial distress likelihood of the listed DMBs in Nigeria. Meanwhile,this outcome is in lined with outcome of Rono (2018), Dewandono (2018) and Lawrence et al (2021). But, oppose the study of Gerasimova (2021), which further validated the underpinning theory of the study. Hypothesis Three (Risk committee Gender and Financial Distress Likelihood) The outcome in the Table 5 shows that Risk Committee Gender (RCG) has a negative and 1%significant P- value of 0.001 with coefficient value of -18.550. The result shows that any additional number of females will bring about remarkable reduction in the financial distress likelihood of the listed DMBs in Nigeria. This also means that RCG has a negative and significant effect on financial distress likelihood in Nigeria. Therefore, this provides reason for not accepting the null hypothesis which states that risk committee gender has no significant effect in moderating CEOs age on financial distress of listed DMBs in Nigeria. Therefore, this finding is in support of the view of Farag and Mallin(2016) and Jia (2019). Although, the outcome contradicted the view of Donker and Santen (2009) and Yousaf et al. (2020). This has also supported the underpinning theory of the study. Hypothesis Four (Risk committee Gender Moderating the effect of CEO Age and Financial Distress Likelihood) It is shown from Table 4 CEO Age has a positive and 1%significant P- value of 0.02 with coefficient value of 0.017 as moderated by risk committee gender. Meanwhile, it infers that any unit increase in CEO Age will lead to an increase in the financial distress of the listed DMBs in Nigeria by 2% as moderated by risk committee gender. This shows that the CEO age has a positive and significant effect on financial distress likelihood in Nigeria as moderated by risk committee gender 270 positively. Therefore, this provides reason for not accepting the null hypothesis which states that risk committee gender has no significant effect in moderating CEOs age on financial distress of listed DMBs in Nigeria. Hypothesis Five (Risk committee Gender Moderating the effect of CEO Gender and Financial Distress Likelihood) Table 4 revealed that CEO gender maintained a negative and 1% significant P- value of 0.011 with a corresponded coefficient value of 0.3793. It therefore, concludes that any change of CEO gender will lead to decrease in financial distress of listed DMBs in Nigeria as moderated by risk committee gender by 38%. Thus, the CEO gender has a negative and significant effect on financial distress likelihood in Nigeria as moderated by risk committee gender. Consequently, the study fails to accept the null hypothesis which states that risk committee gender has no significant effect in moderating CEOs gender on financial distress of listed DMBs in Nigeria. 5. Conclusion and Recommendations The study examined the moderating effect of risk management committee gender on the relationship between CEOs attributes and financial distress likelihood of listed DMBs in Nigeria. It was established that CEO Age (CAG), CEO Gender (CGN) and Risk Committee Gender (RCG) were significantly and negatively influencing financial distress of listed DMBs in Nigeria. On the other hand, upon testing the moderating role of risk committee gender (RCG) in effect of CAG on financial distress likelihood (FD) of listed DMBs in Nigeria as a moderator (CAR), it was found that CAG has a positive and significant effect on FD. Conversely, on testing the moderating role of risk committee gender (RCG) in effect of CEO gender (CGN) on financial distress likelihood (FD) as a moderator (CGR), it was shown that there is a negative and significant effect between CGN and DF of the listed DMBs in Nigeria. Therefore, following the outcome of this study, it is recommended that the board of the DMBs in Nigeria should initiate policy that will specifically; consider average aged bracket or young people in managing the affairs of their banks, which by implication will increase the survival tendency of the listed DMBs in Nigeria. On the hand, the board of the listed DMBs should also, give priority to female in carrying out the affairs of the banks particularly at the top- ranking management positions conspiring their risk apatite on financial management. This will go a long way in reducing the rate or tendency for financial distress among the listed DMBs in Nigeria. References Altman, E. I. (1983). Corporate financial distress. A complete guide to predicting, 271 avoiding, and dealing with bankruptcy. Wiley Inter Science, John Wiley and Sons. Andrade, G. and S. K. (1998). 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