







































American Interdisciplinary Journal of Business and 

Economics 
ISSN: 2837-1909| Impact Factor : 8.87 

Volume. 12, Number 1; January-March, 2025; 

Published By: Scientific and Academic Development Institute (SADI) 

8933 Willis Ave Los Angeles, California 

https://sadijournals.org/index.php/AIJBE| editorial@sadijournals.org 

 

 

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CORPORATE GOVERNANCE AND BANKRUPTCY RISK: AN 

EMPIRICAL ANALYSIS OF NIGERIAN BANKS 

 
1Ezekwere Uzochukwu and 2Amahi Uchechukwu Fidelis 

Department of Accounting, Kingsley Ozumba Mbadiwe University, Ideato, Imo State 

Department of Accounting and Finance, University of Delta, Agbor, Delta State 

Email: uzochukwu.ezekwere@komu.edu.ng 

                                                            DOI: https://doi.org/10.5281/zenodo.14629040 

Abstract: This study determined the effect of corporate governance on bankruptcy risk in commercial banks in 

Nigeria, using audit committee independence, and remuneration committee. Ex Post Facto research design was 

adopted for the study. A sample of eight deposit money banks was used for the study. Data were obtained from 

the annual reports and audited accounts of the banks under assessment. Altman's original model for public 

companies was used to extract data and the formulated hypotheses were tested with regression analysis with aid 

of E-View 9.0.  The analysis and hypotheses tested shows that audit committee independence has no significant 

effect on bankruptcy risk commercial banks in Nigeria. However, the study revealed that remuneration 

committee has a positive significant effect on bankruptcy risk commercial banks in Nigeria. Based on the 

results, the study recommended among others that Since the board of director serves as internal control 

mechanism in the corporate governance, banks policy makers should provide adequate regulations on the 

specific number of boards to be working with, hence, audit committee independence is likely to reduce the 

probability of bankruptcy as they bring wider knowledge and better expertise to the bank. 

Keywords: Corporate governance, Audit committee independence, Remuneration committee and Bankruptcy 

risk 

 

Introduction 

sturdy corporate governance (SCG) practice ensures transparency and consistency in monetary statements. 

Companies can approach outside sources at low prices once they have the self-belief of investors (Tricker & 

Tricker, 2015). Additionally, the implementation of SCG exercise guarantees using the top-of-the-line 

enterprise approach to maximize company price and mitigate associated risks inside the destiny (Husson-

Traore, 2009; Manzaneque et al., 2016). The collapse of groups as a consequence of the financial crisis of 2008 

is proof of the ramifications of weak corporate governance (WCG) implementation (Kumar & Singh, 2013; 

Mehran et al., 2011; Strouhal et al., 2012). SCG policies shield corporations from the hazard of monetary 

misery or insolvency, which are amongst the biggest reasons of financial ruin. The position of SCG adoption in 

mitigating economic distress has been nicely diagnosed in advanced countries. Many researchers have 

performed empirical research at the impact of true company governance (CG) implementation on the 

mailto:uzochukwu.ezekwere@komu.edu.ng


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opportunity of monetary misery. This research has homogenously verified the unfavourable consequences of 

top CG practice on the chance of misery threat (Bravo-Urquiza & Moreno-Ureba, 2021; Miglani et al., 2015). 

even though developing international locations respect the significance of CG, the advantages of CG, which 

have functioned simplest with precise CG adoption, have no longer been a concern. Therefore, CG 

implementation in transitional economies is lacking (Nurunnabi, 2020). 

Furthermore, emerging countries are inherently affected by firms that practice family ownership, so they suffer 

from high levels of corruption and absenteeism among eminent directors. Consequently, adopting SCG policies 

in emerging countries is more of a hurdle than in developed countries because firms are hesitant to adopt SCG 

(McGee, 2009). The advantages of good CG adoption, such as low capital costs, effective management and risk 

mitigation, are hardly understood in emerging countries (Nurunnabi, 2020).  

Financial distress is a broad concept used to describe situations in which firms face financial difficulty. The 

most common terms used interchangeably for financial distress are ‘failure’, ‘default’, ‘insolvency’, and 

‘bankruptcy’ (Geng, Bose, and Chen, 2015). However, bankruptcy is the extreme and irredeemable outcome of 

financial distress and as such many financially distressed firms escape bankruptcy due to early reconstruction of 

operations. There are many definitions of financial distress because different countries have different 

accounting procedures and rules. It is generally believed that it is a situation where operating cash flow does not 

exceed negative net assets (Li et al., 2014). Geng et al. (2015) state that some of the methods that have been 

used for financial distress prediction include discriminant analysis, logit or probit regression model, linear 

conditional probability models, neural network, decision trees, case-based reasoning, genetic algorithm, rough 

sets, support vector machine, and others. However, the assumptions underlying the majority of these methods 

are far from real world situation. Extant research has focused on the discovery of better models for financial 

distress prediction (Ayoola & Obokoh, 2018). 

in the beyond, instability within the Nigerian monetary system and the banking quarter especially turned into 

blamed on institutional disasters. However, this trend has shifted to generalized failure that's presently sweeping 

the banking area. Ogunleye (2006) as mentioned in Olaniyi (2007) corroborating this fact categorized the 

reasons of financial institution failure into institutional, financial and political elements in addition to regulatory 

and supervisory inadequacies. a number of those generalized failure styles have institutional, economic, 

political and socio-cultural dimensions. Mainly, factors like mismanagement, useless equipment for debt 

healing, bad credit score policy and administration, greed, corruption and fraud are a number of the worst 

culprits (Ifeyinwa, 2012). 

The importance and relevance of the Banking industry to any economy is based on its main intermediary role 

expected to be professionally, morally, legally and statistically played as a central position in the financial 

system. Farinde (2013) documented that banks act as intermediaries for efficient transfer of resources from 

surplus to deficit units. For the banks to be able to perform efficiently and contribute meaningfully to the 

development of the economy, the industry must be safe, sound and stable. 

Nowadays, models that can predict the bankruptcy of a company are of interest to various economic entities, 

such as banks, credit agencies, governments, and financial analysts, not to mention customers and suppliers. 

Although bankruptcy detection models have been gradually developing since the 1960s (Altman, 1968), the vast 

majority of them are still based only on accounting and financial variables as explanatory factors. However, 

despite the increase in the amount of research on corporate governance variables, which covers multiple 

disciplines, scholarly literature on the topic is still limited and fragmented (Martín-de Castro et al., 2019), 



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especially with regards to the role and impact of corporate governance on companies’ turnarounds. Research 

tends to instead remain focused on the analysis of the impact of financial variables in predicting corporate 

defaults. 

Studies on the bankruptcy prediction were carried out both locally and internationally using Altman Z score 

model. In foreign countries; Begum, Sarker and Nahar (2023); Khiem (2022); Handriani et al. (2021) and 

Safrida et al. (2021) tested the effect of corporate governance on bankruptcy prediction risk. In Nigeria, Okoye 

and Okoye (2022); Ayoola and Obokoh (2018) investigated the effect of corporate governance on bankruptcy 

prediction in Nigerian banks.   

From the prior studies, majorities of the studies on corporate governance and bankruptcy risk were conducted in 

foreign countries, the only recent studies carried out in Nigeria was the research carried out by Okoye and 

Okoye (2022) which data ended in 2020, thereby created a geographical and periodic gap. In addition, none of 

these previous studies included remuneration committee and risk management committee in their corporate 

governance variable, thereby created variable gap. The study therefore fills these gaps via determined the effect 

of corporate governance on bankruptcy risk on Nigerian deposit money banks from 2012 to 2023.  

The main objective of this study is to ascertain the effect of corporate governance on bankruptcy risk in 

commercial banks in Nigeria. The specific objectives are to: 

1. Determine the effect of audit committee independence on bankruptcy risk deposit money banks in Nigeria. 

2. Ascertain the effect of remuneration committee on bankruptcy risk deposit money banks in Nigeria 

Literature Review 

Corporate Governance 

The set of guidelines and rewards referred to as "CG" are used to direct and regulate a business enterprise's 

management (Ehiedu, 2022; Adeusi, Akeke, Aribaba & Adebisi, 2017). Ehiedu and Ogbeta, (2014) opined that 

company governance is an institutional setup that restrains the excesses of commanding managers. Making sure 

that the enterprise is operated efficaciously and traders earn a fair go back is the middle reason of company 

governance (Kajola, 2018). If a business enterprise is administered with diligence, openness, accountability, and 

obligation with the aim of maximizing shareholders' wealth, that corporation is taken into consideration to have 

complied with the CG rule (Pandy, 2018). 

Corporate governance is concerned with how all parties (stakeholders) involved in the firm's success try to 

guarantee that managers and other insiders are always taking proper actions or implementing procedures that 

protect the stakeholders' interests. Corporate governance tools assure shareholders of adequate returns on 

investments.  Corporate governance was created to defend the interests of shareholders but has increasingly 

gained importance for other stakeholders and society (Mohammad, Aly, Dixon, & Startling, 2014).  

For corporate governance systems, another key aspect for a company is the presence of internal and external 

auditors. In this sense, literature has shown that the presence of internal and external audit systems can have a 

significant impact on changes to a company’s financial performance and on its probability of default (Guo et al., 

2016 and Cenciarelli et al., 2018, among others). Internal and external auditors can guarantee the quality of the 

information of the financial reports provided by the company for investors (Bratten et al., 2013), and their role 

has relevant consequences during a financial crisis (Cenciarelli et al., 2018). In this sense, also the presence of 

the audit committee can have a significant positive impact in preventing the risk of frauds and irregularities 

(Beasley et al., 2000). For distressed firms in particular, statutory auditors and external auditors are obliged to 

judge the ability of the company to operate as a going concern entity for the following 12 months. In this sense, 



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with the European Union’s 2015/848/EU regulation, auditors were required to promptly communicate to the top 

management of a company the presence of indicators of financial distress. In this field, research has shown 

auditors’ ability to anticipate the emergence of a financial crisis (Bhimani et al., 2009). Therefore, their 

presence helps a company to prevent triggering this event. Research on this issue is still limited, especially in 

European countries (Cenciarelli et al., 2018). 

Committee of independent board refers to the percentage of impartial administrators inside the board. Primarily 

based on Clarke (2007), the definition of unbiased director is: “person who has no want or inclination to stay 

inside the precise grace of management, and who will be able to speak out, inside and outside the boardroom, in 

the face of management’s misdeeds with a purpose to protect the pursuits of shareholder”. Independent director 

has two roles inside the board, monitoring roles and provision of sources roles, in line with their role, their 

presupposed to growth the tracking effectiveness and aid the corporation with advices (Hillman & Dalziel, 

2003). 

The RC is evolving to become one of the most prominent issues of the global economy. The RC is recognizing 

the importance of growth and profitability of a company by focusing on the RC of the company and reporting 

its’ performance, there have been many discoveries of the possible benefits that companies may receive (Chung 

& Wei, 2017; Mintah, 2015). Many studies show that in firms with better governance, there are less instances of 

opportunistic behaviour by managers. Better governance, indeed, helps to align the interests of managers and 

shareholders boosting the corporate financial performance.   

Remuneration committee (RC) is very important to any organization, particularly quoted companies. Concerns 

for corporations to make profit have received several attentions based on the numerous amounts of scholarly 

works available, directed at improving firms’ profitability. For example, Yahaya (2014) examined social 

disclosure and profitability. Igbal and Kakakhel (2016) examined the role of remuneration committee in 

financial performance. Also, Agyemang-Mintah (2016) examined the role of RC in firm performance. Yahaya, 

Kutigi, and Ahmed (2014) examined country-specific characteristics and profitability. Gregory-Smith (2012) 

examined CEO pay and RC.  

Furthermore, Słomka-Gołębiowska (2016) examined the effect of remuneration committee independence on 

pay among banks in Poland. Yahaya and Awen (2021) related asset structure with profitability. Safari (2015) 

assessed the role of Remuneration committee in firm dividends in Malaysia. Similarly, Yahaya and Alkasim 

(2021) examined the influence of sustainability on profitability among listed insurance firms in Nigeria. 

Cameron (2005) examined the role of remuneration committees in executive pay determination and firm 

financial performance. Yahaya and Ogwiji (2021) related risk committee traits with profitability among banks 

in Nigeria. Rahayu, Harymawan, Nasih, and Nowland, (2022) looked at the influence of remuneration 

committee in firm financial performance and directors’ pay. Opeyemi, Popoola and Yahaya, (2020) related firm 

specific characteristics with profitability among listed consumer goods firms in Nigeria.  

Nigerian Corporate Governance codes and reforms in Nigeria have centered upon assisting the executive 

management and the board of a company to make the right decisions in order to achieve their stakeholders' 

objectives. So, among the subcommittees noted in the settings, the remuneration committee, as compared to 

other committees, has received the least attention from researchers to the knowledge of the researcher. For this 

reason, the researcher conducted this study to fill the gaps in the theoretical framework and to indicate the 

importance of this committee (Eulaiwi, Al-Hadi, Taylor, Al-Yahyaee, & Evans, 2016). 

Bankruptcy Risk 

The term “chance” comes from Arabic, and expresses an unexpected event. threat is generally defined as 

something risky, indefinite that is associated with the direction of phenomenon and disturbs its behavior. Key 



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definition of threat turned into added by Šoti´c and Raji´c (2015) who stated that “chance is the measure of 

possibility and the weight of undesired consequences”. in line with Cunderlík (2004), danger is the expression 

of the diploma of uncertainty in various bureaucracy. The risk is described as the state of imperfect know-how 

when the decision-maker is aware about the numerous feasible consequences of his selection and is able to 

estimate the degree of opportunity that this or that result happens (Buganová & Hudáková 2012). Businesses 

have to face certain risks, whether financial, commercial, informational or personal. According to Fetisovová et 

al. (2004), for each financial decision, it is necessary to consider not only its expected return, but also the risk 

associated with it. Risk is one of the most important limits that define the scope of financial decision-making 

(Mariniˇc 2008). Special attention should be paid to the risk of long-term financial decisions. Risk is the chance 

to achieve above-average return on investment (Kluˇcka 2006). Tranchard (2018) provided the following 

definition of risk: “Risk is the effect of uncertainty on objectives”. Risk is the probability. 

Bankruptcy risks show the possibility of losses arising from the failure to achieve financial objectives. The 

financial risks related to the financial operation of a business may take many different forms: market risks 

determined by the changes in commodities, stocks and other financial instruments prices, foreign exchange 

risks, interest rate risks, credit risks, financing risks, liquidity risks, cash flow risk, and bankruptcy risk. These 

financial risks are not necessarily independent of each other, the interdependence being recognized when 

managers are designing risk management systems (Woods & Dowd 2008). The importance of these risks will 

vary from one firm to another, in function of the sector of activity of the firms, the firm size, development of 

international transactions, etc. 

Altman Prediction Models of Bankruptcy 

Enterprise failure fashions may be extensively divided into two agencies: quantitative models that are based 

totally largely on posted financial statistics; and qualitative models, which might be primarily based on an 

internal assessment of the agency involved. Both kinds attempt to identify characteristics, whether or not 

economic or non-monetary, which could then be used to distinguish between surviving and failing businesses 

(Robinson & Maguire, 2001). 

a. Qualitative models 

This category of model rests on the premise that the use of financial measures as sole indicators of 

organizational performance is limited. For this reason, qualitative models are based on non-accounting or 

qualitative variables. One of the most notable of these is the A score model attributed to Argenti (2003), which 

suggests that the failure process follows a predictable sequence: (i) Defects (ii) Mistakes (iii) Symptoms of 

failure 

b. Quantitative models 

Quantitative models identify financial ratios with values which differ markedly between surviving and failing 

companies, and which can subsequently be used to identify companies which exhibit the features of previously 

failing companies (Argenti, 2003). Commonly-accepted financial indicators of impending failure include: low 

profitability related to assets and commitments low equity returns, both dividend and capital poor liquidity high 

gearing high variability of income. 

Edward Altman’s Z – Score Model 

Most credit score managers use traditional ratio analysis to become aware of destiny failure of companies. 

Altman (1968) is of the opinion that ratios measuring profitability, liquidity, and solvency are the maximum 

massive ratios. but, it's far hard to understand that's extra important as different research indicate unique ratios 



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as indicators of capability problems. as an example, a company may have bad liquidity ratios and may be 

heading for liquidation. That identical enterprise’s top profitability may additionally undermine the potential 

hazard that is highlighted via the bad liquidity ratios. As a end result, interpretation the usage of conventional 

ratio analyses can be wrong (Odipo & Sitati, 2008). 

Altman set out to mix some of ratios and evolved an insolvency prediction model - the Z–score model. This 

method was advanced for personal production firms and eliminated all firms with belongings much less than $1 

million. This unique model turned into no longer meant for small, nonmanufacturing, or 

255fb4167996c4956836e74441cbd507 corporations, but many credit granters today nevertheless use the unique 

Z score for all types of customers. two in addition prediction models had been formulated through Altman (from 

time to time known as model ‘A’ and model ‘B’) to the original Z score (Altman, 1968). The formula's 

approach has been used in a variety of contexts and countries, although it was designed originally for publicly 

held manufacturing companies with assets of more than $1 million. Later variations by Altman were designed 

to be applicable to privately held companies (the Altman Z'-Score) and non-manufacturing companies (the 

Altman Z"-Score). Altman's 1968 model took the following form -:Z = 1.2A + 1.4B + 3.3C + 0.6D + .999E 

Z < 2.675; then the firm is classified as "failed" 

Where: 

A = Working Capital/Total Assets 

B = Retained Earnings/Total Assets 

C = Earnings before Interest and Taxes/Total Assets 

D = Market Value of Equity/Book Value of Total Debt 

E = Sales/Total Assets 

Altman’s Revised Z-Score Model 

Rather than simply inserting a proxy variable into an existing model to calculate the Z-Scores Altman advocated 

for a complete re-estimation of the model, substituting the book values of equity for the Market value in D. This 

resulted in a change in the coefficients and in the classification criterion and related cut-off scores. The revised 

Z score model took the following form: 

Z' = 0.717T1 + 0.847T2 + 3.107T3 + 0.420T4 + 0.998T5 

Where: 

T1 = (Current Assets-Current Liabilities) / Total Assets 

T2 = Retained Earnings / Total Assets 

T3 = Earnings before Interest and Taxes / Total Assets 

T4 = Book Value of Equity / Total Liabilities 

T5 = Sales/ Total Assets 

Zones of Discrimination: 

Z' > 2.9 -“Safe” Zone 

1.23 < Z' < 2. 9 -“Grey” Zone 

Z' < 1.23 -“Distress” Zone 

Financial Ratios in Z score 

The Z-score is calculated by multiplying each of several financial ratios by an appropriate coefficient and then 

summing the results. The ratios rely on working capital, total assets, retained, EBIT, market value of equity, net 

worth. Working Capital is equal to Current Assets minus Current Liabilities (Milkkete, 2001). Total Assets is 



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the total of the Assets section of the Balance Sheet. Retained Earnings is found in the Equity section of the 

Balance Sheet. EBIT (Earnings before Interest and Taxes) includes the income or loss from operations and from 

any unusual or extraordinary items but not the tax effects of these items. It can be calculated as follows: Find 

Net Income; add back any income tax expenses and subtract any income tax benefits; then add back any interest 

expenses. Market Value of Equity is the total value of all shares of common and preferred stock. The dates 

these values are chosen need not correspond exactly with the dates of the financial statements to which the 

market value is compared (Milkkete, 2001). Net Worth is also known as Shareholders' Equity. Similarly, 

Stepanyan (2014) used the model to analyze the US Airline business and found the model to be very useful.  

Edward Z score  

Working capital to Total Assets  

Mehmet and Eda (2009) indicated that working capital is the whole current assets owned by a firm. Akindele 

and Odusina (2015) defined working capital as basically the portion of assets required by a business in current 

operation. In its gross form, it is the investment in current assets. The ratio provides information about the short-

term financial position of the business that is referred to as the liquidity. The more the working capital there is 

compared to the total assets the better the liquidity situation. According to Agha (2014) the most important 

items inside determination of working capital are inventories of the corporations, its accounts receivable and 

payables.  

Empirical Review  

Dalia (2023) examined the relationship between corporate governance and intellectual capital. It also 

investigates the impact of intellectual capital and corporate governance mechanisms on the bankruptcy risk of 

Egyptian companies listed on the EGX 100 index. Design/methodology/approach– This study depended on a 

sample of 355 observations of 71 companies listed on the EGX 100 index during 2017-2021. The modified 

Altman Z Score model was used to measure bankruptcy risk, and the value-added intellectual coefficient 

(VAIC) model was used to measure intellectual capital. Corporate governance mechanisms, such as board 

characteristics and audit committee are presented as independent variables. The results also show an 

insignificant influence of board independence and audit committee size on intellectual capital efficiency. 

Moreover, this study finds that companies with intellectual capital efficiency are less likely to go bankrupt. 

Furthermore, the results indicate that board size, independence, and meetings have a significant negative effect 

on bankruptcy risk. Thus, good corporate governance improves a company's financial health. Khiem (2022) 

determined the effect of company Governance on the relationship among the macro and micro factors inflicting 

financial misery in 240 Vietnamese indexed non-financial firms. This paper contributes empirical proof at the 

essential benefit of strong company governance practices and marginal gain in danger mitigation in improving 

company governance. the article indicates that Vietnamese firms have to implement sturdy corporate 

governance to overcome the hazard of economic misery. Handriani et al. (2021) explored the effect of board 

length, board independence, and institutional ownership on financial misery for a pattern of nine production 

agencies indexed on the Indonesia stock trade with three hundred observations for the duration of the duration 

2010-2018. They determined that institutional ownership and board independence have a tremendous effective 

impact on averting monetary distress. but board length became found to have a trifling wonderful effect on 

monetary misery. Safrida et al. (2021) tested the effect of corporate governance on bankruptcy prediction for a 

sample of 20 companies listed on the Indonesia Stock Exchange for the period 2016-2020. The results 

demonstrated a significant positive effect of the board of directors, board of commissioners, independent 

commissioners, and audit committee on the prediction of bankruptcy. The results also revealed a significant 

negative influence of Institutional ownership and managerial ownership on bankruptcy prediction. Joshua, 

Efiong, and Imong (2019) examined corporate governance and financial performance of listed deposit money 



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banks (DMBs) in Nigeria from 2007–2016 and data were obtained from their annual financial reports. Data 

were presented using tables and analyzed using panel data regression. The corporate governance mechanisms of 

board size (BSIZE), board composition (BCOM) and audit committee (ACOM) were used as independent 

variables. The findings of this study revealed that board size had a positive but insignificant relationship with 

performance. It was also observed that audit committee, board composition and bank size all had positive and 

significant relationships with return on asset. The study therefore concludes that board composition and audit 

committee are good predictors of performance as measured by return on assets (ROA). Ahmad and Masoumeh 

(2016) investigated the relationship between earnings management and quality of earnings for the bankrupt and 

non-bankrupt firms listed in the Tehran Stock Exchange from 2007 to 2012. The results of estimating 

unbalanced panel data technique for 55 firms subjected to bankruptcy of Altman's model, and 198 non-bankrupt 

firms, shows that the bankrupt firms tend to use opportunistic earnings management, and the non-bankrupt 

choose efficient earnings management. Gnyana (2015) in his research on prediction of financial distress using 

Altman Z score for selected companies in India concluded that, Z score is one of the popular and effective 

models and all investors should analyze the Z score of company before investment decision to avoid financial 

loss due to financial failure. Campa, Del Mar and Miñano (2014) conducted a study on the response to the 

question whether Spanish companies go bankrupt, compared to their counterparts, during the years prior to the 

procedure of bankruptcy law tend to manage earnings or not? In the analysis of a sample matched bankrupt 

companies, it became clear that earnings management of bankrupt companies is more than those in non-

bankrupt them. Findings showed that management tools profit operates by industry in which the company and 

the years of pre-bankruptcy are changed. In Zimbabwe, Ncube (2014) on Altman’s Z score for non-

manufacturing firms and financial institutions listed in Zimbabwe stock exchange recommended the use of the 

model in predicting corporate failure in the financial services and banking sector. From the above, despite 

Altman’s model being old and despite of its limitations, it has remained to be the most globally used model. 

Arguably that various equations now exists but they all follow the concepts of the original one derived by 

professor Altman in 1968.   

Methodology 

Due to the nature of the study, Ex Post Facto research design was adopted. The study analyzed the audited 

accounts of banks. This involves use of financial accounts of the banks under assessment for the period, 2012-

2023 to generate the financial ratios that discriminated the most in prediction of healthy banks using Altman 

Model.  

Population and Sample Size 

This population of this study consists of the deposit money banks quoted on the Nigerian Exchange Group. The 

study covered ten years annual reports and accounts of these banks from 2012 to 2023.  

The "purposive sampling technique was applied (Non-random sample). In this method, the sample is chosen 

based on what the researcher thinks is appropriate for the study. The banks licence with international 

authorization was chosen which consist a total of eight (8) out of the twenty-two (22) deposit money banks 

which was inevitably excluded during the data collection process due to incomplete data, hence majority of the 

other banks are those that either emerged or acquired during the period the study covered without international 

authorization (See appendix for details).  

Source of Data Collection 

Data were collected from only secondary sources. This data was obtained from the annual reports and audited 

accounts of the banks under assessment  

Model Specification 

The study employed Altman Model given as Zeta “Z” 

Z=1.2X1 + 1.4X2+ 3.3X3 + 0.6X4 + 1.0 X5,  

Where: 

          X1         =       Working capital to total assets 



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          X2         =       Retained earnings to total assets 

          X3      =       Earnings before interest and taxes to total asset 

          X4         =       Value of equity to total book debt 

          X5         =       Gross earnings to total assets 

The decision rule is that: 

 (i). For Z<1.81 Bankruptcy region 

 (ii). For 1.81<Z>2.675 High bankruptcy potential 

 (iii). For 2.675<Z<2.99 Low bankruptcy potential 

 (iv). For Z>2.99 Strong (No sign of bankruptcy at all). 

The Altman Model will be modified thus to incorporate corporate governance: 

ATMNit = a0 + β1ACI +β2ACDit + β3RECit+β4RMCit +β5BINDit + it urt …………………. …..…....(i) 

Where; 

ATMN= Altman Prediction Model 

ACI= Audit committee Independence 

REC = Remuneration committee 

Method of Data Analysis  

Data were analyzed with descriptive statistics, and the hypotheses will be tested with Pearson correlation, and 

multiple regression analysis. Since the focus of the study is to examine the effect of asset composition on 

financial performance, regression analysis becomes appropriate tool for it.  

Descriptive statistics employed to summarily describe the mean, median, standard deviation, kurtosis and 

skewness of the study variables. Inferential statistics will also be utilized with the aid of E-Views 9 using: 

i. Coefficient of correlation: which is a good measure of relationship between two variables that tell us about the 

strength of relationship and the direction of the relationship as well?  

ii. Regressions analysis: Regression analysis predicts the value the dependent variable based on the value of the 

independent variable and explains the impact or effect of changes in the values of the variables. 

Decision Rule 

Accept the alternative hypothesis, if the Probability value (P-value) of the test is less than 0.05 (5%). Otherwise 

reject. 

Data Analysis and Results 

Table 1: Descriptive Analysis 
 ATMN ACI REC 

 Mean  2.913370  0.377978  85.49554 

 Median  3.023000  0.330000  88.70000 

 Maximum  6.598000  1.780000  99.94000 

 Minimum  0.399000  0.100000  61.34000 

 Std. Dev.  1.547708  0.313757  12.04400 

 Skewness  0.121996  2.775521 -0.659108 

 Kurtosis  2.306899  11.63645  2.372738 

 Jarque-Bera  2.069699  404.0422  8.169404 

 Probability  0.355280  0.000000  0.016828 

 Sum  268.0300  34.77400  7865.590 

 Sum Sq. Dev.  217.9815  8.958382  13200.26 

 Observations  96  96  96 

Table 1 shows the mean (average) for each of the variables, their maximum values, minimum values, standard 

deviation and Jarque-Bera (JB) Statistics (normality test). The results in table 1 provided some insight into the 

nature of the Nigerian banks that were used in this study. 

It was observed that on the average over the twelve (12) years periods (2012-2023), the sampled banks in 

Nigeria were characterized by positive Altman bankruptcy prediction Model (2.770944). In this table, the 



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Jarque-Bera (JB) which test for normality or the existence of outliers or extreme values among the variables 

shows that most of the variables are normally distributed at 5% level of significance. This means that any 

variable with outlier is not likely to distort our conclusion and are therefore reliable for drawing generalization. 

This also implies that the least square estimate can be used to estimate the pooled regression model. 

Correlation Analysis 

In examining the association among the variables, we employed the Pearson correlation coefficient (correlation 

matrix) and the results are presented in table 2: 

Table 2: Correlation Matrix Analysis 
 

 ATMN ACI REC 

ATMN 1   

ACI -0.09191 1  

REC -0.21482 -0.44006 1 

The use of correlation matrix in most regression analysis is to check for multi-collinearity and to explore the 

association between each explanatory variable; ACI, and REC, and the dependent variable (Altman). Finding 

from the correlation matrix table shows that all our independent variables, (ACI -0.092 and REC -0.215) were 

observed to be negatively associated with dependent variable. In checking for multi-collinearity, we notice that 

no two explanatory variables were perfectly correlated. This means that there is no problem of multi-collinearity 

between the explanatory variables. Multi-collinearity may result to wrong signs or implausible magnitudes in 

the estimated model coefficients, and the bias of the standard errors of the coefficients. 

Test of Hypotheses 

Hypotheses One 

Ho1: Audit committee independence has no significant effect on bankruptcy risk deposit money banks in 

Nigeria. 

Table 3: Regression analysis between Altman predicting model and Audit committee independence 
Dependent Variable: ATMN  

Method: Least Squares   

Date: 10/21/24   Time: 11:47   

Sample: 1 103    

Included observations: 96   

     
     Variable Coefficient Std. Error t-Statistic Prob.   

     
     C 3.045741 0.264154 11.53017 0.0000 

ACI -0.546169 0.538699 -1.013868 0.3133 

     
     R-squared 0.111050     Mean dependent var 2.837883 

Adjusted R-squared 0.001300     S.D. dependent var 1.615218 

S.E. of regression 1.614976     Akaike info criterion 3.817564 

Sum squared resid 239.9496     Schwarz criterion 3.871677 

Log likelihood -177.4255     Hannan-Quinn criter. 3.839422 

F-statistic 1.027928     Durbin-Watson stat 0.556648 

Prob(F-statistic) 0.313305    

     
     
In table 3, a simple least square regression analysis was conducted to test the relationship between audit 

committee independence (ACI) and Altman bankruptcy predicting model (ATMN).  The R-squared is 



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coefficient of determination which tells us the variation in the dependent variable due to changes in the 

independent variable. From the findings in the table 3, the value of R squared was 0.111, an indication that there 

was variation of 9% on ATMN due to changes in ACI. This implies that 11% changes in ATMN of the 

economy could be accounted for by ACI, while 89% was explained by unknown variables that were not 

included in the model. The probability of the slope coefficients indicates that; P (0.313 >0.05). The co-efficient 

value of; β1= -0.546 implies that ACI is negatively related to ATMN, and this is statistically significant at 5%. 

The Durbin-Watson Statistic of 0.556648 suggests that the model does not contain serial correlation. The F-

statistic of the ATMN regression is equal to 1.027928 and the associated F-statistical probability is equal to 

0.313305, so the null hypothesis was rejected and the alternative hypothesis was accepted.  

Decision 

Since the Prob (F-statistic) of 0.313305 is higher than the critical value of 5% (0.05), then, it would be upheld 

that audit committee independence has no significant effect on bankruptcy risk deposit money banks in Nigeria, 

thus, Ho is preferred over HI. 

Hypothesis Two 

Ho2: Remuneration committee has no significant effect on bankruptcy risk deposit money banks in Nigeria 

Table 4: Regression analysis between Altman predicting model and Remuneration committee 
Dependent Variable: ATMN  

Method: Least Squares   

Date: 10/21/24   Time: 11:55   

Sample: 1 103    

Included observations: 96   

     
     Variable Coefficient Std. Error t-Statistic Prob.   

     
     C 4.741432 1.192578 3.975783 0.0001 

REC -0.022318 0.013847 -1.611698 0.1105 

     
     R-squared 0.027459     Mean dependent var 2.837883 

Adjusted R-squared 0.016888     S.D. dependent var 1.615218 

S.E. of regression 1.601521     Akaike info criterion 3.800832 

Sum squared resid 235.9681     Schwarz criterion 3.854945 

Log likelihood -176.6391     Hannan-Quinn criter. 3.822690 

F-statistic 2.597571     Durbin-Watson stat 0.573432 

Prob(F-statistic) 0.110453    

     
     
In table 4, a simple least square regression analysis was conducted to test the significant effect between 

remuneration committee (REC) and Altman bankruptcy predicting model (ATMN).  The R-squared is 

coefficient of determination which tells us the variation in the dependent variable due to changes in the 

independent variable. From the findings in the table 4, the value of R squared was 0.027, an indication that there 

was variation of 3% on ATMN due to changes in REC. This implies that only 3% changes in ATMN of the 

economy could be accounted for by REC, while 97% was explained by unknown variables that were not 

included in the model. The probability of the slope coefficients indicates that; P (0.111>0.05). The co-efficient 

value of; β1= --0.022318 implies that REC is negatively related to ATMN, and this is not statistically significant 

at 5%. 



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The Durbin-Watson Statistic of 0.573432 which is less than 2 suggests that the model does not contain serial 

correlation. The F-statistic of the ATMN regression is equal to 2.597571 and the associated probability F-

statistic is equal to 0.110453, so the null hypothesis was accepted and the alternative hypothesis was rejected.  

Decision 

Since the Prob (F-statistic) of 0.110453 is higher than the critical value of 5% (0.05), then, it would be upheld 

that remuneration committee has no significant effect on bankruptcy risk deposit money banks in Nigeria, thus, 

Ho is preferred over HI. 

Discussion of findings  

The study examined the effect of corporate governance on bankruptcy risk in deposit money banks in Nigeria. 

However, audit committee independence, and remuneration committee have no statistically significant effect on 

bankruptcy risk commercial banks in Nigeria. These results are in line with the study of Boo and Sharma (2008) 

observe no association between audit committee independence and audit fees indicating that auditors will 

minimize their effort in the presence of independent audit committee. Jensen and Meckling (1976) argued that 

the relationship between managerial share ownership and corporate debt is complex. It is argued that managerial 

share ownership can reduce managerial incentives to consume perquisites, expropriate wealth and to engage in 

other non-maximizing behavior.  

Conclusion and Recommendations 

This study investigated the effect of corporate governance on bankruptcy risk in commercial banks in Nigeria, 

using audit committee independence and remuneration committee. Data were obtained from the annual reports 

and audited accounts of the banks under assessment. Altman's original model for public companies was used to 

extract data and the formulated hypotheses were tested with regression analysis with aid of E-View 9.0.  The 

analysis and hypotheses tested shows that audit committee independence has no significant effect on bankruptcy 

risk commercial banks in Nigeria. However, the remuneration committee study revealed that has a significant 

effect on bankruptcy risk commercial banks in Nigeria. This study therefore concluded that corporate 

governance has effect on bankruptcy risk in commercial banks in Nigeria 

Based on the results, the study recommended the followings; 

1. Since the board of director serves as internal control mechanism in the corporate governance, banks policy 

makers should provide adequate regulations on the specific number of boards to be working with, hence, 

audit committee independence is likely to reduce the probability of bankruptcy as they bring wider 

knowledge and better expertise to the bank. 

2. Remuneration committee should be encouraged hence it creates an avenue for collective deliberates on 

financial issues that are significant to the banks such as straighten their operations, as well preventing it 

from going bankruptcy.  

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