A UNIVARIATE APPROACH TO PREDICTING FAILURE IN COMMERCIAL BANKING SUB-SECTOR By Malami Muhammad Maishanu Ph.D Department of Business Admin. Udus ABSTRACT This paper examines the possibility of providing an early warning model for commercial banking sub-sector with the hope that appropriate as well as effective strategies could be adopted to resolve crises promptly before they precipitate into failure. Data were collected for this purpose from thirty-two commercial banks using their 1996 and 1997 Financial Reports. The banks are divided into two groups: distressed and healthy. The study relied on a variety of accounting ratios in developing univariate (independent t-test) model in order to explain the causes of distress and whether any difference exists between distressed and healthy banks. This analysis confirms that there is a significant difference between distress and healthy banks. The univariate model using independent t-test shows that distressed and healthy commercial banks are significantly different in respect of eight ratios at 1 percent and 5 percent levels of significance. To study concludes that an early warning model developed in this study could be used by various stakeholders to monitor distress- proneness, direct attention to laggard areas for remedial action, and adjust their relationships where necessary. 1.1 INTRODUCTION Commercial banking sub-sector as an integral part of the Nigerian financial system is among other things expected to ensure adequate flow, and efficient allocation of financial resources. Over the last decade however, the ability of the commercial banks to contribute meaningfully to the economic growth and development has been hampered by the phenomenon
Transcript
A UNIVARIATE APPROACH TO PREDICTING FAILURE IN COMMERCIAL BANKING SUB-SECTOR
By
Malami Muhammad Maishanu Ph.DDepartment of Business Admin. Udus
ABSTRACTThis paper examines the possibility of providing an early warning model for commercial banking sub-sector with the hope that appropriate as well as effective strategies could be adopted to resolve crises promptly before they precipitate into failure. Data were collected for this purpose from thirty-two commercial banks using their 1996 and 1997 Financial Reports. The banks are divided into two groups: distressed and healthy. The study relied on a variety of accounting ratios in developing univariate (independent t-test) model in order to explain the causes of distress and whether any difference exists between distressed and healthy banks. This analysis confirms that there is a significant difference between distress and healthy banks. The univariate model using independent t-test shows that distressed and healthy commercial banks are significantly different in respect of eight ratios at 1 percent and 5 percent levels of significance. To study concludes that an early warning model developed in this study could be used by various stakeholders to monitor distress-proneness, direct attention to laggard areas for remedial action, and adjust their relationships where necessary.
1.1 INTRODUCTION
Commercial banking sub-sector as an integral part of the Nigerian financial system is
among other things expected to ensure adequate flow, and efficient allocation of financial
resources. Over the last decade however, the ability of the commercial banks to
contribute meaningfully to the economic growth and development has been hampered by
the phenomenon known as distress. This paper is a modest contribution on how to signal
failure in a commercial bank with the hope that appropriate as well as effective strategies
should be adopted to resolve crises in banks promptly before they precipitate into failure.
To do this, the paper is divided into five sections. Section one is this brief introduction.
Section two reviews literature while section three presents the methodology. Section four
presents data analysis and findings while section five concludes the paper.
1.2 LITERATURE REVIEW
A variety of terms, all unpleasant, have been employed in different contexts to explain
the concept of 'failure': collapsed, failed, bankrupt, broke, and bust (Argenti: 1976:01).
In short, failure is financial insolvency and concomitant inability of an organisation to
survive.
Although the subject of failure is unpleasant, it is a sad reality that companies are
collapsing, failing, or busting. But despite the critical importance of corporate health to
economic and social progress, the subject had received practically little attention in
literature. A large number of people feel that business failure is anathema: something
that happens to someone else but hopefully never touches their own lives. They place a
premium on survival and, when failing, "assert that no error has occurred, or that if it did,
it was unimportant, or that if it was important, it was somebody else's fault" (Michael,
1973:133). However Bibeault (1982:07) observes that there are very few instances where
the phenomenal success of an entrepreneur or manager did not follow on the heals of
earlier failure. Again, some failures have led to advancements in organisation change
(Fleishman: 1953, Lawler et’al: 1973) and much can be learned from studying failures in
organisations (Mirvis and Berg: 1977).
Bibeault (1982:09-10) defines business failure from four perspectives: social; economic;
legal; and managerial. From the social standpoint, he argues in terms of its impact. That
is, the human suffering that such a phenomenon usually brings. It affects almost
everyone: the owners; employees; government; customers; investors; suppliers; creditors;
and the society in general. However, not everyone agrees that the longer-range social
impact of corporate failure is negative. Grisati as cited in Bibeault (1982:09) points that:
Some companies never have a reason to exist in the first place. In a lot of markets there is room for two or three companies and no more. Usually the last guy in beyond that point barely makes a living in good times and is extremely vulnerable in bad times, and for good reason, because he shouldn’t exist in the first place. Any good turnaround man will spot that situation right away and avoid it like the plague.
From the economic perspective, Bibeault (1982:10) further views failure as a situation
whereby the realised rate of return on investment capital is significantly and continually
lower than prevailing rates on similar investments. In fact, a company could be an
economic failure for years and yet, in the absence of legally enforceable debt, be able to
meet its current obligations. This view of failure is however subjective, and there are
very few data available on industry or company incidence of economic failure.
Legally, a company/firm is declared as a failure if it is not able to meet its current
obligations and settling its outstanding debts. Thus, failure is synonymous with
insolvency (Benston et’al:1986) and bankruptcy (CFMRIMT: 1985). Glaessner and Mas
(1995) on the contrary, opine that insolvency needs not be synonymous with failure.
Failure occurs only when insolvency is officially recognised and the organisation is
closed. Caprio and Klingebiel (1997:84) however, see financial distress as a situation
where a significant portion of the banking system is insolvent.
A business can also be a failure from a managerial perspective before it is an economic
failure and certainly long before a legal failure. Managerial failure is measured by a long
period of decline leading to large write-offs and to losses at the bottom line, which
culminate, into intense pressure for a change in management.
Argenti (1976) identifies twelve elements that cause failure and links them together thus:
If the management of a company is poor then two things will be neglected: the system of accounting information will be deficient and the company will not respond to change (some companies, even well managed ones, may be damaged because powerful constraints prevent the managers making responses they wish to make). Poor managers will also make at least one of three other mistakes: they will overtrade; or they will launch a big project that goes wrong: or they will allow the company’s gearing to rise so that even normal business hazards become constant threats. These are the chief causes, neither fraud nor bad luck deserve more than a passing mention. The following symptoms will appear: certain financial ratios will deteriorate but, as soon as they do, the managers will start creative accounting, which reduces the predictive value of these ratios and so lends greater importance to non-financial symptoms. Finally, the company enters a characteristic period in its last few months
It is pertinent to note that though these mechanisms operate logically, not all
organisations need to go the whole stretch. Besides, Argenti was silent about the nature
of the organisation, size, and even ownership structure. Yet, they at least buttress the
symptoms and possible causes of failure in organisations.
Specifically narrowing down to a banking business, one discovers that the meaning of
terms such as bankruptcy and insolvency in Corporation Law and Finance do not carry
over in precisely the same way to banking (Benston et’al: 1986:91). Most firms face the
danger of insolvency only as obligations become due. Insolvency or bankruptcy is a
potentially greater threat to a bank than most firms are, because the bulk of the banks’
liabilities are payable on demand or on short notice. Economic insolvency is not fatal to
the business firm because most creditors must wait until their obligations come due to
take any action, regardless of the condition of the firm. Economic insolvency is a
potentially serious situation for a bank, because knowledge of that condition might well
provoke a run on the bank.
In economic terms, banks become insolvent when the market (present) value of their net
worth (capital) becomes zero. At this point, the present value of a bank’s total assets is
equal to the present value of its deposit and non-deposit liabilities other than equity
capital (Benston et’al: 1986, 37). At least economically, the bank no longer belongs to
the shareholders, but to its creditors (including depositors and deposit insurance agencies,
if any). When declared insolvent, the bank is considered to have failed, with penalties
accruing to shareholders and possibly also managers, depositors and other creditors. A
bank fails, if there is a regulatory induced cessation in its operations as an independent
entity free of direct intervention and oversight by a regulatory agency (Benston et’al,
1986:38). Banks are not subject to the bankruptcy laws that apply to other firms as
Benston et’al (1986) further argue. Their analogous legal framework is the power of the
Chartering Authority (e.g. CBN) to declare it `insolvent' and close it and the subsequent
appointment of a receiver. The receiver closes the bank by liquidating its assets or keeps
the doors of the bank open (under a different name and/or ownership). In literature
however, experts have debated the merits and demerits of both options under different
conditions.
Bank failure may differ from failures in other organisations because of its contagious
nature. As Nadler and Bogen (1933: 21-2) state, "a bank failure is an economic, a
financial and a social disaster... a series of bank failures is very aptly called as epidemic.
Failures are contagious ...The collapse of one bank of itself tends to undermine the
confidence of the community and start runs on others". Benston et’al (1986:47) add that
financial problems in one bank may be contagious and ignite runs on other banks.
Bradford (1932:239-340) in addition argues that if bank failures continue on a wide scale,
business concerns, as well as individuals will massively prefer liquidity than leave money
in their accounts. This will have system-wide domino or ripple effect (Benston et’al
1986:68). In support of this, Thornton (1802) and Humphrey (1983) as cited by Benston
et’al (1986) note that:
If one bank fails, a general run on the neighbouring ones is apt to take place, which if not checked at the beginning by a pouring into the circulation a large quantity of gold, leads to very expensive mischief.
Benston et’al 1986) also cite Bagehst (1894) who concludes that
If any large fraction of (money held by bankers) really was demanded, our banking system and our industrial system too, would be in great danger...In wild periods of alarm, one failure makes many
Many factors cause bank failure just as there are many possible causes of death of a
human being (Afolabi, 1994:07-08). In most cases however, it is a case of one factor
precipitating others. The following are causes of bank failure discussed in literature: Bad
management (de-Juan: 1991, Sheng: 1990, Bibeault: 1982 and Thomas (1935);
Inadequate Capital Base (Sheng:1990); Inadequate Supervision (Borish et’al (1995), and
(Graddy and Spencer: 1990); Unbalanced Risk Assets Portfolio and Poor Asset Quality
(Afolabi:1994, Graddy and Spencer :1990, and de Juan: 1991); In-ability to Adapt to
Changes (Afolabi, 1994); Fraud (Graddy and Spencer: 1990, and McCoy (1987);
Political Interference (Sheng: 1996 and Afolabi: 1994); Inappropriate Macroeconomic
Policies (Sundararajan: 1988, Long: 1988) and Hinds:1988); Inadequate planning
(Afolabi: 1994, Graddy and Spencer: 1990, and Sinkey: 1979)
In addition to the foregoing, failure of a bank has multi-dimensional consequences
(Afolabi, 1994) and can be observed at micro and macro levels. In addition, Benston
et’al (1986) argue that bank financial difficulties and failures are both affected by and
affect economic activity in their communities. They argue that when a bank is declared
insolvent, it is considered to have failed, with penalties accruing to shareholders and
possibly managers and/or uninsured depositors, other creditors and customers.
Bank runs and contagion are also by-products of problem banking system (Sheng: 1990).
de-Juan (1991) concurs that bank failure might trigger off a confidence crisis resulting in
deposit runs, which affect stability, contribute to demonetisation, and prompt capital
flight. The implications he opines, are distortions in resource allocation, upward pressure
on interest rates, a corporate culture with no sense of risk or disclosure and losses in the
system (1991:07). Ebhodaghe (1996) also examines the consequences of bank failure on
the credit market, arguing that failed banks will no doubt be incapacitated from extending
new lending.
1.3 METHODOLOGY
The entire commercial banking sub-sector is regarded as the population of this study. As
at the end of 1994, there were sixty-five (65) commercial banks in operation with a total
of two thousand two hundred and fifty nine (2259) branches (NDIC Annual Report,
1994:71). It is however not possible to undertake such an up-hill task. This is because the
population is quite large which makes sampling inevitable.
Data were collected for this purpose from thirty-two commercial banks using their 1996
and 1997 Financial Reports. One of the observations was incomplete, and therefore
excluded from analysis. Consequently, sixty-three observations were used for the
analysis. The banks are divided into two groups: distressed and healthy. The distressed
group consists of twelve banks. This is because all the banks (except one in 1997) were
within that period considered as distressed by the regulatory authorities. The number was
arrived at through the scanty information available about distressed banks in the
publications of Central Bank of Nigeria (CBN) and Nigeria Deposit Insurance
Corporation (NDIC). Besides, it is their policy not to disclose the identities of distressed
banks. Twenty healthy commercial banks were purposively selected using data collected
from the regulatory authorities and the Nigerian Banking Index 1998 (Pharez: 1999). All
the banks selected have satisfied two criteria: (a) their names did not appear in the
distressed banks’ list and; (b) they all have satisfied the minimum paid-up capital
requirement. The purpose is to use their financial reports and returns to the regulatory
authorities for the purpose of computing the relevant ratios. The data collected from the
financial statements, statutory reports were used in developing univariate (independent t-
test) model in order to explain the causes of distress and whether any difference exists
between distressed and healthy banks.
Fifteen (15) different financial ratios were computed based on available data from the
statutory returns of selected banks and their financial statements. The ratios are further
divided into the following five (5) broad categories: capital adequacy, profitability,
liquidity, risk, and asset quality. There are six capital adequacy, three liquidity and three
profitability ratios. In addition, there is one ratio measuring risk and two measuring asset
quality. Ownership variable was also considered because of the role it has played as
reported in various works such as Nyong (1994), and Jimoh (1993). These fifteen ratios
and ownership variables represent the performance variables referred to in hypothesis
two of this study. The researcher utilises them in developing an early warning model
from univariate analysis in order to test the hypothesis on the differences of means of
distressed and healthy banks. These ratios are briefly described below:
CAPITAL ADEQUCY RATIOS
CAPADER1 This is defined as total assets to total shareholders’ funds (tassets/tsfunds). This shows the extent to which total assets are supported by shareholders’ funds. The higher the value of this ratio the better the financial health, hence a positive relationship is expected.
CAPADER2 This is defined as total shareholders’ funds to total assets (tsfunds/tassets). This is a measure of leverage and it reveals how much each Naira of equity has been stretched to create assets. It tells us how much equity cushions the asset base of the bank rests on. The higher the value of this ratio the better the financial health, hence a positive relationship is expected.
CAPADER3 This is defined as total shareholders’ funds to total net loans (tsfunds/tnloans). This reveals the extent to which shareholders’ funds have been used in granting loans to customers. The higher the value of this ratio, the stronger the financial position of the bank. Thus, a Positive relationship is expected.
CAPADER4 This is defined as total shareholders’ funds to total deposits (tsfunds/tdeposits). It gives a measure of the capacity of shareholders’ funds to withstand sudden withdrawals; the use of a bank’s capital as a bridge between demand and supply of funds. If bank’s capital cannot serve as a bridgehead in this respect, the stability of the bank will depend on the degree and extent of withdrawal by depositors. The higher the value of this ratio, the better for the financial health of the company. Thus, a positive relationship is expected.
CAPADER5 This is defined as total shareholders’ funds to contingency liabilities (tsfunds/conliab). This measures the extent to which banks carry off-balance sheet risks, which may crystallize if the counter parties default. It also reveals the adequacy of the bank’s capital against potential losses from off-balance sheet transactions. One would expect a positive relationship as the greater the value of this ratio, the better the financial health.
CAPADER6 This is defined as total shareholders’ fund to total risk weighted assets (tsfunds/trwa). It is a measure of shareholders’ funds in absorbing losses arising from risk assets. A positive relationship is expected because the higher values of this ratio tend to be associated with stronger financial positions.
LIQUIDITY RATIOS
ROA This is defined as net profit to total assets (nprofit/tassets). This reveals the relationship between after tax profit and total assets. A positive relationship is expected, as higher values of this ratio tend to be associated with stronger financial positions.
ROE This is defined as net profit to total shareholders’ funds (nprofit/tsfunds). It is a function of the profitability of the asset base and leverage, such that the higher leverage the more the return to shareholders. Thus, a positive relationship is expected because the higher the value of this ratio the better for the bank.
NPFIXASS This is defined as net profit to fixed assets (nprofit/fassets). This measures the return of the bank’s fixed assets and it is expected to have a positive relationship to the probability of distress.
PROFITABILITY RATIOS
LIQUIDR1 This is defined as total net loans to total deposit (tnloans/tdeposit). It measures the extent to which a bank has tied up its deposits in less liquid assets. The greater the value of this ratio, the weaker the financial health, implying a negative relationship is expected. In fact, a level below 75% suggests that the bank is liquid and it has not tied up its deposits in less liquid banking assets.
LIQUIDR2 This is defined as demand liabilities to total deposits (dliab/tdeposit). Demand liabilities refer to core deposits (savings and demand liabilities). The ratio tells us what portion of the total deposits is less vulnerable to sudden withdrawals. The greater the value of this ratio, the weaker the financial health of a bank.
LIQUIDR3 This is defined as gross loans to total deposits (gloans/tdeposit). It measures the extent to which banks have tied up their deposits in less liquid assets. A negative relationship is expected since the greater the value of this ratio, the weaker the financial health of a bank.
RISK
TRWATOA This is defined as total risk weighted assets to total assets (trwa/tassets). This measures the risk profile of a bank. This ratio is both a measure of how risky the bank asset portfolio is and for a given level of return, how efficient the bank management is in selecting its portfolio. A higher value of this ratio tend to be associated with bank distress
ASSEST QUALITYASEQUAL1 This is defined as loan loss provision to gross loans (llosspr/gloans). It measures the adequacy of
loan loss provision to meet future losses on gross portfolio. The higher the value of this ratio, the more the probability of bank distress. Thus, a negative relationship is expected.
ASEQUAL2 This is defined as loan loss provision to total net loans (llosspr/tnloans). This ratio measures the adequacy of loan loss provision and the ability of the bank to meet further losses on total net loans. A negative relationship is expected, as higher values of this ratio tend to be associated with bank distress.
OWNERSHIPOWNERSHIP The ownership category was simplified to a dummy variable, which takes the value of one for
government owned banks and zero for private owned banks. The higher the value of this ratio, the greater the level of ownership interference, and the more the probability of distress.
However, one of the major limitations of using accounting data or ratio particularly in
banking business is that the data may not be free from manipulation. Some banks
especially those in trouble may likely engage in window dressing or creative accounting
in presenting their financial statements to convince the public that they are healthy. This
is a limitation of this study and should be borne in mind.
For a two-group univariate analysis, the appropriate test statistic is the t statistic (a special
case of ANOVA) (Joseph et’al, 1995:284). The t-test is also the most commonly used
method to evaluate the differences in means between two groups. Theoretically, the t-test
can be used even if the sample sizes are very small (e.g., as small as 10; some researchers
claim that even smaller n's are possible), as long as the variables are normally distributed
within each group and the variation of scores in the two groups is not reliably different.
This study therefore uses the independent t-test, which is a univariate model, to test the
differences of means of the mutually exclusive and exhaustive groups. For example, the
test was applied to examine whether or not distressed and healthy banks differ with
respect to certain financial performance variables. Theoretically, two mutually exclusive
and exhaustive groups differ significantly with respect to certain variables if the absolute
value of:
_ _ X1 - X2
t = SI
2 S2 2
NI + N2
Where XI & X2 are the sample means of Groups 1 & 2
SI2 & S2
2 are the variances of Groups 1 & 2
NI & N2 is the sample size
is greater than the tabulated value of t with N-2 degrees of freedom. In other words,
absolute values of the t statistic that exceed the critical value of the t statistic (tcrit ) lead to
rejection of the null hypothesis of no difference between the distressed and healthy bank
groups.
1.4 DATA ANALYSIS AND FINDINGS
Here, Independent t-test univariate model is employed in order to test the hypothesis on
the differences of means of distressed and healthy banks. The result in Table 1.1 below is
used to test the hypothesis – “there is no significant difference between distressed and
healthy banks with respect to performance variables in the Nigerian commercial banking
sector” - . To test this hypothesis, performance variables serve as the independent
variables while distressed and healthy bank groups are dependent variables. Thus for
ease of analysis, the hypothesis is further divided into other sixteen set of hypotheses
expressed in null and alternative forms. Table 1.1 presents the summary of the t-test
Source: SPSS Output ** Significant at 1% * Significant at 5%
The hypotheses are presented and tested below.
1. H0 There is no significant difference between distressed and healthy banks with respect to their ownership structure.
H1 There is a significant difference between distressed and healthy banks with respect to their ownership structure.
The above set of hypothesis was tested using the independent t-test. The results are
shown in Table 6.6. From the results in the table, it is evident that while the distressed
banks report a mean ownership structure of 0.83, the figure for healthy ones averages
0.15. The results also show a t-ratio of 7.18, which is significant at the 1 percent level.
Thus, the null hypothesis is rejected in favour of the alternative. This leads to the
conclusion that the extent of government equity interest is a significant determinant of
distress.
2. H0 There is no significant difference between distressed and healthy banks with respect to capader1.
H1 There is a significant difference between distressed and healthy banks with respect to capader1.
In testing this set of hypothesis, the result in Table 6.6 is used. From the table, the
distressed banks report a mean score of 6.24 and the mean figure for healthy banks is
11.70. The result shows a t-ratio of –1.35, which is not significant at the 1 percent level.
Thus, the null hypothesis is not rejected. This leads to the conclusion that capader1
which is the ratio of total assets to total shareholders’ fund is not a significant
determinant of distress in the Nigeria Commercial banking sector.
3. H0 There is no significant difference between distressed and healthy banks with respect to capader2.
H1 There is significant difference between distressed and healthy banks with respect to capader2.
Capader2 is defined as total shareholders’ fund to total assets. This ratio reveals how
much each Naira of equity has been stretched to create assets. More importantly, the
ratio tells how much equity cushion the asset base of the bank rest on. From table 6.6, it
is observed that the distressed banks report a mean of -3.13 and the healthy banks average
0.11. With a t-ratio of negative 1.92 at 1 percent level, the null hypothesis is not rejected.
The implication of this result is that capader2 just like capader1 is not a significant
determinant of distress. This is perhaps because not all assets are risky.
4. H0 There is no significant difference between distressed and healthy banks with respect to capader3.
H1 There is significant difference between distressed and healthy banks with respect to the capader3.
Capader3 relates total equity with total net loans. It reveals the extent to which
shareholders’ fund has been used in granting loans to customers. From Table 6.6, the
mean score reported by distressed banks is -3.19 and 0.44 for healthy bank. The results
also show a t-ratio of -2.41, which is significant at 1 percent level. Based on this, we
reject the null hypothesis in favour of the alternative. This leads to the conclusion that
the ratio of shareholders’ fund to total net loans is a significant determinant of distress.
5. H0 There is no significant difference between distressed and healthy banks with respect to capader4.
H1 There is significant difference between distressed and healthy banks with respect to capader4.
Capader4 gives an impression of the capacity of shareholders’ funds to withstand sudden
withdrawals; the use of a bank’s capital as a bridge between demand and supply of funds.
If bank’s capital cannot serve as a bridgehead in this respect, the stability of the bank will
depend on the degree and extent of withdrawal by depositors. From the independent t-
test result in Table 6.6, the category of banks classified as distressed reports a mean of -
1.60 and 0.28 for healthy banks and a t-ratio of negative 6.34. Based on these figures, we
reject the null hypotheses in favour of the alternative hypothesis. This further confirms
that capader4 as significant determinant of distress.
6. H0 There is no significant difference between distressed and healthy banks with respect to capader5.
H1 There is significant difference between distressed and healthy banks with respect to capader5.
Capader5 measures the extent to which banks carry off-balance sheet risks, which may
crystallise if the counter parties default. This ratio reveals the adequacy of the bank’s
capital against potential losses from off-balance sheet transactions. To test its
significance as a determinant of distress, Table 6.6 reports the mean score of -358.74 and
1.42 for distressed and healthy banks respectively. The t-ratio of -1.63 is also reported in
Table 6.6. Thus, the null hypothesis is not rejected. The implication of this is that
shareholders’ fund to contingency liabilities ratio is not a significant determinant of
distress in the Nigerian Commercial banking sector.
7. H0 There is no significant difference between distressed and healthy banks with respect to capader6.
H1 There is significant difference between distressed and healthy banks with respect to capader6.
This measure is a refinement of the capader2 presented earlier. It captures the capacity of
shareholders’ fund in absorbing losses. It is defined as total shareholders’ fund to total
risk-weighted assets. With a mean score of -0.58 for distressed banks, 0.22 for healthy
banks, and a t-value of -7.12, this measure is a significant determinant of distress. This
also confirms the limitation of total shareholders’ fund to total assets (capader2), which is
not interested in the protection offered by equity to the risk assets. Therefore based on
the above the null hypothesis is rejected in favour of the alternative hypothesis.
8. H0 There is no significant difference between distressed and healthy banks with respect to ROA.
H1 There is significant difference between distressed and healthy banks with respect to ROA.
Return-On-Assets (ROA) captures the relationship between net profit and total assets.
This ratio has prominently been used in a portfolio of ratios in failure prediction studies.
From the result in Table 6.6, it is evident that while the distressed banks report a mean
score of -.3293, the figure for healthy ones averages 0.0247. The results also show a t-
ratio of -1.87, which is therefore not significant. Thus, the null hypothesis is not rejected.
From this result, one concludes that Return on Asset ratio is not a significant determinant
of distress.
9. H0 There is no significant difference between distressed and healthy banks with respect to ROE.
H1 There is significant difference between distressed and healthy banks with respect to ROE.
Return-On-Equity (ROE) is a function of the profitability of the assets base, such that the
higher profit the more the return to shareholders. In a situation where banks do not make
profit but loss, this eats up the shareholders’ funds. To test the above set of hypothesis,
we use the independent t-test results shown in Table 6.6. From the results in the table, it
is clear that the distressed and healthy banks report a mean score of 0.0043 and 0.23
respectively. The table also reveals t-ratio of -1.95, which is significant at the 1 percent
level. Thus, the null hypothesis is rejected in favour of the alternative. This leads to the
conclusion that ROE is a significant determinant of distress.
10. H0 There is no significant difference between distressed and healthy banks with respect to npfixass.
H1 There is significant difference between distressed and healthy banks with respect to npfixass.
Npfixass measures the return of the firm’s fixed assets and it is expected to have a
positive relationship to the profitability of distress. From the results in Table 6.6, the
distressed banks report a mean of -2.3902 and 0.6116 for healthy banks. The table also
reveals a t-value of -2.50. In view of this result, the null hypothesis is rejected in favour
of the alternative. The implication of this is that the ratio of net profit to fixed assets is a
significant determinant of distress.
11. H0 There is no significant difference between distressed and healthy banks with respect to liquidr1.
H1 There is significant difference between distressed and healthy banks with respect to liquidr1.
Liquidr1 reveals the relationship between total net loans to total deposits. This ratio
measures the extent to which a bank has tied up its depositors in less liquid earning
assets. To test the significance of this ratio the independent t-test was used and the result
shown in Table 6.6. It is evident from the table that while the distressed banks report a
mean of 1.02 for liquird1, the healthy banks report an average of 0.70. The results also
show a t-ratio of 1.42, which is not significant. Thus, the null hypothesis is not rejected.
This leads to the conclusion that the ratio of total net loans to total deposit (liquidr1) is
not a significant determinant of distress in the Nigerian commercial banking sector.
12. H0 There is no significant difference between distressed and healthy banks with respect to liquidr2.
H1 There is significant difference between distressed and healthy banks with respect to liquidr2.
Liquidr2 expresses the ratio of demand liabilities to total deposits. In Nigerian banks,
demand liabilities are core deposits. The ratio tells us what portion of the total deposits is
less valuable to sudden withdrawal. Since savings and demand deposit constitute the
core deposit, we added savings to demand liabilities to arrive at total demand liabilities.
In our independent t-test, we observed from Table 6.6 that the group of distressed banks
reports a mean of 0.9136 while the mean healthy banks averages 0.80. With a t-ratio of
1.32, the result therefore shows no insignificant differences between the two groups of
banks. Therefore, the null hypothesis is not rejected. We conclude that liquidr2, just like
the liquidr1, is not a significant determinant of distress.
13. H0 There is no significant difference between distressed and healthy banks with respect to liquidr3.
H1 There is significant difference between distressed and healthy banks with respect to liquidr3.
Liquidr3 is the ratio of gross loans to total deposits. This ratio is similar to the
liquidr1except that gross loans are used instead of net loans. The loan loss provision has
not been deducted from the former. Thus without the effect of loan loss provision we try
to measure the extent to which the banks have tied up their deposits in less liquid earning
assets. The distressed banks report a mean of 2.20 while the healthy ones report an
average of 0.75. With a t-value of 2.52, which is significant at the 5 percent level, the
null hypothesis is rejected in favour of the alternative. This leads to the conclusion that
unlike liquidr1, liquidr3 is a significant determinant of distress.
14. H0 There is no significant difference between distressed and healthy banks with respect to trwatoa.
H1 There is significant difference between distressed and healthy banks with respect to trwatoa.
Bankers take reasonable risk; and unfortunately, bad or non-performing loans come with
earning assets creations. Trwatoa is defined as the ratio of risk weighted assets to total
Assets. From Table 6.6, the distressed banks report a mean of 3.01 while the healthy
ones an average of 0.57. The table also reveals a t-ratio of 1.98, which is not significant.
Thus the null hypothesis is not rejected. This means that risk variable as measured by the
total risk weighted asset to total assets is not a significant determinant of distress.
15. H0 There is no significant difference between distressed and healthy banks with respect to asequal1.
H1 There is significant difference between distressed and healthy banks with respect to asequal1.
Asequal1 examines the extent to which loan loss provision to gross loans ratio is a
determinant of bank distress. The ratio measures the adequacy of loan loss provision to
meet future losses on gross portfolio. From the result in Table 6.6, the distressed banks
report an average of 0.50, while the healthy banks report a mean score of 0.07. The
results also show a t-value of 9.11, which is very significant at the 1 percent level. Thus,
the null hypothesis is rejected in favour of the alternative hypothesis. The implication of
this is that asequal1 is a major determinant of distress. It also implies that the distressed
banks, on the average do not make adequate provisions to meet future losses on gross
loans.
16. H0 There is no significant difference between distressed and healthy banks with respect to asequal2.
H1 There is significant difference between distressed and healthy banks with respect to asequal2.
Just like asequal1 except for the gross loans, asequal2 examines the relationship between
loan loss provision and total net loss. This ratio measures the adequacy of loan loss
reserves. From the results shown in Table 6.6 it is clear that the distressed banks report a
mean score of 1.78 while 0.08 for healthy banks: The t-value is computed to be 2.71 and
is significant at 1 percent level. Based on these figures, the null hypothesis is rejected in
favour of the alternative hypothesis. This shows that similar to the asequal1, asequal2 is
also a significant determinant of distress.
This analysis confirms that there is a significant difference between distress and healthy
banks. The univariate model using independent t-test shows that distressed and healthy
commercial banks are significantly different in respect of eight ratios – ownership, total
shareholders’ funds to total deposits (capader4), total shareholders’ funds to contingency
liabilities (capader6), Return On Equity (ROE), Net profit to fixed assets (Npfixass),
Gross loans to total deposits (liquidr3), Loan loss provision to gross loans (asequal1), and
Loan loss provision to net loans (asequal2) at 1 percent and 5 percent levels of
significance.
The ownership of distressed banks was in the ratio of 17:3 in favour of government
confirming the thesis that ownership is directly related with distress condition of banks.
The capital adequacy ratios (capader4 and capader6) show a point of departure between
the healthy and distressed banks. The former had strong shareholders’ funds capable of
withstanding potential losses from off-balance sheet transactions and losses arising from
risk assets. In case of profitability ratios (ROE and Npfixass), the distressed banks as
against healthy banks are characterised with negative returns on shareholders’ funds (i.e.
asset base and particularly the fixed assets). Distressed banks unlike healthy banks have
poor liquidity position triggered largely through tying deposits in less liquid assets
(liquidr3) which consequently create liquidity squeeze in times of high demand. The
distressed banks equally have higher values of asequal1 and asequal2, which imply poor
asset quality due to poor loan portfolio in comparison with healthy. This consequently
requires a higher loan loss provision. Thus, distress in the commercial banking sub-sector
is caused by ownership interference, inadequate capital, poor profitability, illiquidity, and
poor asset portfolio.
1.5 CONCLUSION
It is hoped that this model can serve as a means of predicting bank failure in the Nigerian
commercial banking sub-sector. When all the stakeholders are aware that deterioration in
certain financial ratios of a bank is an early sign of problem, they would be in a better
position to appropriately adjust their relationship with the bank. On the part of regulatory
and supervisory authorities, this model would help in igniting a process of prompt
identification and dealing with distressed banks. However, the task of ensuring financial
system stability in general and commercial banking sub-sector in particular does not lie
with government/regulatory agencies alone but all hands should be on deck for this
colossal unremitting responsibility.
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