ABSTRACT
The study examined critical factors that discriminate
between Non-performing loans and advances and performing ones in commercial
Banks. Non-performing credits has been a major cankerworm that continuously
affects the Nigerian Banking System. A linear discriminant function was
developed after considering the eight factors responsible for discriminating
between Performing credits and Non-performing credits. The study revealed that
only two factors; years of experience and the tenor of the credit facility were
the most important discriminatory factors that successfully discriminate
between Performing and Non-performing credits. The model developed for the
analysis is Y = 0.282 X4 – 0.234X8 . This model was evaluated using F-value,
Chi-square, Eigenvalue, Canonical correlation and Wilk’s Lambda, and it was
confirmed to be significant in discriminating between the two credit groups.
CHAPTER ONE
1.0 INTRODUCTION
1.1 BACKGROUND
OF THE STUDY
Non-performing loans and advances have been a major
problem affecting the banking industry. It creates problem of liquidity into
the system and also is a sign that a bank is unhealthy.
As at the end of March, 2004, the CBN’s ratings of all the
banks classified 62 as sound/satisfactory, 14 as marginal and 11 as unsound,
while 2 of the banks did not render any returns during the period. The weakness
of some ailing banks are manifested by their overdrawn positions with the CBN,
high incidence of non-performing loans, capital deficiencies, weak management
and non corporate governance.
A further analysis of the returns of the marginal and
unsound banks reveals that they account for 19.2 percent of total assets of the
banking system, 17.2 percent of total deposit liabilities while the industry
non-performing assets account for 19.5 percent. Although below the trigger
points for declaring the system as distressed, they are
nevertheless of major supervisory concern (Soludo 2004).
Banks consolidation and 25bn recapitalization in Nigeria
reduces the number of deposit money banks from 89 as at end-June 2004, to 25
banks as at January 2006. The reform is designed to ensure a diversified strong
and reliable banking sector which will ensure the safety of depositors’ money,
play active developmental roles in Nigerian players in the African Regional and
Global Financial system.
In the United States of America, there had been over 7000
cases of bank mergers since 1980. In Korea, for example, the system was left
with only 8 commercial banks with about 4,500 branches after consolidation. A
bank in South Africa – Amalgamated Banks of South Africa (ABSA) has asset base
larger than all of the Nigerian commercial banks put together (Soludo 2004)
The Central Bank of Nigeria removed 5 Banks’ Chief
Executive Directors (CEO) and their Executive Directors on 14th of
August, 2009 for excessive high level of non-performing loans in five banks
which was attributable to poor corporate governance practices, lax credit, administration
processes and absence or non-adherence to banks credit risk management practices.
Thus, the percentage of non-performing loans to total loans ranged from 19% to
48% (Vanguard Online, 14 August, 2009).
Furthermore, additional three Banks’ Managing Directors
and Executive Directors were also fired on 2nd October, 2009 for the
same offences. The huge provisioning for the non-performing loans have
virtually eroded the shareholders fund. Thus, the banks are under-capitalized
for their current levels of operations and are required to increase their
provisions for loan losses, which impacted negatively on their capital (Sanusi
2009).
In other words, these banks were unable to meet their
maturing obligation as they fall due without resorting to the CBN or Inter Bank
market. Their liquidity ratios ranged from 17.65% to 24% as at May 31, 2009
(Regulatory minimum is 25%). Hence, the need to identify the factors
contributing to non-performing credits in Nigeria Banking Industries.
In furtherance of the efforts of the Central Bank of
Nigeria (CBN) to assist the banks affected by the outcome of the recent
CBN/NDIC Special Examination,
published the list of non-performing loans of N100m and above for Bank PHB,
Spring Bank, Unity Bank, Wema Bank and Equitorial Trust Bank on The Nation
Newspaper. The number of the non-performing loans of N100m and above for the
banks stated above respectively are 149, 221, 120, 79 and 45 (The Nation,
October 14, 2009) The banking
sector reform is valid for now.
1.2 DISCRIMINANT
FUNCTION ANALYSIS AS A MULTIVARIATE
TECHNIQUE
Multivariate analysis can be referred to as all
statistical methods that simultaneously analyze multiple measurements on each
individual or object under investigation. Any simultaneous analysis of more
than two variables can be loosely considered as multivariate analysis. As such,
multivariate techniques are extensions of univariate analysis (analysis of
single-variable distributions) and bivariate analysis (cross-classification
correlation).
However, to be considered
truly multivariate all of the variables must be random variables that are
interrelated in such ways that their different effects cannot be meaningful
interpreted separately.
Discriminant analysis is a multivariate technique
concerned with separating distinct set of objects or observations and with
allocating new objects to previously defined groups.
It can be referred to as a statistical technique by which
we can make decisions to categorise groups or classify individuals (objects)
into their respective groups usually on the basis of some measurement observed
on the individuals (objects). This implies that the basic problem of
discriminant analysis is to assign an observation, X, of unknown origin to one
of two (or more) distinct groups on the basis of the value of the observation.
In some problems, fairly complete information is available
about the distribution of X in the two groups. In this case we may use this
information and treat the problem as if the distribution are known.
The Central Bank of Nigeria is saddled with the
responsibility to act and protect all depositors and creditors and ensure that
no one loses money due to bank failure. The commercial banks give out
depositors money as loan and advances which should be paid back at expiration
of such facilities.
The basic question is what factors contribute or
identifies non-performing loans or performing loans. What factors or indices
should be looked into, to avoid non-performing loans which can eventually make
a bank to have liquidity problem which can culminate to classify a bank as
distressed and depositors losing their hard-earned money. Hence, the research
is focused on Discriminant Function analysis of performing loans/advances and
non-performing loans/advances.
1.4 LIMITATION
AND SCOPE
This project work is limited to commercial loans and
advances granted by commercial banks in Nigeria between 2006 and 2008, both
year inclusive. Consumer
loans are not included in this analysis.
1.5 AIMS
AND OBJECTIVES
The study is aimed at performing a discriminant analysis
on performing loans/advances and non-performing loans/advances. Using data
compiled from schedules received from 5 randomly selected commercial Banks
(Skye Bank, Intercontinental Bank, Union Bank, UBA Bank, and Bank PHB) through
their Account/Credit officers. The project seeks to achieve the following sets
of objectives:
1. To
identify the socio-economic characteristics that discriminate between
performing loans/advances and nonperforming loans/advances;
2. To
be able to predict the likelihood that loans/advances given out by a bank will
belong to a group of performing or not based on the rule to be derived with
Fisher’s Discriminant Analysis.
Non-performing loans/advances cause liquidity problems in
the banking industry whereby banks were unable to meet up with their
obligations as they fall due. This study is justified in that it will add to
the body of knowledge pertaining to factors contributing to non-performing
loans/advances.
The inferences from the research will enable the
management of various banks to restructure their loans and advances to address
the socio-economic characteristics that contributed to non-performing loans.
1.7 PURPOSE
OF DISCRIMINANT ANALYSIS
Ø
To classify cases into groups
using a discriminant prediction equation.
Ø
To investigate independent
variable mean difference between groups formed by the dependent variable.
Ø
To assess the relative importance
of the variable in classifying
the
dependent variable.
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Item Type: Project Material | Size: 78 pages | Chapters: 1-5
Format: MS Word | Delivery: Within 30Mins.
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