LOANS AND ADVANCES EVALUATION WITH DISCRIMINANT ANALYSIS: A CASE STUDY OF FIVE COMMERCIAL BANKS

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.

1.3                   STATEMENT OF PROBLEM
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.

1.6                   SIGNIFICANCE OF THE STUDY
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.

Ø      To discard variables which are of little discriminating power to the group distinctions.

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Item Type: Postgraduate Material  |  Attribute: 78 pages  |  Chapters: 1-5
Format: MS Word  |  Price: N3,000  |  Delivery: Within 30Mins.
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