Project Abstract

Abstract
The development of a credit facility calculator is aimed at providing users with a convenient tool to accurately assess and plan their credit needs. This project involves the creation of a user-friendly online platform that allows individuals to input relevant financial information, such as income, expenses, and desired loan amount, to determine the most suitable credit facility for their requirements. The calculator will utilize advanced algorithms to analyze the data provided and generate personalized recommendations based on the user's financial profile. By incorporating factors such as interest rates, repayment terms, and potential fees, the credit facility calculator will offer a comprehensive overview of the available options, enabling users to make informed decisions about their borrowing needs. Additionally, the tool will provide real-time updates and comparisons of different credit products, allowing users to explore various scenarios and choose the most cost-effective solution. The development process will involve a multidisciplinary team of software engineers, financial analysts, and user experience designers working collaboratively to ensure the calculator's accuracy, reliability, and ease of use. Rigorous testing and validation procedures will be implemented to verify the tool's functionality and performance across different devices and platforms. The credit facility calculator will be designed to comply with industry regulations and data protection standards to safeguard users' sensitive financial information. Security measures such as encryption, authentication protocols, and secure data storage will be implemented to protect user privacy and prevent unauthorized access to personal data. The ultimate goal of this project is to empower individuals to make informed financial decisions and improve their financial literacy. By providing a transparent and user-friendly tool for assessing credit facilities, users will be able to compare options, understand the associated costs, and select the most suitable product that aligns with their financial goals and capabilities. In conclusion, the development of a credit facility calculator represents a valuable resource for individuals seeking to navigate the complex landscape of credit products. By leveraging technology and data analytics, this tool will enable users to make well-informed decisions about their borrowing needs, ultimately promoting financial responsibility and empowerment.

Project Overview

INTRODUCTION

1.0 Introduction

Attracting and retaining profitable customers, and increasing revenue from those customers, is a priority of the managers of all firms in today’s globalised marketplace. It is particularly important in the highly competitive retail financial services market, where the core business of banking continues to be “the profitable management of risk”. For banks and other shareholder-owned financial services firms, risk management is consistent with their profit-maximizing objective and is evidenced by the focus of the commercial banks on providing tailored home and personal loan packages to profitable low-risk customers (Saunders and Lange, 2001). Academic research suggests that the increasing availability of consumer credit to traditionally rejected households is a major influence on rising consumer bankruptcies in developed countries (Getter, 2000). The authors show that the combination of more high-risk borrowers and more bankruptcies is a warning for financial institution managers not to allow their social role to override sound lending practice. According to Ziegel (2001), sound lending practice has three key elements namely: the systematic identification of the risk of individual loan applicants, the adjustment of lending conditions to compensate for this risk prior to loan approval; and the implementation of timely arrears procedures when payments are missed. Financial institutions are very important in any economy. Their role is similar to that of blood arteries in the human body, because financial institutions pump financial resources for economic growth from the depositories to where they are required (Shanmugan and Bourke, 2003). Commercial banks are financial institutions and are key providers of financial information to the economy. They play even a most critical role to emergent economies where borrowers have no access to capital markets (Greuning and Bratanovic, 2003). Wellfunctioning commercial banks accelerate economic growth, while poorly functioning commercial banks impede economic progress and exacerbate poverty.

Commercial banks (CBs) face various risks that can be categorized into three groups: financial risk, operational risk and strategic risk. These risks have different impact on the performance of commercial banks. The magnitude and the level of loss caused by credit risk (CR) compared to others is severe to cause bank failures (Chijoriga, 2000). Over the years, there have been an increased number of significant bank problems in both matured and emerging economies. Credit problems, especially weakness in credit risk management (CRM), have been identified to be a part of the major reasons behind banking difficulties (Grasing, 2002). Loans constitute a large proportion of CR as they normally account for 10-15 times the equity of a bank (Kitua, 2002). Kitua (2002) further argued that banking business is likely to face difficulties when there is a slight deterioration in the quality of loans, and that poor loan quality has its roots in the information processing mechanism. According to Kitua, the problem often begins right at the loan application stage and increases further at the loan approval, monitoring and controlling stages, especially when CRM guidelines in terms of policy and strategies/procedures for credit processing do not exist or weak or incomplete.

Lending has been, and still is, the mainstay of banking business, and this is more true to emerging economies where capital markets are not yet well developed (Mwisho, 2001). To most of the transition economies, lending activities have been controversial and a difficult matter. This is because business firms on one hand are complaining about lack of credits and the excessively high standards set by banks, while CBs on the other hand have suffered large losses on bad loans (Richard, 2006). It has been found out that in order to minimize loan losses and so as the CR, it is essential for CBs to have an effective CRM system in place (Basel, 2002). Given the asymmetric information that exists between lenders and borrowers, banks must have a mechanism to ensure that they not only evaluate default risk that is unknown to them ex ante in order to avoid adverse selection, but also that can evolve ex post in order to avoid moral hazard (Richard, 2006).

According to Heffernan (2002), banks face the twin problems of moral hazard (monitoring problem) and adverse selection (risk assessment problem) when dealing with small firm lending propositions. It is possible to argue that these problems can lead to a credit glut, but there has been some work in the UK, which has revealed the expected mismatches between providers (the commercial banks) and clients suggested by the theoretical papers. Banks will find it difficult to overcome moral hazard, because (for relatively small amounts of finance) it is not economic to devote resources to monitor ventures closely. However, there are marketing implications of taking what might be cost minimization approaches to these twin problems of moral hazard and adverse selection (Kantor and Maital, 2001).

To facilitate easy management of credit facility calculations there is need for the development of software systems that will accurately compute the interest rate on the loans issued to the customers. This will be more reliable that human computation as errors are more likely to take place when the computation is manually done. When this computerized system is in place, it will aid proper utilization and realization of profit on credit issued to customers. The system should be able to determine if customers are eligible to be given credit. It serves as a credit risk assessment system and interest calculator.