Loan Application Selection and Ranking System for Private Banks in Myanmar using TOPSIS

Abstract

Decision support systems are gaining an increased popularity in various domains, including business, engineering, the military, and medicine. They are especially valuable in situations in which the amount of available information is prohibitive for the intuition of an unaided human decision maker and in which precision and optimality are of importance. Bank loan plays a vital role for enterprises and the decision making for accepting or rejecting loan applicants is also important for banks. In order to achieve loan from bank, the applicants need to fulfill the criteria. The pre selection and analysis of loan applicants required to calculate some criteria according to mathematical equation. The bank loan officer checked and calculated these criteria manually. So, the analysis of criteria is time consuming, and a prior automated system that can support decision requirements is needed to determine the loan applicants who will receive or not receive the loan. One of the Decision Support System (DSS) modeling used in decision making to establish the best criteria from a number of alternatives based on certain criteria is Multi-Criteria Decision Making (MCDM). This method is mainly chosen because the customer selection process deals with various criteria and sub criteria as foundation of loan applications. Among the MCDM methods, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is used in a decision support system to search the best loan applicants because of its ability to recommend loan applicants from several variables of applicants. TOPSIS can compute the advantage and disadvantage for several criteria of customers to the decision maker. This system implemented the decision support system for selecting the bank’s loan by using TOPSIS. This system will be implemented using JAVA programming language with Microsoft SQL Server database.