AN EFFICIENT DATA PRE PROCESSING FRAME WORK FOR LOAN CREDIBILITY PREDICTION SYSTEM

Soni P M, Varghese Paul, M.Sudheep Elayidom

Abstract: In todays world data mining have increasingly become very interesting and popular in terms of all applications especially in the banking industry. We have too much data and too much technology but dont have useful information. This is why we need data mining process. The importance of data mining is increasing and studies have been done in many domains to solve tons of problems using various data mining techniques. The art of preparing data for data mining is the most important and time consuming phase. In developing countries like India, bankers should vigilant to fraudsters because they will create more problems to the banking organization. Applying data mining techniques, it is very effective to build a successful predictive model that helps the bankers to take the proper decision. This paper covers the set of techniques under the umbrella of data preprocessing based on a case study of bank loan transaction data. The proposed model will help to distinguish borrowers who repay loans promptly from those who do not. The frame work helps the organizations to implement better CRM by applying better prediction ability

Keywords: Data preprocessing, Customer behavior, Input columns, Outlier columns, Target column, Dataset, CRM

DOI: https://doi.org/10.15623/ijret.2015.0405051