DocumentCode
3581276
Title
Predicting bad utility consumers in Malaysia
Author
Hoe, Alan Cheah Kah ; Dhillon, Jaspaljeet Singh
Author_Institution
Dept. of Inf. Syst., Univ. Tenaga Nasional, Kajang, Malaysia
fYear
2014
Firstpage
234
Lastpage
237
Abstract
In many organizations, especially in most utility companies including Company X, revenue collection is a major issue when customers face difficulties in paying their utility bills before the deadline. There are many reasons for this problem but it becomes a serious financial issue for the organizations when the cumulative amount of bad debts reached a staggering figure. This paper reports a study of this issue for Company X involving its customers based in Bangi and Kajang, totaling upto 1,525 customers. The study is conducted to identify the factors of customers who would default payment of their bills. The identification of such factors is important to enable Company X to identify these customers and implement the necessary measures to mitigate the problem. The CRISP-DM (Cross-Industry Standard Process for data mining) model was employed in conducting the study. The results provide an intial understanding of the issue and the solution model generated could be used to resolve the issue for other areas in Malaysia.
Keywords
data mining; financial data processing; CRISP-DM; Malaysia; bad utility consumer prediction; cross-industry standard process for data mining model; financial issue; revenue collection; Companies; Data mining; Data models; Information technology; Market research; Predictive models; CRISP-DM; data mining; data modeling clustering; data preparation; utility consumers;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Technology and Multimedia (ICIMU), 2014 International Conference on
Type
conf
DOI
10.1109/ICIMU.2014.7066636
Filename
7066636
Link To Document