Call For Paper Volume:4 Issue:8 Aug'2017 |

Credit Card Risk Evaluation Using Incremental Learning Technique

Publication Date : 10/07/2015



Author(s) :

Pallavi Kulkarni , Roshani Ade.


Conference Name :
4th International Conference on Recent Trends in Engineering & Technology(ICRTET-2015) July 2-4,2015 Organized by SNJB's KBJ College of Engineering,Chandwad,Nashik,Maharashtra,India



Abstract :

Credit card is the popular mode of payment in financial field. With the increasing number of users’ worldwide, risks on use of credit card has also been increased, where there is danger of stealing of credit card details and committing threats. Incremental techniques are desirable in recent machine learning areas like financial problems such as credit card risk assessment since amount of data and information is intensifying over the time. Scale up in learning can be achieved by updating classifier as and when training data becomes available. A smart technique known as ensemble technique has become popular, in which multiple classifiers are united in such a way that correct decisions are amplified and incorrect ones are discarded. Major focus of ensemble based techniques is diversity of classifiers that leads to reduction in misclassification. This paper presents ensemble based technique named as KIN algorithm, which handles credit data efficiently and finally distinguishes the bad customers from faithful ones in more accurate way.


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