Predicting churn and NPAs in banking industry

The Digital Institutional Repository of IIM Bangalore

Please use this identifier to cite or link to this item: https://repository.iimb.ac.in/handle/2074/12070

DC Field	Value	Language
dc.contributor.author	Nagadevara, Vishnuprasad
dc.date.accessioned	2020-05-05T14:16:11Z	-
dc.date.available	2020-05-05T14:16:11Z	-
dc.date.issued	2013
dc.identifier.issn	1945-2950
dc.identifier.issn	2378-8674
dc.identifier.uri	https://repository.iimb.ac.in/handle/2074/12070	-
dc.description.abstract	Banking industry has been collecting large amounts of information with respect to their customers in the recent years. This information can be used to build data mining models to address various issues such as risk management, portfolio management, trading, customer profiling, and customer relationship management etc. This paper demonstrates the effectiveness of such models in predicting customer churn and non-performing assets.
dc.publisher	International Academy of Business and Ecomomics.
dc.subject	Data Mining
dc.subject	Banking Industry
dc.subject	Customer Churn
dc.subject	Support Vector Machines
dc.subject	Non-performing Assets
dc.title	Predicting churn and NPAs in banking industry
dc.type	Journal Article
dc.identifier.doi	10.18374/JIFS-13-1.10
dc.pages	89-94p.
dc.vol.no	Vol.13	-
dc.issue.no	Iss.1	-
dc.journal.name	Journal of International Finance Studies
Appears in Collections:	2010-2019

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