Predictive Analytics in Retail Banking
Disha Budale1, Dashrath Mane2
1Disha Budale, Department of M.CA, V.E.S. Institute of Technology, Chembur, Mumbai, India.
2Dashrath Mane, Department of M.CA, V.E.S. Institute of Technology, Chembur, Mumbai, India.
Manuscript received on May 27, 2013. | Revised Manuscript received on June 19, 2013. | Manuscript published on June 30, 2013. | PP: 508-510 | Volume-2, Issue-5, June 2013. | Retrieval Number: E1897062513/2013©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Today banks are facing intensive competition due to the gradual growth of many banks as well as due to the increase in demands of the customers. Customers easily switch to another bank if the other bank is providing them more benefits and facilities that they want. To tap these needs of the customers and reduce the customer attrition, many banking institutions are using predictive analytics. Using the predictive analytics banks are trying to improve their relationship with customer, and retain their existing customers and also devise effective mechanism for marketing.
Keywords: Predictive Analytics, Banks, CRM, Customer Retention.