A Framework for Analysis of Bank Customer Records by Machine Learning
G. Poorani1, S. Vignesh2, A. S. Vijay3, A. Sachin Mareswaran4
1G. Poorani, Assistant Professor Department of Computer Science and Engineering, Sri Krishna College of Technology, Coimbatore ,Tamil Nadu, India.
2S. Vignesh, Student, Department of Computer Science and Engineering, Sri Krishna College of Technology, Coimbatore ,Tamil Nadu, India.
3A. S. Vijay, Student, Department of Computer Science and Engineering, Sri Krishna College of Technology, Coimbatore ,Tamil Nadu, India.
4A. Sachin Mareswaran, Student, Department of Computer Science and Engineering at Sri Krishna College of Technology, Coimbatore ,Tamil Nadu, India.
Manuscript received on March 15, 2020. | Revised Manuscript received on March 24, 2020. | Manuscript published on March 30, 2020. | PP: 4631-4635 | Volume-8 Issue-6, March 2020. | Retrieval Number: F8846038620/2020©BEIESP | DOI: 10.35940/ijrte.F8846.038620
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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: At present, business banks are confronting triple gigantic weight, including budgetary disintermediation, loan cost marketization and Internet fund. In the mean time, expanding monetary utilization request of clients further increases the challenge among business banks. Clients have gotten increasingly inspired by the nature of administration that associations can give them. To build their benefits for proceeding with tasks and improve the center seriousness, business banks must maintain a strategic distance from the loss of clients while getting new clients. This task talks about business bank client stir forecast dependent on different AI strategies, considering the unevenness qualities of client informational indexes. The outcomes show that this technique can successfully improve the forecast exactness of the chose model.
Keywords: Algorithm, Roc curve Customers, Bank, Marketization, Profits, Machine Learning.
Scope of the Article: Machine Learning.