C-Score: An Alternative Banking Methodology
M.Naveen Nanda1, D. Venkata Subramanian2, N. S. Kalyan Chakravarthy3
1M. Naveen Nanda, UG Student, Research Scholar, Easwari Engineering College, (Tamil Nadu), India.
2D. Venkata Subramanian, Professsor, Department of Computer Science and Engineering, QIS College of Engineering and Technology, Ongole (Andhra Pradesh), India.
3N. S. Kalyan Chakravarthy, QIS College of Engineering and Technology, Ongole (Andhra Pradesh), India.
Manuscript received on 15 October 2019 | Revised Manuscript received on 24 October 2019 | Manuscript Published on 02 November 2019 | PP: 2439-2442 | Volume-8 Issue-2S11 September 2019 | Retrieval Number: B12840982S1119/2019©BEIESP | DOI: 10.35940/ijrte.B1284.0982S1119
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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: In this day and age, we talk the dialect of assets, stock market investigation and transaction arranged business, or to put a more extensive perspective, money. The current framework focuses on credit score as a default standard for advance application and profiting other banking facilities. The real aspect which is by all accounts missing is adaptability and a connect with the customer. This indirectly prompts a disarray of customer satisfaction and acquisition. The objective of this paper is to build up a superior association with the customers and to create a framework with more pliant aspects, thinking about a more extensive scope of factors for deciding the advance status of a potential applicant. Keeping in mind the end goal to help our speculation, we have contrived a mathematical equation that enables us to perform calculations in light of bigger scope of factors which help decide the applicant’s status. This status will appear as a value, which we call the C-Score. This value is utilized to set the level of advantages which can be profited by a customer, accordingly featuring the efficiency of a customer. A calculation is constructed utilizing random forest regression to monitor defaulters and understanding the stream of transactions with respect to advance installments, which is additionally a part of the C-Score. Machine Learning is utilized to play out the calculations at a dynamic stream, the variance being for each customer individually.
Keywords: Assets, Stock Market, Transaction, C-Score, Machine Learning, Random Forest, Regression.
Scope of the Article: Machine Learning