This paper is published in Volume-5, Issue-2, 2019
Area
Machine Learning
Author
Jujjuri Goutham
Co-authors
T. Anitha, S. Joshua Johnson, Routhu Dhanunjay, Vemuri Susmitha, Nagavarapu Sravani
Org/Univ
Anil Neerukonda Institute of Technology and Sciences, Visakhapatnam, Andhra Pradesh, India
Pub. Date
15 March, 2019
Paper ID
V5I2-1309
Publisher
Keywords
Random forest classifier, Defaulters, Mathew's correlation coefficient, Credit scoring

Citationsacebook

IEEE
Jujjuri Goutham, T. Anitha, S. Joshua Johnson, Routhu Dhanunjay, Vemuri Susmitha, Nagavarapu Sravani. An adaptive approach to prognosticate an individual’s capability for emolument through Machine Learning, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Jujjuri Goutham, T. Anitha, S. Joshua Johnson, Routhu Dhanunjay, Vemuri Susmitha, Nagavarapu Sravani (2019). An adaptive approach to prognosticate an individual’s capability for emolument through Machine Learning. International Journal of Advance Research, Ideas and Innovations in Technology, 5(2) www.IJARIIT.com.

MLA
Jujjuri Goutham, T. Anitha, S. Joshua Johnson, Routhu Dhanunjay, Vemuri Susmitha, Nagavarapu Sravani. "An adaptive approach to prognosticate an individual’s capability for emolument through Machine Learning." International Journal of Advance Research, Ideas and Innovations in Technology 5.2 (2019). www.IJARIIT.com.

Abstract

One of the major integrant to be considered while granting a loan is the customer‟s ability to pay back the amount to the bank as per the bank's provided a schedule. Our work focuses on the analysis of all the attributes that might affect the customer‟s ability to pay the loan. It is basically a credit scoring mechanism used by the bank to make sure a customer's intentions to apply for a loan are legit using Ensemble Algorithms. Our work gives a probabilistic predictive model or a scorecard to estimate the probability of defaulters in the current global scenario. Our work is due diligence fulfilled by the investors involved with the bank. Our aim is to prognosticate correct credit worth which will cause a significant increment in the profits of commercial institutions.
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