Md.Mahbubur Rahman

Work place: Dept. of Computer Science and Engineering, Bangladesh University of Business and Technology, Dhaka, Bangladesh

E-mail: mahabub.cse.buet@gmail.com

Website:

Research Interests: Computer systems and computational processes, Data Mining, Data Structures and Algorithms

Biography

Md.Mahbubur Rahman has been lecturing in CSE since mid of 2011, he received his B.Sc.Engg. in CSE from Patuakhali Science and Technology University in 2011and continuing his M.Sc. Engg. in CSE at Bangladesh University of Engineering and Technology(BUET), Bangladesh. He is now serving one of the top most private Universities in Bangladesh named Bangladesh University of Business and Technology (BUBT). His research interests are Digital Forensics,Secure and Trustworthy computing, Data mining, Graph theory, Biometric system.

Author Articles
Nearest Neighbor Classifier Method for Making Loan Decision in Commercial Bank

By Md.Mahbubur Rahman Samsuddin Ahmed Md. Hossain Shuvo

DOI: https://doi.org/10.5815/ijisa.2014.08.07, Pub. Date: 8 Jul. 2014

Bank plays the central role for the economic development world-wide. The failure and success of the banking sector depends upon the ability to proper evaluation of credit risk. Credit risk evaluation of any potential credit application has remained a challenge for banks all over the world till today. Artificial neural network plays a tremendous role in the field of finance for making critical, enigmatic and sensitive decisions those are sometimes impossible for human being. Like other critical decision in the finance, the decision of sanctioning loan to the customer is also an enigmatic problem. The objective of this paper is to design such a Neural Network that can facilitate loan officers to make correct decision for providing loan to the proper client. This paper checks the applicability of one of the new integrated model with nearest neighbor classifier on a sample data taken from a Bangladeshi Bank named Brac Bank. The Neural network will consider several factors of the client of the bank and make the loan officer informed about client’s eligibility of getting a loan. Several effective methods of neural network can be used for making this bank decision such as back propagation learning, regression model, gradient descent algorithm, nearest neighbor classifier etc.

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