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Improving Credit Risk Assessment in MSMEs: A Machine Learning-Based Approach

Megha Mishra1 , Manish Varshney2

  1. Shri Siddhi Vinayak Institute of Technology, AKTU, Lucknow, India.
  2. Dept. of Computer Science and Engineering, Shri Siddhi Vinayak Institute of Technology, Bareilly, India.

Section:Research Paper, Product Type: Journal Paper
Volume-11 , Issue-7 , Page no. 29-33, Jul-2023

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v11i7.2933

Online published on Jul 31, 2023

Copyright © Megha Mishra, Manish Varshney . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Megha Mishra, Manish Varshney, “Improving Credit Risk Assessment in MSMEs: A Machine Learning-Based Approach,” International Journal of Computer Sciences and Engineering, Vol.11, Issue.7, pp.29-33, 2023.

MLA Style Citation: Megha Mishra, Manish Varshney "Improving Credit Risk Assessment in MSMEs: A Machine Learning-Based Approach." International Journal of Computer Sciences and Engineering 11.7 (2023): 29-33.

APA Style Citation: Megha Mishra, Manish Varshney, (2023). Improving Credit Risk Assessment in MSMEs: A Machine Learning-Based Approach. International Journal of Computer Sciences and Engineering, 11(7), 29-33.

BibTex Style Citation:
@article{Mishra_2023,
author = {Megha Mishra, Manish Varshney},
title = {Improving Credit Risk Assessment in MSMEs: A Machine Learning-Based Approach},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {7 2023},
volume = {11},
Issue = {7},
month = {7},
year = {2023},
issn = {2347-2693},
pages = {29-33},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=5598},
doi = {https://doi.org/10.26438/ijcse/v11i7.2933}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v11i7.2933}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=5598
TI - Improving Credit Risk Assessment in MSMEs: A Machine Learning-Based Approach
T2 - International Journal of Computer Sciences and Engineering
AU - Megha Mishra, Manish Varshney
PY - 2023
DA - 2023/07/31
PB - IJCSE, Indore, INDIA
SP - 29-33
IS - 7
VL - 11
SN - 2347-2693
ER -

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Abstract

This paper delves into the utilization of machine learning (ML) to enhance the credit risk assessment of Micro, Small and Medium Enterprises (MSMEs). With the burgeoning digital economy and growing complexities in financial transactions, traditional methods for assessing credit risk are proving inadequate. The research aims to establish an ML model that will offer more accurate, reliable, and efficient credit risk assessment in the MSME sector. The model’s development, implementation, and performance are critically evaluated using real credit data from various banks.

Key-Words / Index Term

Machine Learning, Credit Risk Assessment, MSMEs, Risk Management, Financial Technology.

References

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