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Credit Risk Assessment in P2P Lending Using LightGBM and Particle Swarm Optimization

Credit risk evaluation is a vital task in the P2P Lending platform. An effective credit risk assessment method in a P2P lending platform can significantly influence investors' decisions. Machine learning algorithm such as LightGBM can be used to evaluate credit risk. However, the results in ev...

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Main Authors: Yosza Dasril a, Yosza Dasril a, Muslim, Much Aziz, Al Hakim, M. Faris, Jumanto, Jumanto, Budi Prasetiyo, Budi Prasetiyo
Format: Article
Language:English
Published: unipdu 2023
Subjects:
T Technology (General)
Online Access:http://eprints.uthm.edu.my/9376/1/J15898_e63681e26a66ff10c518c7ea4a580069.pdf
http://eprints.uthm.edu.my/9376/
http://doi.org/10.26594/register.v9i1.3060
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spelling my.uthm.eprints.93762023-07-30T07:09:57Z http://eprints.uthm.edu.my/9376/ Credit Risk Assessment in P2P Lending Using LightGBM and Particle Swarm Optimization Yosza Dasril a, Yosza Dasril a Muslim, Much Aziz Al Hakim, M. Faris Jumanto, Jumanto Budi Prasetiyo, Budi Prasetiyo T Technology (General) Credit risk evaluation is a vital task in the P2P Lending platform. An effective credit risk assessment method in a P2P lending platform can significantly influence investors' decisions. Machine learning algorithm such as LightGBM can be used to evaluate credit risk. However, the results in evaluating P2P lending need to be improved. This research aims to improve the accuracy of the LightGBM algorithm by combining it with the Particle Swarm Optimization (PSO) algorithm. This research is novel as it combines LightGBM with PSO for large data from the Lending Club Dataset, which can be accessed on Kaggle.com. The highest accuracy also presented satisfactory results with 98.094% accuracy, 90.514% Recall, and 97.754% NPV, respectively. The combination of LightGBM and PSO has resulted in better outcome. unipdu 2023 Article PeerReviewed text en http://eprints.uthm.edu.my/9376/1/J15898_e63681e26a66ff10c518c7ea4a580069.pdf Yosza Dasril a, Yosza Dasril a and Muslim, Much Aziz and Al Hakim, M. Faris and Jumanto, Jumanto and Budi Prasetiyo, Budi Prasetiyo (2023) Credit Risk Assessment in P2P Lending Using LightGBM and Particle Swarm Optimization. Jurnal Ilmiah Teknologi Sistem Informasi, 9 (1). pp. 18-28. ISSN 2502-3357 ( http://doi.org/10.26594/register.v9i1.3060
institution Universiti Tun Hussein Onn Malaysia
building UTHM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tun Hussein Onn Malaysia
content_source UTHM Institutional Repository
url_provider http://eprints.uthm.edu.my/
language English
topic T Technology (General)
spellingShingle T Technology (General)
Yosza Dasril a, Yosza Dasril a
Muslim, Much Aziz
Al Hakim, M. Faris
Jumanto, Jumanto
Budi Prasetiyo, Budi Prasetiyo
Credit Risk Assessment in P2P Lending Using LightGBM and Particle Swarm Optimization
description Credit risk evaluation is a vital task in the P2P Lending platform. An effective credit risk assessment method in a P2P lending platform can significantly influence investors' decisions. Machine learning algorithm such as LightGBM can be used to evaluate credit risk. However, the results in evaluating P2P lending need to be improved. This research aims to improve the accuracy of the LightGBM algorithm by combining it with the Particle Swarm Optimization (PSO) algorithm. This research is novel as it combines LightGBM with PSO for large data from the Lending Club Dataset, which can be accessed on Kaggle.com. The highest accuracy also presented satisfactory results with 98.094% accuracy, 90.514% Recall, and 97.754% NPV, respectively. The combination of LightGBM and PSO has resulted in better outcome.
format Article
author Yosza Dasril a, Yosza Dasril a
Muslim, Much Aziz
Al Hakim, M. Faris
Jumanto, Jumanto
Budi Prasetiyo, Budi Prasetiyo
author_facet Yosza Dasril a, Yosza Dasril a
Muslim, Much Aziz
Al Hakim, M. Faris
Jumanto, Jumanto
Budi Prasetiyo, Budi Prasetiyo
author_sort Yosza Dasril a, Yosza Dasril a
title Credit Risk Assessment in P2P Lending Using LightGBM and Particle Swarm Optimization
title_short Credit Risk Assessment in P2P Lending Using LightGBM and Particle Swarm Optimization
title_full Credit Risk Assessment in P2P Lending Using LightGBM and Particle Swarm Optimization
title_fullStr Credit Risk Assessment in P2P Lending Using LightGBM and Particle Swarm Optimization
title_full_unstemmed Credit Risk Assessment in P2P Lending Using LightGBM and Particle Swarm Optimization
title_sort credit risk assessment in p2p lending using lightgbm and particle swarm optimization
publisher unipdu
publishDate 2023
url http://eprints.uthm.edu.my/9376/1/J15898_e63681e26a66ff10c518c7ea4a580069.pdf
http://eprints.uthm.edu.my/9376/
http://doi.org/10.26594/register.v9i1.3060
_version_ 1773545890994192384
score 13.211869

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