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Topics
Peer-to-peer Lending (opens in a new tab)Borrowers (opens in a new tab)Loan (opens in a new tab)Credit - Risk Evaluation (opens in a new tab)Supervised Learning (opens in a new tab)Fuzzy Set Theory (opens in a new tab)Machine Learning (opens in a new tab)
15 Citations
- Fadhlurrahman Akbar NasutionSiti SaadahPrasti Eko Yunanto
- 2023
Computer Science, Business
Jurnal RESTI (Rekayasa Sistem dan Teknologi…
A system was built using the CatBoost method to detect credit risk for minimizing P2P lending credit risk and the best result regard to scenario 2 with a data splitting of 90:10 was caused by the result of AUC value’s 0.80329.
- Baah AlexanderZhong-ming TanGuoping DingA. H. NtarmahA. Kwabena
- 2020
Computer Science, Business
Business and Economic Research
This article compared two learning algorithms – Logistic regression and Artificial Neural Network to classify borrowers based on loan repayment schedule and revealed that both approaches were robust in classifying late borrowers with logistic regression being 0.02% more robust than Neural Network.
- PDF
- Aleksandra Wójcicka-WójtowiczKrzysztof Piasecki
- 2021
Mathematics, Business
Mathematics
The paper presents evaluation scales of imprecise phrases commonly used during the process of credit risk assessment based on experts’ preferences and uses a scoring function determined with the use of an adapted Simple Additive Weighting (SAW) method.
- Aleksandra Wójcicka-WójtowiczKrzysztof Piasecki
- 2019
Business, Mathematics
SSRN Electronic Journal
Banks faced many difficulties related to lax credit standards. The effective management of credit risk is a critical component of a comprehensive approach to risk management and it should maintain…
- 4
- Fooz AlghamdiNora Alkhamees
- 2023
Computer Science, Business
International Journal of Advanced Computer…
The Default Borrowers Detection Model (DefBDet) is a novel model, it can predict a loan status based on a multi-classification bases rather than a binary class bases, so that special conditions are assigned before loan being approved.
- Ryan Randy SuryonoB. PurwandariI. Budi
- 2019
Economics, Business
Procedia Computer Science
- 77
- Siddharth PandeyRajeev Kumar
- 2021
Business, Law
Individuals and corporations borrow and lend to each other. China has developed with most financial intermediaries. Still, there is a systemic risk involved in managing this business. This risk…
- Susana BernardinoJ. Freitas SantosSilvie Oliveira
- 2021
Business, Economics
A problem faced by nascent entrepreneurs is to attract outside capital to finance a new venture. A new promising funding mechanism created outside the banking system is crowdfunding (CF). The…
- Susana BernardinoJ. Freitas SantosSilvie Oliveira
- 2021
Business, Computer Science
Cuadernos de Gestión
The findings show that social media and e-WOM strategies play a critical role and have a positive significant impact on a CF campaign.
- 5
- PDF
- Ryan Randy SuryonoEkawati MarlinaMardiana PurwaningsihD. I. SensuseMochammad Arief Hcrmawan Sutoyo
- 2019
Business, Computer Science
2019 International Conference on Computer Science…
The proposed P2P Lending for Tourism platform in the Indonesian context consists of business process and application, which are adopted from the p2p lending and combine with e-commerce.
- 4
44 References
- Yu JinYu Zhu
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Business, Computer Science
2015 Fifth International Conference on…
This study uses data from the Lending Club to explore the characteristics of loan and its applicant and uses random forest to do the feature selection in the modeling phase, and shows that the term of loan, annual income, the amount of loans, debt-to-income ratio, credit grade and revolving line utilization play an important role in loan defaults.
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- Ajay ByanjankarM. HeikkiläJ. Mezei
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Business, Computer Science
2015 IEEE Symposium Series on Computational…
A credit scoring model using artificial neural networks in classifying peer-to-peer loan applications into default and non-default groups is proposed and results indicate that the neural network-basedcredit scoring model performs effectively in screening default applications.
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Business, Computer Science
2012 International Conference on Data Science…
A multi relational Bayesian classification method is used to predict the default probabilities of borrowers, where the input attributes consists of both core credit and social network information.
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Business, Computer Science
Experimental studies using real world data sets have demonstrated that the classification and regression trees and neural networks outperform the traditional credit scoring models in terms of predictive accuracy and type II errors.
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Computer Science, Economics
Expert Syst. Appl.
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- Riza EmekterYanbin TuB. JirasakuldechMin Lu
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Economics, Business
Online Peer-to-Peer (P2P) lending has emerged recently. This micro loan market could offer certain benefits to both borrowers and lenders. Using data from the Lending Club, which is one of the…
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- C. Serrano-CincaB. Gutiérrez-Nieto
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Economics, Business
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Computer Science, Business
IEEE Transactions on Systems, Man, and…
This paper presents the current achievements and limitations associated with the development of bankruptcy-prediction and credit-scoring models employing machine learning, and provides suggestions for future research.
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- Xu-chen LinXiaolong LiZhongyu Zheng
- 2017
Economics, Business
ABSTRACT Recent years have witnessed the popularity of online peer-to-peer lending, which allows individuals to borrow from and lend to each other on an Internet-based platform. Using data from a…
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- D. JiangXiaoqing Li
- 2017
Computer Science, Business
Based on BP neural network, P2P network platform credit risk evaluation model were built to train and simulate and the results show that the final data generated by these models are of practical value.
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