Credit Quality Evaluation on a Dynamic Network with Latent Variables-Reference-Cited by-同舟云学术

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Credit Quality Evaluation on a Dynamic Network with Latent Variables

Published:2023-09-15 Issue:6 Volume:4 Page:
ISSN:2661-8907
Container-title:SN Computer Science
language:en
Short-container-title:SN COMPUT. SCI.

Author:

Sewe Stanley^ORCID,Ngare Philip,Weke Patrick

Funder

African Union

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Computer Networks and Communications,Computer Graphics and Computer-Aided Design,Computational Theory and Mathematics,Artificial Intelligence,General Computer Science

Link

https://link.springer.com/content/pdf/10.1007/s42979-023-02192-3.pdf

Reference26 articles.

1. Björkegren D and Grissen D. Behavior revealed in mobile phone usage predicts loan repayment. arXiv preprint. 2017; arXiv:1712.05840.

2. Crook JN, Edelman DB, Thomas LC. Recent developments in consumer credit risk assessment. Eur J Oper Res. 2007;183:1447–65.

3. Dempster AP, Laird NM, Rubin DB. Maximum likelihood from incomplete data via the EM algorithm. J Roy Stat Soc B. 1977;39:1–38.

4. Elliott RJ, Filinkov A. A self tuning model for risk estimation. Expert Syst Appl. 2008;34:1692–7.

5. Francis E and Blumenstock J, Robinson J. Digital credit: a snapshot of the current landscape and open research questions, CEGA White Paper (2017).

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