Using Network Features for Credit Scoring in MicroFinance: Extended Abstract

• Type: Article in International Conference Proceedings Book
• Date: 2020

Authors

Paraiso, P (Author) Other; Ruiz, S (Author) Other; Gomes, P (Author) Other; Rodrigues, L (Author) Other; João Gama (Author) FEP

Conference proceedings International

Title: 7th IEEE International Conference on Data Science and Advanced Analytics, DSAA 2020, Sydney, Australia, October 6-9, 2020

Pages: 783-784

Indexing

ISI Web of Knowledge - 1 Citation

Scopus - 1 Citation

Other information

Authenticus ID: P-00T-7RX

DOI: 10.1109/dsaa49011.2020.00115

Abstract (EN): This paper uses non-traditional data, from a MicroFinance Institution (MFI), in a Credit Scoring loan classification problem and addresses a common problem in emerging markets of the lack of a verifiable customers' credit history. We perform a set of experiments to define a baseline model and prove the relevance of node embedding features, in credit scoring models, using a real world dataset. © 2020 IEEE.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 2