Spatiotemporal Integration of Mobile, Satellite, and Public Geospatial Data for Enhanced Credit Scoring

Spatiotemporal Integration of Mobile, Satellite, and Public Geospatial Data for Enhanced Credit Scoring

Credit scoring of financially excluded persons is challenging for financial institutions because of a lack of financial data and long physical distances, which hamper data collection. The remote collection of alternative data has the potential to overcome these challenges, enabling credit access for...

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Bibliographic Details
Main Authors: Naomi Simumba, Suguru Okami, Akira Kodaka, Naohiko Kohtake
Format: Article
Language:English
Published: MDPI AG 2021-03-01
Series:Symmetry
Subjects:
credit scoring
satellite data
machine learning
ensemble learning
financial inclusion
Online Access:https://www.mdpi.com/2073-8994/13/4/575

Internet

https://www.mdpi.com/2073-8994/13/4/575

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