Facilitating inclusive financial services for increasing overall social good is one of the hottest worldwide topics nowadays. Inspired by the observation that locations are somehow related to people’s credit levels, this research aims to enhance credit investigation with users’ geographic footprints. A two-stage credit investigation framework is designed, namely CreditPrint.
All experiments were run on a cloud service platform (https://www.bitahub.com/) with one GTX1080Ti (16G RAM).
Python version: 3.6
Necessary packages: listed in file requirements.txt
pip install -r requirements.txt