Design and Implementation of an Ai-Powered Credit Scoring System for Loan Approval
Student: Victor Onyenma (Project, 2025)
Department of Computer Science
Nigeria Army Institute of Tech and Environmental Studies,makurdi,benue State
Abstract
This project introduces an AI-Powered Credit Scoring System to improve financial inclusion in Nigeria, addressing the exclusion of over 38 million unbanked or underbanked adults due to traditional credit scoring limitations. Utilizing alternative data (e.g., mobile usage, utility payments, transactions), the system employs the XGBoost algorithm for real-time credit assessments. It is implemented with React.js for the interface, Python (Flask) for the backend, and PostgreSQL for data management, featuring a web platform and mobile app.
Keywords
For the full publication, please contact the author directly at: onyenmavictor4real@gmail.com
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Institutions
- Federal Polytechnic, Ado-Ekiti, Ekiti State 34
- Federal Polytechnic, Bauchi, Bauchi State 3
- Federal Polytechnic, Bida, Niger State 15
- Federal Polytechnic, Damaturu, Yobe State 12
- Federal Polytechnic, Ede, Osun State 135
- Federal Polytechnic, Idah, Kogi State 1
- Federal Polytechnic, Ilaro, Ogun State 12
- Federal Polytechnic, Ile-Oluji, Ondo State 7
- Federal Polytechnic, Kaura/Namoda, Zamfara State 3
- Federal Polytechnic, Mubi, Adamawa State 20