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
- The Oke-Ogun Polytechnic, Saki, Oyo State 7
- The Polytechnic, Ibadan, Oyo State 14
- THOMAS ADEWUMI UNIVERSITY, OKO-IRESE, KWARA STATE 1
- UMA UKPAI SCHOOL OF THEOLOGY, UYO, AKWA IBOM STATE (AFFL TO UNIVERSITY OF UYO) 1
- Umaru Ali Shinkafi Polytechnic, Sokoto, Sokoto State 25
- Umaru Musa Yaradua University, Katsina, Katsina State 30
- Umca, Ilorin (Affiliated To University of Ibadan), Kwara State 1
- University of Abuja, Abuja, Fct 129
- University of Africa, Toru-Orua, Bayelsa State 4
- University of Benin, Benin City, Edo State 369