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.
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For the full publication, please contact the author directly at: onyenmavictor4real@gmail.com
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Institutions
- Landmark University, Omu-Aran, Kwara State 1
- Lead City University, Ibadan, Oyo State 2
- Lens Polytechnic, offa, Kwara State. 227
- Madonna University, Elele, Rivers State 22
- Madonna University, Okija, Anambra State 2
- Mcpherson University, Seriki Sotayo, Ogun State 1
- Michael and Cecilia Ibru University, Owhrode, Delta State 1
- Michael Okpara University of Agriculture, Umudike 45
- Michael Otedola Col of Primary Educ. Epe, Lagos (affl To University of Ibadan) 8
- Modibbo Adama University, Yola, Adamawa State 16