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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM67699
Volume:
10 |
10 |
Oct 2026
Pages:
1-4
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

Information Technology
Trinity Academy of Engineering, Pune

Information Technology
Trinity Academy of Engineering, Pune

Information Technology
Trinity Academy of Engineering, Pune

Information Technology
Trinity Academy of Engineering, Pune
This paper presents ScholarAid, a digital platform designed to help NGOs manage educational fee subsidies and scholarships efficiently, transparently, and fairly. The platform supports both online student self-registration and NGO-assisted applications for students who rely on offline or paper-based processes. It includes document upload and verification, OCR-based data extraction, duplicate and fraud-risk checks, applicant priority scoring, and budget-based scholarship allocation recommendations. Priority scores are generated using factors such as family income, academic performance, special circumstances, and document-risk indicators. To ensure fairness and accountability, the system follows a human-in-the-loop model in which AI provides recommendations, while NGO staff and administrators make the final decisions. The platform also provides verification dashboards, notifications, token and cheque-distribution support, and a complete audit trail. ScholarAid aims to reduce manual errors, improve processing speed, strengthen document verification, and make scholarship distribution more accountable for NGOs and eligible students.
KEYWORDS
ScholarAid is an AI-enabled platform designed to improve the management of educational scholarships and fee subsidies by NGOs. It replaces manual paper-based processes with a centralized digital system for student registration, document upload, eligibility checking, verification, priority scoring, fund allocation, and application tracking. The platform supports both online student applications and NGO-assisted applications for students with limited internet access or digital literacy. OCR-based document processing, duplicate detection, fraud-risk checks, and budget-aware allocation recommendations help reduce errors and improve efficiency. However, AI only provides recommendations, while NGO staff and administrators retain final decision-making authority. By combining digital accessibility, AI assistance, transparent approval workflows, notifications, and audit logs, ScholarAid can help NGOs distribute educational financial support more fairly, securely, and efficiently.
1. B. J., D. K. K. R., D. P. R., R. S., and V. P. M., “Scholarship Eligibility and Application Portal,” International Research Journal of Education and Technology, vol. 7, no. 3, Mar. 2025, doi: 10.70127/irjedt.vol.7.issue03.858. 2. S. Jadhav and N. Pise, “CryptoScholarChain: Revolutionizing Scholarship Management Framework with Blockchain Technology,” International Journal of Advanced Computer Science and Applications, vol. 14, no. 8, 2023, doi: 10.14569/IJACSA.2023.0140872. 3. T.-A. Nguyen-Hoang, N. C. Hoang, P. T. Hua, M.-T. N. Thi, T.-T. Ta, T. Nguyen, K. Tan-Vo, N.-T. Dinh, and H.-T. Nguyen, “Advancing Scholarship Management: A Blockchain-Enhanced Platform With Privacy-Secure Identities and AI-Driven Recommendations,” IEEE Access, vol. 12, pp. 168060–168090, 2024, doi: 10.1109/ACCESS.2024.3486078. 4. W. D. Ahmad and A. Abu Bakar, “Classification Models for Higher Learning Scholarship Award Decisions,” Asia-Pacific Journal of Information Technology and Multimedia, vol. 7, no. 2, pp. 131–145, 2018, doi: 10.17576/apjitm-2018-0702-10. 5. M. A. Rashid, K. Deo, D. Prasad, K. Singh, S. Chand, and M. Assaf, “TEduChain: A Blockchain-Based Platform for Crowdfunding Tertiary Education,” The Knowledge Engineering Review, vol. 35, Article e27, 2020, doi: 10.1017/S0269888920000326. 6. R. Smith, “An Overview of the Tesseract OCR Engine,” in Proceedings of the Ninth International Conference on Document Analysis and Recognition, vol. 2, 2007, pp. 629–633, doi: 10.1109/ICDAR.2007.4376991. 7. National Institute of Standards and Technology, Artificial Intelligence Risk Management Framework (AI RMF 1.0), NIST AI 100-1, Gaithersburg, MD, USA, Jan. 2023, doi: 10.6028/NIST.AI.100-1.
Publication Date
10/6/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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No funding information available for this research.
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