DIGITAL MECHANISM FOR BENEFICIARY IDENTIFICATION UNDER GRANT-IN-AID (GIA) COMPONENT

Abstract

The effective implementation of government welfare schemes largely depends on the accurate identification of eligible beneficiaries. Grant-in-Aid (GIA) programs are designed to provide financial assistance to individuals and institutions; however, traditional beneficiary identification mechanisms often suffer from inefficiencies, lack of transparency, and susceptibility to fraudulent practices.This paper presents a comprehensive digital framework for beneficiary identification that integrates centralized data management, automated verification, and intelligent decision- making techniques. The proposed system incorporates data preprocessing, feature extraction, and probabilistic classification methods to enhance accuracy in eligibility determination. Additionally, the framework employs secure identity verification and multi-source data validation to ensure reliability and accountability. Extensive evaluation demonstrates that the proposed system significantly reduces processing time, minimizes administrative overhead, and improves the accuracy of beneficiary selection. The framework offers a scalable and adaptable solution for modern e - governance systems, enabling transparent and efficient distribution of public funds while reducing the risk of fraud and duplication