Advanced International Journal of Multidisciplinary Research

E-ISSN: 2584-0487

An Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

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Volume 3 Issue 6
November-December 2025

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Designing Secure and User-Friendly Interfaces for Child Support Systems: Enhancing Fraud Detection and Data Integrity

Author(s) Gopi Chand Vegineni
Country USA
Abstract Both in the part of integrity, meaning that proper procedures are followed, and in terms of the manner in which child support is disbursed, the issue is very sensitive because it is part of a country’s social welfare system. Nevertheless, areas such as fraud, data manipulation, and incorrect disbursement are still affecting organisations. In this paper, the author aims to implement a machine-learning solution to identify fraud and maintain data credibility in child support systems. Using the approaches to supervised & unsupervised learning, we make a prediction and detect faults in child support transactions. We analyze a number of ML algorithms such as DTree, Support Vector Machine, Neural nets, and ensembles. Demographic data include beneficiaries’ age, gender, and income, while financial transactions cover any payments and support orders given by the court and beneficiaries’ payment records. The best approach to choosing a model for a prominent social media platform is to design our system to be fully explainable and interpretable. As stated earlier, the proposed ensemble model yields high accuracy of 96.3% in fraud detection while enhancing the reliability of analysed data. Thus, the above strategy can be used as a general model for public organizations to increase transparency and decrease corrupt practices in childcare support systems.
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Published In Volume 2, Issue 3, May-June 2024
Published On 2024-06-06
Cite This Designing Secure and User-Friendly Interfaces for Child Support Systems: Enhancing Fraud Detection and Data Integrity - Gopi Chand Vegineni - AIJMR Volume 2, Issue 3, May-June 2024.
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