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Al-Daoud, K. I., & Abu-AlSondos, I. A. (2025). Robust AI for Financial Fraud Detection in the GCC: A Hybrid Framework for Imbalance, Drift, and Adversarial Threats. Journal of Theoretical and Applied Electronic Commerce Research, 20, Article 121.
https://doi.org/10.3390/jtaer20020121

has been cited by the following article:

• TITLE: Combining Expert Knowledge Systems and AI Technology for Disseminating Anti-Fraud Knowledge in Rural Financial Contexts

  AUTHORS: Qingkai Zeng

  KEYWORDS: Expert Knowledge Systems (EKS), Artificial Intelligence (AI), Rural Financial Contexts, Financial Fraud

  JOURNAL NAME: Open Journal of Social Sciences, Vol.13 No.9, September 24, 2025

  ABSTRACT: Over the past decade, financial fraud has emerged as a critical challenge in rural communities, where limited financial literacy, weak digital infrastructure, and social vulnerabilities make populations particularly susceptible to deception. Traditional awareness campaigns and regulatory efforts, while significant, have struggled to keep pace with the increasing sophistication of fraudulent schemes. Against this backdrop, this study explores the integration of Expert Knowledge Systems (EKS) and Artificial Intelligence (AI) technologies to enhance the dissemination of anti-fraud knowledge in rural financial contexts. A pilot implementation was conducted in three rural communities, employing survey-based evaluations, system performance testing, and user engagement monitoring to assess both technical and social impacts. The findings found the hybrid EKS-AI framework significantly outperforms traditional methods in terms of rural fraud detection accuracy, knowledge dissemination effectiveness, and user engagement.