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Cognitive Companion AI for Vulnerable Demographics: Fraud Prevention and Real-Time Protection for the Elderly

Mithilesh Ramaswamy, Email: rmith87@gmail.com

Abstract

Online fraud is a growing threat, particularly for demographics such as the elderly, who are more susceptible to manipulative tactics and phishing attempts. This paper introduces "Cognitive Companion AI," a novel Agentic AI system designed to provide real-time fraud prevention and education for vulnerable users. Leveraging advanced natural language processing (NLP), emotion-aware analytics, contextual threat recognition, and human-in-the-loop monitoring, the Cognitive Companion analyzes online interactions for fraudulent indicators and provides live alerts with actionable explanations. The framework includes behavioral modeling and adaptive learning algorithms to stay ahead of evolving fraud tactics. The inclusion of human oversight enhances trust and ensures a failsafe mechanism for particularly high-risk scenarios, such as safeguarding elderly users. This system aims to empower users with protection and awareness, significantly reducing the risk of fraud while maintaining transparency and accessibility. This paper explores the framework, use cases, and human-in-the-loop mechanisms and addresses challenges in its implementation.

Keywords

Cognitive Companion AI, online fraud prevention, real-time threat detection, vulnerable demographics, natural language processing, explainable AI, human-in-the-loop systems, digital guardianship.