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The Emerging Trends of Online Romance Fraud in the Era of Artificial Intelligence

Sanjeev P. Sahni Jindal (2024) — Relation between International and National Criminal Law

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DOI: 10.51204/zbornik_umkp_24110a (opens in a new tab)

Type:   Proceedings Article
Country:   India
Tags:   AI-Enabled Fraud, Deceptive Personas, Emotional Manipulation, Fraud Detection, Law Enforcement, Measurement, Offender Tactics, Prevention, Psychology, Regulation, Romance Scams, Victim Experience, Victim Vulnerability
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Synopsis

            
The convergence of online connectivity and increasingly capable artificial intelligence has transformed how people form and maintain relationships. Against this backdrop, online romance fraud has emerged as a notable cybercrime. In this paradigm, perpetrators construct deceptive personas to present themselves as legitimate romantic partners within digital environments, targeting unsuspecting individuals. The fraudsters exploit emotional vulnerabilities, trust, and the perceived anonymity of online interactions to obtain financial gain and extract personal information. As AI algorithms become more sophisticated, bad actors gain access to tools that enable them to craft more convincing and lifelike personas, thereby raising the success rate of these schemes. The article sets out to examine the developing patterns of online romance fraud and to assess how the broader integration of AI into the digital landscape may be shaping these criminal activities. This work investigates the techniques employed by fraudsters, the psychological and emotional manipulation tactics used, and how AI reinforces deceptive practices. It also analyzes the social and economic contexts that contribute to victims’ vulnerability, highlighting the human dimensions of the crime. In addition, the study considers potential responses to this threat, including technological and regulatory measures designed to detect and prevent online romance fraud. Proposed countermeasures encompass developing AI-based fraud-detection systems, expanding public awareness, and promoting responsible online behavior among users. By exploring these elements, the research aims to illuminate how fraudsters operate and how societies might respond to reduce harm. This study relies on a synthesis of existing literature, real-world case analyses, and insights drawn from professionals in cybersecurity and AI. Through a comprehensive review, the article endeavors to present a balanced, evidence-backed account of online romance fraud and its relationship to AI innovations, offering implications for policy, practice, and further inquiry.

          

        
                  

            
Identified Gaps

            
No explicit research gap is stated. The paper frames a need to understand emerging AI-enabled romance-fraud trends, offender techniques, manipulation tactics, victim vulnerability factors, and effective technological and regulatory countermeasures.

          

        
                  

            
Methods

            
The paper states that it draws on a comprehensive analysis of existing literature, real-world case studies, and insights from cybersecurity and AI experts. The available text describes a broad, primarily qualitative and descriptive examination of AI-enabled online romance fraud.

          

        
                  

            
Limitations

            
The supplied text is limited to the abstract and does not report a search strategy, case-selection procedure, expert-sampling approach, analytic framework, or empirical results. Consequently, the evidentiary basis, reproducibility, and strength of the paper's conclusions cannot be assessed from the available material.

          

        
                  

            
Future Work

            
Develop AI-driven fraud-detection systems, strengthen technological and regulatory responses, raise public awareness, and encourage responsible online behaviour. These measures are presented as ways to detect and prevent evolving online romance fraud.

          

              

    
    

        
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