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“I knew it was a scam”: Understanding the triggers for recognizing romance fraud

Cross, C. (2023) — Criminology & Public Policy

DOI: 10.1111/1745-9133.12645
Type:   Journal Article
Country:   Australia
Tags:   victim experience, platform policy, AI misuse, prevention, romance fraud, victim recognition, Scamwatch, financial loss, verification checks, third-party intervention, fraud prevention, bank intervention, prevention messaging, banks

Synopsis (AI-Generated)

This article examines the factors that contribute to the moment a romance fraud victimization becomes realized, drawing on 1015 reports submitted to Scamwatch, Australia’s online fraud reporting portal, during the period from July 2018 through July 2019. By analyzing the free-text narratives provided in each report, the study identifies five distinct trigger categories that recur across cases. The categories are further requests for money, particular characteristics of the communications, the verification checks attempted by the victim, actions taken by the offender, and instances in which a third party provides information or influence. Through this categorization, the research delineates a structured view of how romance fraud signals emerge within real-world reports. The five trigger categories collectively illuminate common pathways through which victims recognize and respond to romance fraud. Recurrent demands for funds reflect the financial bait that underpins many schemes. The descriptions of communications highlight specific patterns or features that distinguish fraudulent interactions from ordinary online contact. Verification-related steps underscore the attempts victims make to confirm information, while offender actions capture the strategic moves employed by perpetrators. Third-party communications point to external influences that can complicate discernment and delay realization. Together, these elements portray a sequence of cues and responses that help explain how, why, and when victims become aware of the deception. Policy implications drawn from these insights advocate for broader messaging strategies designed to bolster financial literacy and well-being, cyberliteracy and critical thinking, cybersecurity practices, and the promotion of respectful and healthy relationships. By integrating these areas into education and awareness initiatives, the aim is to enhance individuals’ ability to recognize romance fraud more effectively. The analysis further suggests that banks and other financial institutions occupy a pivotal role in disseminating these wider messages, using their platforms and networks to drive positive changes in recognition and prevention of romance fraud. In sum, the study argues for a multi-faceted educational approach that aligns consumer protection with broader literacy and behavioral guidance to reduce victimization risk.

Identified Gaps (AI-Generated)

Recognition of romance-fraud victimization has received less attention than motivations for fraud reporting and complaint processes. The study indicates that known warning signs are often recognized only after financial loss, leaving a need to identify ways to foreground triggers early in relationships and before a first transfer. The value and limits of verification checks also require attention as AI-generated synthetic identities may undermine image-search results.

Methods (AI-Generated)

Qualitative inductive thematic analysis of de-identified free-text Scamwatch reports. The author obtained 3,463 shareable romance/dating-fraud reports lodged July 2018–July 2019, removed duplicates and nonrelationship billing cases, and analyzed 1,015 reports involving financial loss. Narratives were read to identify recognition reasons, then consolidated into five higher-level trigger categories and further coded in NVivo 2020. The sample was 60% women; 60% reported being in Australia and 31% overseas.

Limitations (AI-Generated)

Narrative detail and length varied despite the mandatory free-text field, and complainants received no guidance on what information to include. Data rely on complainants’ memories and interpretations; the researcher could not verify narratives or loss amounts. Findings are constrained by what people chose to disclose and by researcher interpretation; direct questioning might have identified different recognition triggers. Percentages across trigger categories are indicative rather than robust quantitative estimates because cases could involve multiple factors.

Future Work (AI-Generated)

Evaluate whether prevention messages framed around financial wellbeing, cyberliteracy, cybersecurity, and healthy relationships improve earlier recognition and reduce transfers. Test proactive, coordinated bank and financial-institution communications on transfer risks, account autonomy, disclosure, and help-seeking. Assess how AI-generated synthetic identities affect the usefulness of reverse-image and online verification checks.

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AI-Generated Content Notice

The synopsis and research notes on this page were generated with AI from available publication information and, when available, the uploaded paper text. They may contain errors, omissions, or interpretation issues. Readers should follow the DOI or source link, review the original publication, and make their own judgment about the content.

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