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Romance Scam Statistics 2024-2026: verified, source-attributed figures from FBI IC3, FTC, City of London Police, Cybermalveillance.gouv.fr, GASA and Chainalysis (Baromètre 2026 des arnaques sentimentales)

Valentin Le Normand (2026)

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DOI: 10.5281/zenodo.22284080 (opens in a new tab)

Country:   United Kingdom
Tags:   AI-Enabled Fraud, Cross Cultural, Cross National Comparison, Cryptocurrency, Law Enforcement, Money Mules, Pig Butchering, Prevention, Reported Losses, Romance Fraud Statistics, Underreporting, Victim Demographics, Victim Experience
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Synopsis

            
This publication compiles official figures from government and industry sources to describe romance scam activity in 2024–2026, focusing on reported losses and case counts in the United States, United Kingdom, Australia, Canada, and other contexts. Its stated purpose is to present a consolidated, source-attributed snapshot of the landscape, highlighting how losses are evolving, how victims report data, and how evolving techniques affect detection and policy responses. The approach centers on summarizing data from agencies such as the FBI IC3, the FTC, the City of London Police, and counterpart bodies, while noting that most victims do not report. The work explicitly treats reported figures as undercounts and emphasizes the gap between reported and actual victimization. Principal findings include a sustained rise in reported romance-scam losses, with US figures showing a jump to $929 million in 2025 per the FBI IC3, and the FTC reporting $1.16 billion in nine months of 2025. UK data indicate more than £102 million lost in 2025, with the average loss approaching £9,500. A notable shift toward cryptocurrency and pig butchering investment scams is described, alongside indicators that AI-enabled methods (photos, chatbots, deepfakes, voice cloning) are increasing scam scale and sophistication. The report cautions that traditional statistics undercount true losses due to under-reporting and reclassification of cases, and it notes policy and enforcement implications, including cross-border challenges and evolving banking safeguards. Limitations highlighted include reliance on reported data, methodological differences across agencies, and the ongoing difficulty of capturing the full scope of global romance fraud. The synthesis remains grounded in the cited sources and avoids unsupported extrapolation.

          

        
                  

            
Identified Gaps

            
Reported figures substantially understate prevalence and losses because many victims do not report. No recent study reliably quantifies the reporting rate. Classification differences between agencies and the separation of investment fraud from romance fraud hinder comparison and obscure the scale of romance-initiated pig-butchering schemes.

          

        
                  

            
Methods

            
This is a descriptive cross-national compilation of reported romance-fraud statistics and trends. It synthesizes figures attributed to government, law-enforcement, industry, and anti-scam sources, including the FTC, FBI IC3, ACCC, City of London Police, CAFC, Global Anti-Scam Alliance, and Chainalysis. It compares reported losses, complaints, demographics, payment methods, platforms, and emerging tactics across years and jurisdictions.

          

        
                  

            
Limitations

            
The article relies on reported cases, while it states that a large majority of victims do not report. Agency reporting systems and offense categories differ, making figures non-comparable in some cases. Romance-initiated investment fraud may be counted as investment fraud rather than romance fraud. Some claims are presented as summarized source findings without underlying methodological detail in the supplied text.

          

        
                  

            
Future Work

            
Develop reliable estimates of romance-scam reporting rates and total victimization. Improve measurement of romance-initiated investment fraud, which may be classified separately from traditional romance fraud. Strengthen data collection so governments and platforms can make policy decisions using more complete evidence.

          

              

    
    

        
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