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Old techniques, new technologies: Exploring patterns from scammers that commit financial fraud via cryptocurrency

Dulisse, Brandon ; Fitch, Chivon ; Denis, Jaden ; Connealy, Nathan (2025) — Journal of Economic Criminology

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DOI: 10.1016/j.jeconc.2025.100178 (opens in a new tab)

Type:   Journal Article
Country:   United States
Tags:   Cryptocurrency Fraud, Financial Loss, Fraudulent Trading Platforms, Pig Butchering, Repeat Victimization, Romance Scams, Scam Trackers, Social Media Scams
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Synopsis

            
This publication investigates cryptocurrency-related scams by analyzing complaint data from two state scam trackers—California’s DFPI and Wisconsin’s DFI—launched in 2023 and 2024, respectively. The study treats crypto fraud as a convergence of traditional online deception and new digital platforms, aiming to describe how scammers contact victims, identify what scam types are most prevalent and costly, and assess whether higher victimization frequency relates to greater losses. The authors code narrative complaint descriptions to extract patterns across social media channels, messaging apps, and other contact points, and to categorize scam “titles” used to establish legitimacy. Key findings indicate that two scam types dominate crypto fraud: fraudulent trading platforms and pig butcher­ing scams, which together account for a substantial share of cases. Victims are primarily reached through online messaging apps and social media, with titles such as authority figures (professors, coaches, mentors) and financial professionals used to gain trust; family or known acquaintances also feature prominently in some schemes. The analysis shows that multiple victimizations tend to be associated with larger total losses, and that pig‑butchering scams, in particular, yield the highest average losses compared with several other scam families. The study acknowledges several limitations: the data come from two states and rely on self‑reported consumer complaints that are not systematically verified for accuracy; incomplete narratives and missing data constrain certain analyses; and results are exploratory rather than generalizable. Despite these caveats, the work contributes descriptive insight into how social media, cryptotrading platforms, and romantic or familiar tropes facilitate crypto fraud, with implications for public education, consumer awareness, and platform‑level prevention efforts.

          

        
                  

            
Identified Gaps

            
The study identifies limited knowledge about the initial point of contact between cryptocurrency-fraud victims and offenders. It also notes gaps in scam-tracker data, including structured details on offender introductions, communication frequency and style, contact initiation, trading platforms, number of requests or victimizations, and total losses. The authors call for more consistent and robust information on victims, offenders, and scams across jurisdictions.

          

        
                  

            
Methods

            
The study conducted exploratory descriptive and regression analyses of 291 self-reported consumer complaints from California's cryptocurrency scam tracker (n=260) and Wisconsin's investment scam tracker (n=31). Researchers coded complaint narratives for contact channel, implied victim gender, offender titles, scam type, reported losses, and single versus multiple victimizations. They compared loss amounts across scam types and offender-title categories and used regression to test whether repeat victimization predicted total loss.

          

        
                  

            
Limitations

            
The sample is limited to publicly accessible trackers in California and Wisconsin, so complaints may not represent all cryptocurrency fraud. Reports could potentially originate outside those states. Tracker complaints were checked for completeness but not accuracy, and the authors lacked control over secondary-data measures. Some narratives were vague, making scam classification difficult. Missing data were notable for implied victim gender and loss amounts; findings are exploratory and limited to victim-provided information.

          

        
                  

            
Future Work

            
Future research should examine how scammers find targets and use communication techniques, romance, financial success, blackmail, or desperation to deceive them. Studies could integrate additional data, conduct detailed case studies of victim disclosures, and examine points of monetary transfer. Researchers should also assess how technologies such as social media, messaging, cryptocurrency, and trading platforms create advantages for offenders and make legitimate opportunities difficult to distinguish from fraud.

          

              

    
    

        
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