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The Deceptive Allure: Understanding and Combating Cryptocurrency Pig Butchering Scams

Krause, David (2025) — SSRN Electronic Journal

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DOI: 10.2139/ssrn.5233661 (opens in a new tab)

Type:   Journal Article
Country:   Global
Tags:   AI Fraud Detection, Cfpb, Consumer Protection, Cross Border Enforcement, Cross Border Fraud, Cryptocurrency, Cryptocurrency Fraud, Investment Fraud, Pig Butchering, Romance Scams
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Synopsis

            
The paper uses a descriptive case study of a Wisconsin cryptocurrency-scam victim who lost $85,000, alongside a comparative analysis of consumer-protection and cryptocurrency regulatory frameworks in the United States and other jurisdictions. It synthesizes cited reports, policy sources, and documented scam examples to describe pig-butchering mechanics, harms, regulatory weaknesses, and prevention recommendations. The paper recommends recognizing requests for upfront fees or taxes to release earnings as a warning sign of fraud. The Wisconsin victim experienced severe emotional distress, insomnia, and profound erosion of trust. The analysis appears primarily descriptive and source-synthesis based, relying on one detailed Wisconsin case study and comparative regulatory discussion rather than systematic victim, offender, or platform data.

          

        
                  

            
Identified Gaps

            
The paper identifies limited evidence on how to optimize AI fraud detection without excessive false positives or bias. It also identifies unresolved questions about how regulatory fragmentation impairs enforcement against cross-border fraud, how emerging technologies are weaponized by scammers, and the ethics of aggressive automated prevention measures. Its discussion further characterizes current U.S. protections as fragmented and reactive.

          

        
                  

            
Methods

            
The paper uses a descriptive case study of a Wisconsin cryptocurrency-scam victim who lost $85,000, alongside a comparative analysis of consumer-protection and cryptocurrency regulatory frameworks in the United States and other jurisdictions. It synthesizes cited reports, policy sources, and documented scam examples to describe pig-butchering mechanics, harms, regulatory weaknesses, and prevention recommendations.

          

        
                  

            
Limitations

            
The analysis appears primarily descriptive and source-synthesis based, relying on one detailed Wisconsin case study and comparative regulatory discussion rather than systematic victim, offender, or platform data. Consequently, claims about scam prevalence, victim experiences, and the effectiveness of countermeasures are not empirically tested within the paper. The paper itself calls for further research on detection efficacy, regulatory fragmentation, emerging technologies, and automated-prevention ethics.

          

        
                  

            
Future Work

            
Evaluate AI-driven fraud detection models for emerging scams, including false-positive and bias risks; examine how domestic and international regulatory fragmentation enables cross-border fraud; study criminal use of deepfakes, synthetic identities, and DeFi; and assess ethical implications when automated financial systems flag, delay, or deny transactions.

          

              

    
    

        
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