Skip to main content

Exploring the roles played by trust and technology in the online investment fraud victimisation process

Anderson, Matthew ; March, Evita ; Land, Lesley ; Boshuijzen-van Burken, Christine (2024) — Journal of Criminology

View Original Source (opens in a new tab)

DOI: 10.1177/26338076241248176 (opens in a new tab)

Type:   Journal Article
Country:   Global
Tags:   AI-Enabled Fraud, Digital Literacy, Online Guardianship, Online Investment Fraud, Pig Butchering Scams, Rich Media, Romance Initiated Investment Scams, Trust Building, Victim Experience, Victim Self Reports
Citation tools
Download RIS Download BibTeX 


              
              

            

          

        


      

      

    

        
Transparency

        
Evidence and review status

        
This page contains AI-generated content. No human content review or subject-matter-expert review is recorded.

    


    

                    

                
Source basis

                

                    Downloaded PDF
                

            

                    

                
AI-generated page content

                

                    Yes
                

            

                    

                
Automated checks

                

                    Passed
                

            

                    

                
Administrative approval

                

                    Yes
                

            

                    

                
Human content review

                

                    Not recorded
                

            

                    

                
Subject-matter-expert review

                

                    Not recorded
                

            

            


    

        
            How this was prepared
        
        

                            

                    
Source basis

                    

                    
RSRC downloaded and privately stored a copy of the paper for internal analysis. The PDF is not offered to viewers from this page.


                                            
    
                                                            
  • 
                                    PDF added to RSRC:
                                    
                                
    • 
                                                    

                    
                                        

                

                            

                    
AI-generated page content

                    

                    
AI-generated research notes displayed on this page: Synopsis, Identified gaps, Methods, Limitations, Future work. The paper itself is not described as AI-generated.


                                            
    
                                                            
  • 
                                    Document analysis recorded:
                                    
                                
    • 
                                                            
  • 
                                    Synopsis generation recorded:
                                    
                                
    • 
                                                            
  • 
                                    Page record updated:
                                    
                                
    • 
                                                    

                    
                                        

                

                            

                    
Automated checks

                    

                    
The current, source-bound synopsis passed the recorded versioned publication checks.


                                            
    
                                                            
  • 
                                    Checks completed:
                                    
                                
    • 
                                                    

                    
                                            

                            
                                View passed checks (3)
                            
                            
    
                                                                    
  • Length, completeness, repetition, refusal, boilerplate, and active-markup screening
    • 
                                                                    
  • Numerical claims checked against the available source text
    • 
                                                                    
  • English-source lexical grounding check
    • 
                                                            

                        

                                        

                

                            

                    
Administrative approval

                    

                    
An authenticated administrator approved the bibliographic record for public Library display. This is not a review of every research claim.


                                            
    
                                                            
  • 
                                    Approved for public display:
                                    
                                
    • 
                                                    

                    
                                        

                

                            

                    
Human content review

                    

                    
No human review is recorded for the AI-generated content displayed on this page.


                    
                                        

                

                            

                    
Subject-matter-expert review

                    

                    
RSRC has not recorded review of this content by a subject-matter or methods expert.


                    
                                        

                

                    

    


    

        Review-state definitions

        Found a possible error?
        Request a correction.
    



    



              

        
                  

            
Synopsis

            
This study analyzes how trust and technology contribute to victimisation in online investment fraud. It draws on 200 self‑reported victim testimonies collected from online forums and analyzes them with inductive thematic analysis to explore how trusting relationships and digital tools facilitate scams. The authors aim to extend understanding of how trust is formed and maintained across online interactions and how various technologies shape victims’ perceptions of legitimacy and risk. Key findings describe multiple mechanisms by which scammers cultivate trust. Scammers use rich media, interactive websites, and responsive support channels to create the impression of legitimacy and ongoing profitability. In many cases, victims reported engaging in online relationships with scammers for extended periods before investment discussions began, a pattern reminiscent of grooming in romance scams. When relationships progressed to investment, victims often perceived legitimate investment processes through detailed information packages and staged evidence of gains, which reinforced trust and encouraged further funding. The study also notes that victims sometimes attempted to protect themselves with digital tools, but such safeguards were often ineffective due to limited digital literacy or inadequate safeguards. The authors discuss theoretical framing in terms of hyperpersonal computer‑mediated communication and media richness, and they acknowledge limitations related to representativeness and the types of fraud in the dataset. They suggest directions for future work, including examining guardianship online, the persuasive messaging of scams, and educational interventions that target general awareness of common scam tactics rather than specific schemes. The article concludes that wealth of interactive content and cross‑channel communication play central roles in online investment fraud victimisation.

          

        
                  

            
Identified Gaps

            
The mechanisms by which trust forms and is maintained through technological communication in online investment fraud are underexamined. The dataset contained little evidence about persuasive content that first draws victims into scams. Evidence is also limited on whether scammers deliberately select communication channels to build trust, on individual and social differences in responses to rich media, and on the nature and effectiveness of capable online guardianship.

          

        
                  

            
Methods

            
The study inductively thematically analyzed 200 anonymous, publicly available victim self-reports of online investment fraud from the U.S. FTC Consumer Information Blog and Reddit r/Scams, collected between July and September 2021. Cases were purposively selected for an identifiable victim, a qualifying investment scam, and sufficient detail. NVivo supported coding. Three additional coders independently coded a random 10% sample using a codebook; Fleiss’ kappa after theme consolidation was 0.621, with 74.19% agreement.

          

        
                  

            
Limitations

            
The self-report data from two websites are not fully representative of online investment fraud. The sample lacked accounts of more complex fraud, such as Ponzi schemes; this may reflect either lower prevalence or different reporting patterns. Because data were collected in 2021, they may not represent current investor attitudes, newer scam forms, or emerging technologies such as AI tools. Sparse demographic detail also prevented deeper analysis of demographic and social risk factors.

          

        
                  

            
Future Work

            
Study whether capable online guardianship exists in online investing spaces and how effectively it moderates offender–victim interactions. Interview online investment fraudsters to include the absent offender perspective. Analyze persuasive messaging in investment-fraud advertising, including experiments that vary persuasive strategies. Research safety-by-design measures for dating platforms and regularly assess prevention measures as scams and technologies change.

          

              

    
    

        
Related Research Insights

        

            See how this publication connects to RSRC's living evidence syntheses through current citations and research-topic mapping.