Cyber Crime: A Qualitative Case Study of Investment Scams in Thailand

Abstract

Investment scams have become one of the most financially damaging forms of cyber-enabled fraud in Thailand and across Southeast Asia. Much of the available evidence is survey- or administrative-data driven (e.g., Kraiwanit, 2025), which is well suited to estimating prevalence and correlates but less able to reconstruct the psychological mechanisms and interactional scripts that sustain victim commitment during the offence. This qualitative case study addresses that gap by examining (i) how perpetrators orchestrate investment deception, (ii) why individuals become victims, (iii) the multi-dimensional impacts of victimization, and (iv) practical prevention measures at individual, platform, banking, and policy levels. Using purposive sampling, we conducted in-depth semi-structured interviews with 27 key informants: 17 victim-survivors, 5 officials/scholars involved in victim assistance and prevention, and 5 individuals who reported participation in scam operations. The analysis indicates a staged scam lifecycle: exposure and grooming on social platforms; credibility engineering via ‘team leader’ narratives, testimonials, and simulated returns; onboarding to controlled apps or web platforms; escalation through top-up pressure and borrowing; and lock-in via withdrawal blocks, fabricated fees, and threats. Risk factors cluster around low investment and digital literacy, social proof from acquaintances, persuasive legitimacy cues, and time-pressure tactics that amplify fear of missing out. Impacts extend beyond financial loss to indebtedness, psychological distress, family conflict, and erosion of trust in digital services. Building on these findings and recent international evidence on industrial-scale scam centres in Southeast Asia (e.g., UNODC, 2025), we propose an integrated prevention framework with four core components: (1) recognition through scenario- and script-based education (‘cyber vaccine’); (2) containment through platform verification, advertising controls, and rapid takedown of repeat recruitment accounts; (3) transactional friction through risk-scored banking safeguards (e.g., step-up verification and cooling-off delays) at high-risk transfer moments; and (4) rapid response through simplified reporting, fast freezing/recall protocols, and victim-support pathways (Akesson et al., 2023; Global Anti-Scam Alliance & Feedzai, 2024; INTERPOL, 2025; Payment Systems Regulator, 2025; UNODC, 2025).