CYBER FRAUD: FAKE PROFILES DRIVE INSTANT LOAN SCAMS TARGETING INDIA'S INFORMAL WORKERS

Abstract

The surge in digital lending in India, propelled by UPI and post-COVID financial distress, has spawned a pernicious ecosystem of instant loan app frauds, with losses exceeding Rs 22,845 crore in 2024 alone (NCRB, 2025). These scams disproportionately target informal sector workers daily-wage earners, domestic help, and vendors through fake social media profiles that masquerade as empathetic lenders. Despite regulatory interventions like RBI's 2025 Digital Lending Directions, empirical voids persist: no integrated studies explore the supply-side (perpetrator tactics) and demand-side (victim vulnerabilities) nexus in this unorganized workforce, where 90% of India's labor force resides.

This study addresses this gap via four objectives: mapping victimization patterns, dissecting fake profile operations, assessing psychological-economic harms, evaluating regulatory efficacy, and proposing interventions. Four research questions probe predictors, trust-building mechanisms, interplay dynamics, and policy gaps. Employing a sequential explanatory mixed-methods design, primary data encompassed a survey of 432 workers across five cities, 35 victim interviews, 12 informant sessions with perpetrators/police, and digital ethnography of 8 fake profiles.

Key findings reveal 55.1% victimization prevalence, skewed toward low-income females (60.5%) with <10th-grade education (68.5%), via WhatsApp lures (50%) and usurious rates (1,607% p.a.). Modus operandi involved AI-groomed profiles and recovery via data/nude morphing (59.7%), yielding socio-economic fallout: 28% suicidal ideation, 35% family breakdowns. Theoretically, findings extend Routine Activity Theory with a "predation loop" for cyber lending. Policy-wise, immediate app bans and KYC mandates, medium-term literacy modules, and long-term platform liabilities are urged to recalibrate financial inclusion.