Measuring Online Ponzi Schemes: Recruitment, Ecosystem Overlaps and Cash-Out Mechanisms Across Academics, Industry, and Regulators

Abstract

This dissertation compares how academic, regulatory, industry, and grey literature sources document online Ponzi schemes as operational systems. It studies nine major schemes spanning varied architectures (smart-contract MLM, exchanges, "cloud mining," and algorithmic-trading fronts) and analyses persuasion lures, recruitment channels, and ecosystem overlaps with adjacent frauds. Verbatim claims were systematically extracted from publicly available documents and coded using a reproducible framework. The mixed-methods design prioritises cross-source comparability and quantifies documentation bias across source families.