An Anti-Fraud Policy: A Theoretical Framework for a Prosperity Tripod of Massive Data, Blockchain, and AI

The authors’ aspiration was to learn—and focus on policy against fraud—leading to the sustainably growing societal illnesses of dishonesty, fraud, pessimism, and divisive issues. The appropriate venue, within the currently evolving laws and regulations, is proposed to be a three-tier combination of massive data, including data accumulation, transformation, organization, stratification, estimations, data analysis, and blockchain technology, predicted to revolutionize competition and efficiency, which are further suggested to be prerequisites for a more successful creation and implementation of the third element, AI. A currently evolving prosperity tripod is hinging on the three technological legs of the massive data control/management, blockchain tech, and a rapidly growing AI. While briefly incorporating some analysis of the blockchain application, we have analytically focused on the rest—the data and AI—of what we deem to be the prospective prosperity tripod for businesses, markets, and societies, in general, despite the challenges and risks involved in each. Instead of hypothesizing a predetermined economic model, we are proposing a data-based Vector Autoregression (VAR) methodology for the AI with an application to the fraud and anti-fraud structure and policymaking. Hopefully, the entire attempt would portend some tangible prospective contribution in an achievable positive societal change.