Building a Blockchain-Based Artificial Intelligence (AI) Classification Model to Detect Frauds in a Live Transactional Financial System - Ketha, Srinivas (Digital Repository of Theses - SSBM Geneva, 2024)
This research is being conducted to understand and explore on how to integrate two most trending, disruptive and innovative technologies of the current era that is Blockchain and Artificial Intelligence to find a solution to the business problem of detecting frauds in a live transactional financial system. The goal is to propose a conceptual framework encompassing Blockchain and Artificial Intelligence to detect and prevent frauds in a live transactional financial system for future research in the same domain to increase the chances of their success. The ongoing research aims to forge a deeper comprehension and exploration into the seamless integration of two cutting-edge and revolutionary technologies prevalent in today's landscape: Blockchain and Artificial Intelligence (AI). This integration seeks to tackle the pressing business challenge of detecting fraudulent activities within a dynamic, live transactional financial system. The primary objective revolves around devising a conceptual framework that harmonizes Blockchain and AI, ultimately aiming to proactively identify and mitigate fraud instances within such financial ecosystems. At its core, this research endeavors to leverage the inherent strengths of both Blockchain and AI. Blockchain technology, renowned for its decentralized and immutable nature, forms a robust foundation that ensures the integrity and transparency of transactions within a financial system. Simultaneously, “AI with its” prowess in “pattern recognitionand data analysis,” holds the potential to significantly enhance fraud detection capabilities by swiftly identifying anomalous patterns or irregularities amidst a myriad of transactions. The overarching ambition is to propose a comprehensive conceptual blueprint that encapsulates the synergy between Blockchain and AI. This blueprint serves as a foundational framework for future research endeavors within the same domain, fostering an environment conducive to heightened probabilities of success in addressing fraud detection and prevention. By intricately merging Blockchain's secure, transparent ledger with AI's analytical capabilities, the proposed framework aspires to fortify the existing defenses against fraudulent activities within live transactional systems. Through this amalgamation, the research aims to establish an innovative approach that not only detects ongoing fraud instances “in real time but also” proactively prevents potentially fraudulent activities, thereby fostering a more resilient and secure financial environment.