Abstract: Ensuring data integrity in decentralized financial systems is a critical challenge due to the distributed nature of data sources, transaction complexities, and the absence of centralized oversight. This review explores a model that leverages blockchain technology and artificial intelligence (AI) to achieve auditable, automated reconciliation and strengthen data integrity across decentralized finance (DeFi) ecosystems. By harnessing blockchain’s immutable ledger and consensus protocols, the model ensures tamper-proof transaction records, while AI enhances real-time anomaly detection, predictive reconciliation, and process automation. The review critically analyzes current methodologies, identifies gaps in traditional reconciliation approaches, and presents a framework where smart contracts, AI-driven analytics, and decentralized oracles work synergistically to ensure transparent, verifiable, and efficient financial operations. Furthermore, it evaluates the implications for regulatory compliance, scalability, and system resilience. The proposed model represents a significant advancement toward self-reconciling systems that enhance trust, reduce operational costs, and improve decision-making in DeFi infrastructures.
Keywords: Decentralized Finance (DeFi), Blockchain Technology, Artificial Intelligence (AI), Data Integrity, Smart Contracts, Cost-Benefit Analysis.
Title: Data Integrity in Decentralized Financial Systems: A Model for Auditable, Automated Reconciliation Using Blockchain and AI.
Author: Esther Alaka, Kehinde Abiodun, Shereef Olayinka Jinadu, Emmanuel Igba, Vera Nwakaego Ezeh
International Journal of Management and Commerce Innovations
ISSN 2348-7585 (Online)
Vol. 13, Issue 1, April 2025 - September 2025
Page No: 136-158
Research Publish Journals
Website: www.researchpublish.com
Published Date: 27-June-2025
