Web 3 Data Matching for Blockchain-Supported Real Estate (Position Paper)

Abstract

The real estate sector plays a vital role in today's economy and society. However, the current system for managing real estate transactions remains heavily reliant on manual document handling and verification processes, which are often inefficient and vulnerable to fraud, underscoring the need for innovative solutions. This position paper proposes a system that integrates Optical Character Recognition (OCR), Natural Language Processing (NLP), and Verifiable Credentials (VCs) to automate document extraction, verification, and management within real estate transactions. Key goals include (1) a comprehensive workflow to transform diverse document formats into standardized VCs and (2) an automated data matching mechanism to identify inconsistencies and potential fraud indicators. The approach involves using the potential of blockchain and Web3 technologies as a decentralized trust layer to improve data integrity and transparency. This solution holds significant promise for streamlining real estate processes, fostering trust among stakeholders, and establishing a scalable framework for secure and efficient digital transactions.