Project BRIDGE

Blockchain Receipt Intelligence for Developing Greater Equity Tokenizing Financial Inclusion Through Computer Vision–Based Receipt Verification

Project Overview

BRIDGE is a machine vision and blockchain research project designed to convert everyday receipts into portable, verifiable financial records. By extracting key payment information through optical character recognition and anchoring cryptographic proofs to a blockchain ledger, BRIDGE explores how receipt level data can support equitable credit scoring for underbanked communities.

About the Researcher

Crystal Tubbs

Crystal Tubbs is an AI Solutions Architect and Emerging Technologies Specialist with experience in applied AI, custom LLM agent design, model evaluation, and blockchain enhanced digital verification systems. Her academic work explores fairness, computer vision, knowledge extraction, and equitable financial technologies. She is completing her Master of Science in Artificial Intelligence at Kennesaw State University.

Key Findings

OCR combined with preprocessing significantly improves extraction accuracy on low quality receipts.
Recurring payments such as utilities and groceries can be reliably detected and categorized.
Blockchain anchoring of hashed receipt identifiers is low cost and preserves privacy.
Receipt based intelligence shows strong potential for decentralized credit pathways.

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