Greystone

Improved compliance and reduced manual errors.

Finance & Legal

|

Real Estate

|

Natural Language Processing

Project Overview

Automating document comparison and discrepancy detection across loan agreements.

Layman's Explanation

The system extracts and compares key information from different loan documents to ensure consistency, replacing a tedious manual process with fast, automated checks.

Analogy

It’s like automating quality checks in real estate finance, where AI becomes an assistant that quickly identifies mismatched figures, just as inspectors spot building defects.

Details

A machine learning pipeline using Google Cloud tools, including OCR for entity extraction and field comparisons between complex mortgage documents. This solution processes documents in minutes, significantly reducing the manual workload, improving accuracy (~80%), and ensuring compliance with loan agency timelines.

Project Novelty

Using OCR and machine learning to automate mortgage document comparisons is advanced and reduces significant manual work.

Project Estimates

Timeline:

5 months

Cost:

$125,000

Headcount:

4

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