Document classification
Application document classification.
AI Document Processing for
Fintech
Turn financial documents into structured information for review.
Zimozi develops document processing workflows for fintech applications and internal teams. We classify files, extract agreed fields and validate results before information reaches the next system.
Field extraction
Statement and business record field extraction.
Invoice processing
Invoice and payment document processing.
WHAT WE BUILD
Document workflows we build.
Document classification
Application document classification.
Field extraction
Statement and business record field extraction.
Invoice processing
Invoice and payment document processing.
Completeness checks
Missing information and completeness checks.
Review interfaces
Review interfaces and exception queues.
Approved data transfer
Approved data transfer to onboarding or operations systems.
A PRACTICAL FIRST STEP
Define what needs to be extracted.
The starting point
Statements, application forms and company records vary in layout and quality. We assess representative samples and agree the required fields, formats and validation checks.
How we scope it
The source document remains available so staff can inspect uncertain results.
Document classification
Application document classification.
Combine extraction with validation
Optical character recognition may be required for scanned files. Extracted values are checked against agreed formats and business rules. Unclear fields and unfamiliar layouts go to review instead of being accepted without verification.
Measure performance on your documents
Evaluation covers field-level accuracy, missing fields and the rate of manual review. Results depend on document quality and variety, so expectations are set after testing representative samples.
From idea to everyday use.
Discover
Understand the users, current process and intended result.
Assess
Review the data, systems, access and review needs.
Develop
Build a focused pilot around the agreed use case.
Deploy
Connect the solution to the workflow and test exceptions.
Evolve
Monitor quality, usage and costs, then improve.
BUILT FOR REAL WORKFLOWS
Combine extraction with validation.
Optical character recognition may be required for scanned files. Extracted values are checked against agreed formats and business rules. Unclear fields and unfamiliar layouts go to review instead of being accepted without verification.
IN PRACTICE
A practical use case.
Measure performance on your documents
The situation
An onboarding team receives several documents for one application.
The workflow
The workflow identifies document types, extracts required information and flags missing or inconsistent fields. Staff review the results alongside the originals before the application proceeds.
In context
This example illustrates a potential workflow, not a claimed customer result.
Project scope
Evaluation covers field-level accuracy, missing fields and the rate of manual review.
Delivery details
Results depend on document quality and variety, so expectations are set after testing representative samples.
Frequently asked questions
Still have a question?
Can’t find the answer you’re looking for? Send us a message and we’ll get back to you as soon as possible.
Send message
Yes, depending on scan quality and layout. We test samples before setting accuracy targets.
Field extraction alone does not establish authenticity. Verification requirements need separate controls or specialist provider integration.
Yes, for approved cases within the agreed validation rules. Uncertain results can require staff approval.
YOUR NEXT STEP
Start with one document type
Share sample documents and the fields your team needs. We will help define a workflow that is practical to test and operate.
Start a ProjectTell us about
Tell us about
your project.
Share a short brief, or book a time to talk with our team.