The company and workflow in this article are fictitious. They illustrate how a document-heavy expense process could be assessed and redesigned.
The problem: receipts arrive faster than finance can process them
Northbridge Field Services employs engineers who travel between customer sites. Employees collect paper receipts for parking, fuel, accommodation and materials.
Its expense process depends on several manual steps:
- Employees keep receipts until they return to the office.
- They scan each receipt or photograph it and email it to finance.
- Finance staff rename and file the image.
- They copy the supplier, date, amount and tax details into the expense system.
- They contact the employee when a receipt is unclear or its business purpose is missing.
The problem is not simply scanning. Information moves between paper, email, folders and the expense system without a consistent structure. That increases administration and makes it harder to spot incomplete, duplicated or questionable claims.
Before proposing technology, Northbridge would need to establish a baseline: receipt volumes, handling time, common errors, missing fields and the number of claims returned for clarification.
The design: take a photo, add a tag and submit
The proposed app gives employees one simple task. They photograph the receipt when they receive it, select an expense tag and submit it.
The app uses AI-assisted document extraction to suggest:
- supplier name;
- transaction date;
- total amount;
- tax amount, where visible;
- currency; and
- likely expense category.
The employee checks the suggested information and adds a short business-purpose tag, such as “Customer visit — Birmingham”. The app then sends the image and structured data into a review queue for finance.
This design reduces rekeying, but it does not treat AI output as fact. Low-confidence fields are highlighted. Missing information is requested before submission. Finance retains responsibility for approval and can correct extracted data.
Controls should be part of the workflow
A useful expense app needs more than accurate text extraction. The design should also address:
- duplicate receipt detection;
- image quality and missing-page checks;
- expense-policy prompts;
- role-based access;
- an audit trail of submissions, edits and approvals;
- secure retention and deletion rules; and
- clear handling of personal or payment information visible on receipts.
These controls help the business assess operational risk before connecting the app to accounting or payment systems.
Execution: prove the workflow before integrating everything
Northbridge could test the concept with a limited group of employees and a narrow set of receipt types.
1. Map the current process
Document every hand-off, system and exception. Record the baseline measures that will be used to judge the trial.
2. Build a controlled prototype
Create the photo, extraction, tagging and finance-review journey. Keep the existing expense system as the system of record during the trial.
3. Test real operating conditions
Use an approved sample covering faded print, folded receipts, poor lighting, different currencies and handwritten tips. Check whether employees understand the prompts and whether finance can resolve exceptions quickly.
4. Measure the outcome
Compare the trial with the baseline. Useful measures include handling time per receipt, extraction correction rate, incomplete submissions, duplicate claims and employee completion rate.
5. Decide whether to integrate and expand
Proceed only if the measured value justifies further work. The next stage might connect approved data to the expense platform, extend receipt categories or add policy checks.
The goal is a better-controlled process, not AI for its own sake
For finance teams, the opportunity is to remove repetitive document handling without weakening oversight. A focused trial can show whether photo capture and AI-assisted extraction reduce rework, improve submission quality and make expense review easier to manage.
If manual receipt processing is consuming finance time, request a free opportunity call to assess the workflow, its risks and a measurable proof of value.