Accuracy and Limits in Receipt Reading

Photographing a receipt and having the amount populate automatically is a huge upgrade from the glovebox archive. But OCR is not magic: it reads some receipts extremely well, while misreading or completely failing to read others.

In this article, we explain what determines accuracy, the limitations, and the habit of approval — to help set the right expectations.

What OCR does

Optical character recognition converts text in an image into digital text. When scanning expense receipts, the following are typically targeted:

• Total amount (and VAT if possible)
• Date
• Vendor / title
• Document no (if any)

The system suggests an expense draft; it should not become a final record until you approve it. We covered the product side of this workflow in the expense receipt scanning article.

What it reads well

• Clearly printed cash register / POS receipts
• Close-up photos taken in proper lighting
• Single-page, crease-free, high-contrast printouts
• Standard, well-formatted e-document PDF outputs (cleaner when processed as a file rather than a scan)

Under these conditions, the amount and date are usually captured correctly. Still, a quick glance on the approval screen is essential — especially for the VAT rate and vendor name.

What it struggles with / cannot read

• Faded thermal receipts. Sun-exposed, faded receipts are the classic enemy of OCR.
• Handwriting. Notes and signature areas cannot be read reliably.
• Creased, reflective, or blurry photos. Capture quality dictates the result.
• Multi-line, complex invoices. Parsing item-by-item is harder than reading a total.
• Foreign languages / unusual layouts. Field detection may go off track.

In such cases, the system may read partially or leave fields blank. The right response: fix it manually and save — rather than assuming "it's bound to be right."

Habits that boost accuracy

• Snap receipts flat, shadow-free, and vertically if possible.
• Photograph them on the same day before they fade.
• Check the amount, date, VAT, and vendor during approval.
• Choose the right expense category; the wrong category messes up period-end closing. Expense classification
• Link the payment to the record as well; cash discrepancies often stem from this. One-step payment

Setting the right expectations

The value of OCR isn't "saving without looking," but cutting down data entry time. A 100% accuracy promise is unrealistic; a good process means high accuracy + human approval.

When used alongside the AI assistant, the receipt draft + the question "how much was spent on fuel this month" follow the same discipline: clean data, clear question. Asking financial questions to AI

Frequently asked questions

What happens if an incorrect amount gets recorded?

Correct it before approval. If it has already been approved, update it via cancellation/correction, and also check the bank or cash transaction.

Is a receipt mandatory, or an invoice?

Deductible VAT and document requirements vary depending on the amount and the nature of the business. Don't confuse small retail receipts with invoiced purchases; ask your accountant if in doubt.

Are PDF invoices scanned too?

In most systems, e-invoices/e-archives arrive electronically anyway; OCR is primarily for paper/receipt photos. Avoid unnecessarily photographing PDFs.

Does it consume quota?

Depending on the product, receipt reading may consume credits. Check the Qolay Credits article.

In short: receipt OCR is strong on well-shot, clear receipts; weak on faded or handwritten ones. Its value lies in approved speed — not blind trust.

By opening a free account on Qolay.App, you can try out the expense receipt scanning workflow.

This article is for general informational purposes. Expense document and VAT deduction rules vary by context; consult your accountant for your specific situation.