Finance · Process breakdown
Let AI read receipts and check policy, approve the routine claims automatically, and send only the odd ones to a person.
The expense claim process is one of the few back-office jobs where AI can do the core work rather than assist with it. An expense claim process runs on small, repeated decisions: is the receipt readable, does the amount match, is it within policy, who approves it. Reading receipts is exactly the unstructured task AI handles well, and policy checks are rules. What remains for people is the small share of claims that are unusual, sensitive or large. Start by writing the policy down as rules a system could apply, because a policy that lives in someone’s head cannot be automated, only imitated.
The employee photographs the receipt in the expense app and the system files it against the employee, the cost centre and the date. Intake is plumbing, not judgement.
AI extracts merchant, date, amount, currency, tax and category from the photo, including crumpled, faded and foreign receipts that template-based capture never handled.
Limits per category, per diem rules, required fields and duplicate detection run as explicit rules on the extracted data. Claims that pass are approved and queued for payment.
AI compares a claim with the employee’s history and typical patterns for the category, and writes a one-line reason why it looks unusual. The reviewer starts from that note instead of a blank screen.
The manager or finance reviews flagged claims with the AI note attached, asks for missing details, and approves or rejects. Approved exceptions join the payroll export.
Run AI extraction and the policy check in shadow mode for one month while managers approve as they do today. Count field corrections, false flags, and claims the rules would have cleared that a manager rejected. Switch on automatic approval for the lowest-risk category first, with a monthly sample check.
Automating approval before the policy is precise. If two managers would decide a claim differently, the rules are not ready, and the AI will simply be inconsistent faster.
You need a single place where claims and receipt images arrive, a way to run policy rules, and an export to payroll or your accounting system. Expense management software bundles those and usually includes receipt reading. If you already have an expense app, check whether it exposes claims through an API before adding another tool; the AI and policy steps can often sit around what you have.
Good enough to handle most clean receipts without correction and to say when it is unsure, which is the property that matters. Faded thermal paper, handwritten totals and foreign tax lines are where errors cluster. Measure accuracy per field during the pilot and let the system flag low confidence instead of forcing a value; a flagged field costs seconds, a wrong amount costs trust.
At the policy, the thresholds and the exceptions. Finance decides what the rules are and changes them, a manager reviews claims that are unusual or large, and someone remains accountable for fraud checks. Everything below those lines can run without a person touching it, as long as a monthly sample review confirms the rules still behave as intended.
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