Automating invoice coding in SAP
Rules can only automate recurring invoices, and in most companies those make up just 20% of non-PO invoices. The other 80% are still coded by hand at €4-8 each, and that is the automation still sitting on the table in most SAP finance teams.
This white paper shows how self-learning AI closes the gap: over 90% of invoices automated, under €1 per invoice, 98%+ coding accuracy, and no change to how your team works in SAP.
What self-learning AI makes possible in SAP
Snowfox connects to the backend of your SAP Finance environment as an add-on and builds a self-learning model from your own invoice history. Nobody writes rules, nothing is reconfigured, and your team carries on working in SAP exactly as before.
Without it, most non-PO invoices arrive in SAP with empty coding fields and somebody fills in every one of them. From day one Snowfox predicts the GL account, cost centre, tax code and the other dimensions you use, along with the right approver, based on how similar invoices were coded and routed before. Every prediction carries a confidence score: high-confidence predictions post automatically, and anything below the threshold you set is flagged for review instead.
Rules and templates got invoice automation this far and they still handle the invoices that repeat exactly. What they cannot do is adapt, and every new supplier, cost centre or organisational change adds maintenance. The AI learns from each correction your team makes during approval, so accuracy climbs on its own.
What this white paper covers:
- Why rule-based automation leaves most non-PO invoices untouched
- How a self-learning model codes and routes invoices with no rules to build or maintain
- Confidence scores, and deciding what posts automatically
- The business case, worked through on a 50,000 invoice example
- What setup involves, and what happens to every invoice in production
- Connecting to SAP, and why it is live in weeks
- An anonymised customer reference: 80%+ auto-coded, clear value in two months
