SAP remains the system of record
The workflow complements the finance environment instead of creating a parallel ledger or asking users to re-enter approved results.
Use case · Finance
Let Finance review the exception. Let the system prepare the match.
Many bank statement items clear through established SAP rules. The expensive work begins when a payment reference is incomplete, one transfer covers several invoices, or the missing context sits in an email. This workflow prepares the evidence and proposed match around SAP so a finance professional can resolve the exception with control. The scenario arose from customer conversations and has not yet been implemented by AutoMates.
What this means in practice
Attention moves to exceptions
Clear matches follow agreed rules. Finance spends its time on incomplete, ambiguous, split, or genuinely unusual cases.
Approval follows authority
Confidence, value thresholds, company codes, and finance roles determine what can be prepared, proposed, approved, or escalated.
The recurring problem
The payment is visible. The reason behind it is scattered.
A difficult item rarely lacks data entirely. The useful evidence is simply distributed across the bank statement, SAP, invoices, remittance advice, shared inboxes, and knowledge held by the team.
Incomplete references
A payer uses a customer name, amount, or free-text reference that does not cleanly identify the open item. A person searches several views to reconstruct the likely match.
Many-to-many reality
One payment can cover several invoices; deductions, fees, currency differences, or partial payments break a simple one-to-one rule.
Recurring exceptions stay manual
Teams often recognise the same exception pattern repeatedly, but the reasoning remains in individual experience instead of becoming a controlled reusable rule.
The proposed workflow
Prepare one evidence-backed resolution inside the existing finance process.
The exact SAP version, interfaces, authorisations, posting rules, and approval design are confirmed during Process Discovery. The workflow can then be scoped around what the environment safely supports.
Bring the relevant evidence together
Read the unresolved statement item and permitted SAP records, then retrieve supporting context such as remittance advice, invoice references, customer correspondence, or an approved exception rule.
Generate candidate matches
Combine deterministic rules with AI-assisted interpretation where references are unstructured. Present the likely open items, variances, assumptions, and source evidence rather than a black-box answer.
Route by confidence and authority
Straightforward cases can follow approved rules. Ambiguous, high-value, or unusual items enter the correct finance queue with a proposed action and the evidence needed to review it.
Write back the approved result
After the authorised person confirms or corrects the proposal, the integration records the permitted outcome in SAP and preserves a trace of what was proposed, changed, and approved.
The operating view
Give Finance a smaller queue and a better decision.
The target is not maximum autonomy. It is less searching, less rekeying, and clearer control over the cases that still deserve professional judgment.
For the finance team
Each exception arrives with the likely match, supporting records, unexplained difference, and proposed next action.
- Filter by entity, value, age, or confidence
- See source evidence beside the proposal
- Correct or approve without rebuilding the case
For the process owner
Recurring failure patterns become visible enough to improve master data, references, rules, and upstream behaviour.
- Track exception volume and ageing
- Measure touch time and correction rate
- Turn repeated resolutions into controlled rules
Common questions
Answers before the call.
Clear answers to the practical questions that usually come up before a first conversation.
Can this work with our existing SAP environment?
Potentially, yes. The design depends on your SAP product and version, available interfaces, current bank statement setup, authorisations, surrounding inboxes, and approval requirements. Process Discovery establishes the viable integration path before a build is proposed.
Does AI post directly into SAP?
It does not have to. The workflow can prepare and route a proposed resolution while an authorised finance user approves the consequential action. Direct execution is only considered for bounded cases where rules, permissions, confidence, and audit requirements support it.
How should the improvement be measured?
Useful measures include automatic match rate, unresolved-item backlog and age, handling time per exception, correction rate, and the share of recurring exceptions converted into reliable rules. The baseline must be established before implementation.
Continue exploring
AI Field Audit Reporting
See another use case where AI prepares evidence and a qualified person retains sign-off.
Trust & Security
Review role, access, approval, logging, and handover principles.
Process Discovery
Map the SAP process, interfaces, exception volume, and baseline before choosing the architecture.
AutoMates
How much Finance time is hiding in the exception queue?
Bring one reconciliation flow, its recurring exceptions, and the systems around it. We will test whether the manual effort is large and stable enough to automate.