Digitizing Business Processes More Cost-Effectively with Business AI: Part 4

Part 4:
How Business AI Is Truly Transforming Finance & Administration

In many companies, finance and administration are viewed as a necessary evil: a lot of effort, little visibility, and hardly any strategic recognition. Yet this area holds enormous potential for efficiency—and, at the same time, an underestimated risk. After all, errors in financial accounting cost not only time but also money: through lost cash discounts, incorrect journal entries, missed deadlines for filing complaints, or unplanned overtime in the receiving department.

What makes Business AI in Finance & Administration unique is that it does not interfere with strategic decisions—those remain the responsibility of humans. Instead, it handles the tasks of reading, reviewing, categorizing, and preparing. Employees act as reviewers, not data entry clerks. Four specific use cases illustrate how this works in practice.

What Business AI Means for Finance & Administration

Finance & Administration relies on documents: purchase requisitions, incoming invoices, shipping notices, complaints, and credit memos. They come in a wide variety of formats, from a wide variety of senders, and contain a wide variety of potential errors. The task of AI agents is not to post these documents autonomously, but to read, understand, and verify them, and to provide the administrator with a clear, prepared decision-making template.

The principle is called “User in the Loop“: No automatic posting takes place without human confirmation. Each step in the posting process requires explicit approval. The AI handles the routine work, while humans decide on exceptions.

Simplifier is the platform on which these agents are natively created, integrated, and operated—directly connected to SAP FI, SAP MM, and other ERP systems.

1. BANF Recognition Agent: From Photo to SAP Posting — With Just One Click

The problem: Purchase requisitions (BANFs) reach the purchasing department in a wide variety of formats: handwritten forms, scanned PDFs, emails, and Excel files. Someone has to manually read and verify the content and enter it into the ERP system. Particularly critical: incorrectly identified cost centers or item numbers lead to incorrect postings that require time-consuming corrections.

The Business AI Solution: The agent automatically recognizes incoming documents as purchase requisitions and extracts all relevant fields: item number, quantity, cost center, desired delivery date, and requesting department. It transfers the result as a structured draft to SAP MM and submits it to the responsible buyer for review. Fields with lower recognition accuracy are highlighted in color. The transaction is posted only after explicit human approval.

Here’s a concrete example: A maintenance foreman sends a handwritten purchase requisition via photo: “40 V-belts, Type B-42, cost center 3210, by calendar week 48.” The agent identifies the belt type, finds the correct SAP item number, and sets the cost center. She correctly reads the quantity “40,” but flags the handwritten “4” with a yellow note because it could easily be misread as “1.” The buyer confirms the 40, approves it with a single click—and the transaction is posted without having to manually enter a single number.

Target: −75% reduction in manual data entry time | Error rate close to zero.

2. Invoice Verification Agent: From 35 minutes to 4 minutes per invoice

The problem: Incoming invoices must be reconciled against purchase orders and goods received—the so-called three-way reconciliation. Today, this is done manually: pulling the invoice from the inbox, looking up the purchase order number, comparing quantities and prices, and resolving discrepancies. With hundreds of invoices each month, this is an enormous time drain. And because invoices remain in circulation for too long, cash discounts are lost—hard cash that sits unused.

The Business AI Solution: The agent fully parses the incoming invoice (PDF, scan, or EDI) and automatically performs a three-way reconciliation with the purchase order and goods receipt in SAP FI/MM. The results are clearly presented to the processor:

• Green: Fully tested, ready for release
• Yellow: Minor deviation within the tolerance range — with a suggested explanation
• Red: Critical discrepancy requiring manual resolution

The administrator reviews only the flagged exceptions—and then approves them. No posting is made without his confirmation.

Here’s a concrete example: An invoice with 23 line items is received. The agent verifies all line items in seconds: 21 match exactly. Line item 18 differs by 1.2% in price—which is within the agreed-upon tolerance (yellow). Item 22 has no associated goods receipt document (red). The clerk checks only these two items—processing time: 4 minutes instead of the previous 35.

Target: −80% reduction in manual inspection time | Discount losses virtually eliminated.

3. Shipping Notice Processing Agent: The Goods Receiving Department always knows what’s coming

The problem: Delivery notices arrive via email, fax, EDI, or the supplier portal—in completely different formats depending on the supplier, sometimes in three different languages on the same day. The receiving department must manually review the notification, look up the expected delivery in the ERP system, and create a delivery schedule. Overlooked notifications lead to unplanned overtime or delivery backlogs.

The Business AI Solution: The agent automatically recognizes incoming delivery notices in any format and extracts the supplier, delivery date, time, item numbers, quantities, and the reference to the SAP purchase order. It creates a delivery proposal, including loading dock scheduling. Only after confirmation by the goods receipt clerk is the shipment notification posted in SAP MM and the loading dock reserved.

Here’s a concrete example: On Tuesday evening, 8 delivery notices for Wednesday deliveries come in—via email, in German, English, and Czech, with three different layouts. The agent processes all 8 in under 2 minutes. He notices that one delivery is arriving two days earlier than expected and exceeds the daily capacity of Dock 3. He flags this case for the dispatcher, who confirms Dock 2 as an alternative. The remaining seven delivery notices are automatically processed. No manual reading of a single email is required.

Target: −70% effort in delivery notice processing | No unplanned surprises at the loading dock.

4. Credit Memo & Discrepancy Report Agent: No open case will be overlooked

The problem: When delivery quantities vary, goods arrive damaged, or prices don’t match the order, someone has to resolve the discrepancy, file a complaint with the supplier, and request and post a credit memo. This process is often completely unstructured, handled via email, and takes weeks. Unresolved discrepancies get lost in the day-to-day operations, and credit memos are posted too late—or not at all.

The Business AI Solution: The agent automatically detects discrepancies during invoice or goods receipt reconciliation and opens a structured clarification case in the system. It drafts the complaint text to be sent to the supplier, tracks the case until a credit memo is issued, and, following manual approval, posts it correctly in SAP FI. Each step—sending the complaint, assigning the credit memo, and triggering the posting—requires explicit human confirmation.

Here’s a concrete example: For a shipment of 100 hydraulic valves, only 87 are delivered, but 100 are billed. The agent immediately identifies the quantity discrepancy, drafts a complaint to the supplier, and submits it to the buyer for approval. Two weeks later, the credit memo arrives as a PDF—the agent identifies it, assigns it to the open clarification case, and proposes the posting. The administrator confirms—done. Not a single step has gone missing in the email inbox.

Target: −60% resolution time | 100% follow-up rate for open discrepancies.

What All Four Use Cases Have in Common

Finance & Administration is the area where companies lose money every day—quietly and without much fanfare. Through cash discount losses that no one keeps track of. Through accounting errors that take a lot of effort to correct. Through discrepancies that get lost in email inboxes. And through employees who spend valuable time entering numbers instead of making decisions.

Business AI with Simplifier fundamentally changes the dynamic: The AI reads, reviews, and prepares—humans make the decisions and approve. This isn’t a loss of control—it’s the opposite: more control with less effort, because no information is lost in the manual process anymore.

Conclusion: Finance that finally thinks for itself

The Finance & Administration department of the future doesn’t enter numbers. It reviews exceptions. It makes decisions where it matters most and leaves the reading, categorization, and preparation to AI. Business AI with Simplifier makes exactly that possible today—as a concrete, actionable solution for midsize companies with SAP environments, without vendor lock-in and with predictable costs.

Read Part 1: Business AI in Manufacturing

Read Part 2: Business AI in Logistics

Read Part 3: Business AI in the Service Industry

Harness the potential of AI across a wide range of departments

Over the next few weeks, we’ll be presenting AI-powered use cases for various business processes. If you’d like to get a glimpse of the potential of business AI for your department’s processes right now: