Three-Way Matching Bot

Ingests unstructured and structured invoice formats (PDF, EDI, XML, paper scans) and extracts critical line-item data. Optical Character Recognition (OCR) combined with Natural Language Processing (NLP) identifies supplier identity, quantities, unit prices, and total amounts. The bot normalizes disparate data schemas into a unified digital record for comparison, eliminating manual data entry errors.

• Extracts header and line-item details
• Classifies document type (Invoice vs. Credit Memo)
• Maps supplier data to the master vendor record

Executes a rule-based comparison of the Purchase Order (PO) , the Goods Received Note (GRN) , and the Supplier Invoice. The bot validates that what was ordered matches what was received and what is being billed. It applies configurable tolerance thresholds for quantity and price variances to automatically approve or flag transactions.

• Quantity Matching: Invoice qty ≤ GRN qty ≤ PO qty
• Price Matching: Invoice unit price ≤ PO unit price
• Tolerance Logic: Auto-approves if variance is within ±2% or $50

When a mismatch exceeds defined tolerances, the bot does not simply fail. It classifies the exception type—price variance, quantity overage, or missing receipt—and routes the transaction to a specific human workflow queue with a pre-populated audit trail. This ensures that only true anomalies require manual intervention.

• Categorizes mismatches by root cause
• Attaches relevant PO, GRN, and Invoice evidence
• Routes to the specific category manager or warehouse lead

Before matching, the bot cross-references the invoice against historical transactions to detect duplicate invoices or synthetic fraud. It hashes key data points (supplier tax ID, invoice number, amount) to identify exact or near-duplicate submissions, preventing erroneous double payments.

• Fuzzy matching on invoice numbers
• Cross-checking bank account changes against vendor master
• Flagging round-amount invoices for review

For transactions that pass all matching and fraud checks, the bot updates the Enterprise Resource Planning (ERP) system status from 'Received' to 'Approved for Payment'. It triggers the payment run file directly, bypassing the manual approval queue entirely to capture early payment discounts.

• Updates ERP status codes via API
• Triggers payment batch processing
• Logs full audit trail for SOX compliance

Monitors resolution patterns from the exception queue to refine matching logic. If a specific supplier consistently ships 5% over the PO quantity and it is always accepted, the bot can propose a dynamic tolerance adjustment for that vendor relationship, reducing future false positives.

• Tracks acceptance rates of exceptions by vendor
• Recommends tolerance rule updates
• Builds a behavioral profile for strategic suppliers

The end-to-end business process that the three-way matching bot completes. P2P automation orchestrates the entire lifecycle from requisitioning to final payment settlement without human touchpoints. The matching event is the critical gating function that determines whether funds are released.

• Integrates with ERP master data for vendor records
• Triggers dynamic discounting based on early payment
• Maintains a complete audit trail for compliance

A continuous auditing bot that operates in parallel with the matching engine. Before an invoice is approved, this agent screens the transaction against sanctions lists, internal delegation of authority policies, and tax compliance rules. It ensures that a matched invoice is not just mathematically correct, but legally sound.

• Validates VAT/GST identification numbers
• Checks for segregation of duties violations
• Monitors for sanctioned entity exposure

Unsupervised machine learning algorithms that identify purchases occurring outside the formal three-way matching process. These models analyze transactional data to find spend that bypassed the purchase order system entirely, creating a risk of unmatched invoices and budget leakage.

• Clusters transactions by vendor and category
• Identifies rogue buying patterns in real-time
• Quantifies savings erosion from off-contract spend

An algorithm that activates once the three-way match is confirmed. It calculates a real-time sliding scale discount for early payment based on the buyer's cost of capital and the supplier's implied liquidity needs. The matched invoice becomes a financial instrument.

• Offers APR-equivalent returns on early payments
• Strengthens supplier relationships through optional liquidity
• Integrates with treasury management systems

The algorithmic aggregation of data points generated during the matching process. Every quantity shortage, incorrect pricing, or late delivery detected during the three-way match feeds into a dynamic, objective scorecard for the vendor, influencing future sourcing decisions.

• Tracks Perfect Order Rate metrics
• Correlates discrepancy types with specific suppliers
• Feeds risk scores into Strategic Sourcing AI