Every bank deposit needs to be matched to the right customer and invoice in NetSuite. With a global footprint spanning 74 bank accounts across 10+ subsidiaries and 8 currencies, this creates a daily puzzle. The team was processing 25+ payments per day, each requiring customer identification and invoice matching. Manual processing consumed approximately 3 hours per day just on research, matching, and data entry.
Two Workato recipes orchestrate the entire flow, from bank statement ingestion to NetSuite payment posting. The system uses a 5-layer matching engine that runs each payment through progressively broader matching strategies until the best match is found.
Import daily bank lines from statement files across all accounts and currencies.
AI identifies customer payments vs. other transactions (equity, internal transfers, tax refunds).
Fetch open invoices from NetSuite via SuiteQL for the relevant subsidiary and currency.
Each payment runs through confirmed mappings, remittance cross-check, invoice reference matching, customer + invoice resolution, and aggregate waterfall allocation.
Team reviews matches in a custom dashboard. High-confidence matches auto-apply directly to NetSuite via REST API.
Every thumbs up and thumbs down makes the next run more accurate. No ML model needed, just a growing knowledge base. Confirmed matches permanently link bank names to customers. Rejected matches reveal missing aliases or edge cases. Exclusion patterns teach the system to auto-exclude non-payment items. Accuracy compounds daily.
High-confidence matches are applied without manual review. Auto-applied payments go straight from bank to NetSuite with no copy-paste. The team's hours are redirected from repetitive matching to higher-value analysis and exception handling. The system supports USD, GBP, EUR, AUD, CAD, SGD, JPY, and NZD, all mapped to the correct subsidiaries.