AI Account Reconciliation Agent

Bonami's agent achieves 92–97% auto-match rates on production volumes, depending on data quality. The ML model learns from your historical decisions over 4–6 weeks — structured bank and ERP data typically reaches 96–97% within 60 days, while high-volume payment environments stabilise at 92–94%.

Certified native connectors for SAP S/4HANA, Oracle Fusion Financials, Oracle NetSuite, Workday Financials, BlackLine, and Coupa.

The agent ingests intercompany payables and receivables from each entity's ERP, builds a consolidated matching dataset, and flags discrepancies from timing, currency translation, and coding mismatches.

Instead of accumulating transactions for bulk matching at close, the agent matches them as they flow through bank feeds and ERP sub-ledgers, typically within minutes of posting.

Every action is captured in an immutable audit log — match decisions, exception rationale, manual overrides, and timestamped sign-offs.

A standard implementation runs 6–10 weeks: connectivity and policy setup, a parallel-run phase, phased go-live by account category, then ML fine-tuning and training.

Manual reconciliation costs $15–$40 per transaction; AI-automated runs below $2 — an 85–93% reduction, or $1.3M–$3.8M a year for a team processing 10,000 items per close.

Most financial reconciliation software relies on static rules that need heavy configuration and break on edge cases. Bonami's account reconciliation software adds four matching layers, including ML trained on your historical decisions, reaching 92–97% auto-match rates without hardcoded thresholds.

Yes. As month end close software it matches continuously across bank feeds, ERP sub-ledgers, and intercompany accounts, so 85–90% of reconciliation is done before close.