
Intercompany reconciliation remains one of the main pain points in the close. Differences are often detected late, when teams have little time to identify the cause, contact the counterparty and correct the data.
What today’s tools can do
- collect balances by entity and partner;
- automatically match by amount, currency and reference;
- manage tolerances;
- convert into a common currency;
- provide justification and resolution workflows;
- support comments and attachments;
- propose or generate journal entries;
- provide dashboards and automated reminders.
Exact matching is only the first level
Simple cases can be matched automatically. Complex cases require more sophisticated rules: grouping several invoices, timing differences, netting, foreign-exchange differences or relationships between reciprocal accounts.
Can AI help?
Anomaly detection and probabilistic matching can suggest matches or prioritize differences. They are useful when references are incomplete. Validation must remain traceable, however, and deterministic rules should be preferred whenever sufficient.
Recurring causes to address
- incorrect or missing partner;
- invoice recorded in different periods;
- different currencies or rates used;
- incorrect reciprocal account;
- VAT or fees recorded on only one side;
- difference between invoice and payment;
- data submitted after the deadline.
Reconcile before consolidation
The best process starts in ERP systems or an intercompany portal before final submission. Partners then have time to resolve differences. Consolidation receives reliable data instead of becoming the main place where corrections are made.
Useful indicators
- automatic match rate;
- amount and age of differences;
- differences by cause and entity;
- average resolution time;
- number of post-submission corrections;
- share of flows without usable references.
A progressive automation approach
- standardize accounts, partners and references;
- define matching rules and tolerances;
- automate simple cases;
- organize a workflow for exceptions;
- analyze root causes;
- gradually extend automation.
Technology can greatly accelerate reconciliation, but it cannot compensate for poor data quality. Maximum value is achieved when intercompany rules, responsibilities and calendars are harmonized across the group.