Reducing manual reconciliation of intercompany financial flows
A bank subsidiary struggled with the monthly reconciliation of more than 3,000 intra-group postings until an automated workflow eliminated media breaks and noticeably eased the monthly closing.
- Financial services
- Accounting
Key metric
Time spent on intercompany reconciliation
5030hrs
Time needed for intercompany reconciliation per month
At a glance
Starting point
The subsidiary of a banking group runs its own business unit with several product lines. Around 3,000 intra-group postings arise every month, such as allocations of IT costs, transfer prices and internal refinancing. These are transferred from various upstream systems into the general ledger and have to be reconciled on time for the consolidated financial statements. Until now, the team exported data from the core banking system, the general ledger and several secondary systems into Excel, performed the matching there and emailed lists to counterparties. Responses came in with a delay, sometimes in their own Excel formats, so reconciliation often dragged on until just before the group deadline and noticeably increased the pressure during the monthly closing.
- 3,000+
- intercompany postings/month
- 8
- employees in the closing
The challenge
Manual intercompany reconciliation was error-prone and hard to manage. Different posting logic in the entities involved led to discrepancies that were often noticed late. The accounting team had to export data from three systems, consolidate it in Excel and match it with complex formulas. Every adjustment required new exports and manual rework, which cost time and increased the risk of errors. At the same time, the group's deadlines were strict: late submissions led to queries and escalations. There was no transparency on progress; the team lead only saw shortly before the cut-off dates which counterparties were still open. Responsibilities in the business units changed, so knowledge of posting logic often depended on individual people.
Typical symptoms in the organization
Why this remained unsolved
The process had grown historically and only just worked, which is why larger IT projects were reserved for other topics. Replacing the general ledger or the core banking application was out of the question, and the department did not want to introduce another rigid piece of specialist software that would immediately require IT changes whenever the process changed. Earlier attempts were limited to new Excel templates and checklists. These reduced individual errors but did nothing about media breaks and the dependence on manual email loops. It was also unclear how an automated workflow would fit into the bank's strict authorization and compliance requirements.
Our solution
Together with the department, an automated workflow for intercompany reconciliation was built. The core idea is a central reconciliation hub that regularly reads in posting data from the general ledger and relevant secondary systems, matches it according to defined rules and assigns open discrepancies as tasks to the responsible people. The workflow recognizes which counterparties and posting types belong together and automatically creates suggestions for matches and offsetting entries without posting them directly. Employees review the suggestions in an interface, add justifications and mark items as resolved. Status information is updated continuously, so the team lead can see at any time which partners are still open and where things are stuck. Escalation rules ensure that critical discrepancies are addressed in time. The workflow remains configurable: new posting types or partners can be added without major IT projects, so the process grows with the group's requirements.
- Automated import of posting data from the general ledger and secondary systems with regular runs and plausibility checks to ensure a consistent and complete data basis.
- Rule-based matching of intercompany items by partner, account, product line and period, including flagging of discrepancies and suggestions for offsetting entries.
- Task-based workflow with a role and permission concept that assigns open discrepancies to the responsible people, monitors deadlines and escalates automatically when a deadline is at risk.
Automated reconciliation in four steps
Process analysis and target picture
Together with accounting and group financial reporting, reconciliation paths, posting types and deadlines were documented. This resulted in a target picture for the future workflow with roles, statuses and escalation rules.
Data integration and rule set
The relevant data sources from the general ledger and secondary systems were connected. Based on past closings, matching rules and plausibility checks were defined and validated together with the department.
Pilot with selected partners
The workflow was first introduced for two large intercompany partners. The team tested import, matching and task management in parallel operation and adjusted rules and interfaces based on the feedback.
Rollout and training
After a successful pilot, further partners and posting types were added. Training sessions and short guides helped establish the new process and replace the previous Excel lists.
Measured: across three monthly closings
Period: measured across three monthly closings.
| Metric | Value | Basis |
|---|---|---|
| Time spent on intercompany reconciliationKey metric | Reduced by around 40% | Time tracking before/aftermeasured |
| Share of discrepancies shortly before the deadline | Down from approx. 30% to 10% | System measurementmeasured |
| Share of items correctly matched automaticallyQuality metric | Between 70% and 80% | Samplemeasured |
Cost-effectiveness
The solution deliberately covers only the reconciliation process and replaces neither the general ledger nor group reporting. Changes in the group structure or new products require timely maintenance of the matching rules; otherwise the degree of automation drops.
Integration and operation
Transferability
The pattern of an automated reconciliation workflow transfers well to other industries where large volumes of internal or external transactions have to be matched regularly. The key is that data from several systems is brought together, matched according to clear rules and open discrepancies are worked through in a structured way.
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