Pillar Two & reporting · Oracle HFM
Pillar Two and global tax reporting built into HFM
Problem. An international private-banking and asset-management group ran its tax reporting through Oracle HFM, with no structured way to compute and report its Pillar Two position.
What we did. Led the Pillar Two implementation and redesigned tax reporting inside HFM. Built the GloBE data model on the existing consolidation data, added the Transitional CbCR Safe Harbour tests and put controls in place so tax numbers reconciled without re-keying.
Result. Pillar Two and routine tax reporting from the same platform finance already trusted, with an audit trail on every adjusting entry.
Direct tax & Pillar Two · Tax engine
One tax engine for reporting and Pillar Two
Problem. A global branded-products group needed its direct tax reporting and provisioning out of spreadsheets and then Pillar Two in the same place rather than in a separate model.
What we did. Implemented reporting and provisioning in a dedicated tax engine, mapping the group's hierarchy and data feeds into it. Then built a Pillar Two add-on in the same engine, drawing on the data already there.
Result. One engine for routine reporting and Pillar Two, with GloBE numbers sourced from the same data as the provision, not reconciled to it afterwards.
Tax reporting · OneStream
OneStream as the single source for global tax reporting
Problem. A large, listed global technology and internet group needed tax reporting off manual consolidation roll-ups and onto a platform that would scale and stand up to audit.
What we did. Delivered a full OneStream tax implementation: the tax data model, calculation and reporting workflows and the connection to the group's consolidation.
Result. One automated platform for provisioning and reporting, with tax numbers flowing from a single source instead of being rebuilt each period.
Indirect tax & AI · Azure
A VAT engine that flags its own errors
Problem. A high-volume business ran VAT-relevant transactions across a complex SAP and Oracle estate. Even a small error rate meant many errors and manual review could not keep up.
What we did. Built and implemented a custom VAT engine on Azure, integrated with the ERP estate, with machine learning to pick up likely errors before filing. Added the VAT workflows (CBS, VIES, ICL) and handled the effect of the Oracle Fusion migration on VAT determination.
Result. The tax team spent its review time on the transactions the model flagged, rather than sampling blind.