AI-powered revenue forecasting and scenario modelling for an EMEA financial services firm

The Challenge

Revenue planning ran on quarterly Excel models the finance team updated by hand. By the time a cycle was finished, the assumptions behind it were already months old. There was no way to test what a product launch or a shift in market conditions would do to the numbers — not without starting a new model build from scratch. Budget decisions were being made on data that had a lag baked into it.

Our Approach

The first step was getting the underlying data in order. Revenue history from the CRM and billing system was cleaned and structured, then enriched with external economic indicators and pipeline signals.

A model trained on four years of revenue data now produces a 12-month rolling forecast, updated weekly. Confidence intervals come as standard — the goal was to give finance a range to plan against, not a single number to dispute.

A scenario layer was built on top so the finance and strategy teams can adjust assumptions directly — new product, market contraction, client expansion — and see the revenue impact themselves without going back through the data team each time.

Key Deliverables

• AI revenue forecasting model with a 12-month rolling horizon, refreshed weekly
• Structured data pipeline connecting CRM, billing, and external market indicators
• Self-serve scenario modelling interface for finance and strategy teams
• Confidence interval outputs for range-based planning
• Forecast vs. actuals tracking with ongoing model performance reporting

“We stopped debating the numbers and started acting on them. That's a different kind of planning meeting.”

— CFO, EMEA Financial Services Firm

Results

Engagement

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