Financial Analytics & Investor Clarity

What We Deliver

Your Finance team files a ticket every time they need a price update. Engineering queues it. A developer edits a Jinja macro, opens a PR, waits for review, deploys. Three days pass. The price change that should have taken five minutes took a sprint.

We know because we lived it. At a cloud security platform, pricing had been hardcoded in Jinja macros since 2021. Three versioned variants with no changelog. An undocumented 118% price increase running in production since v3.1 — creating a $472K gap that nobody noticed until we ran reconciliation.

$84 million in revenue calculations had never been cross-checked against an independent model.

What financial analytics debt looks like

It is not dramatic. It is quiet. A formula in a spreadsheet that nobody remembers writing. A revenue calculation that rounds differently than the source system. A pricing table that was “temporarily” hardcoded two years ago and now has three versions, none documented.

The cost compounds silently until someone asks a question the system cannot answer cleanly — an auditor, a board member, a potential acquirer. Then it becomes urgent, expensive, and embarrassing.

What we did for $84M in revenue

Phase one: pricing extraction. We migrated every hardcoded rate into 5 structured seed tables with full rate history preserved via temporal lookups. Reverse-engineered the undocumented 2.185x multiplier from reconciliation data. Delivered the FY27 pricing model in 9 days across 9 sequential, validated batches.

Phase two: revenue validation at scale. We ran legacy and new models in parallel across 8 product lines. Final variance: 0.002% on $84M — a $1,634 total difference, five times better than the 0.01% target. PASS/FAIL automation running continuously. Fifteen silent production bugs discovered and corrected, including the $472K rate anomaly.

Phase three: Finance self-service. We replaced 5 seed CSV files with 4 Sigma input tables that Finance edits directly — no engineering tickets, no code deploys, no waiting. Seven dimension tables power dropdown validation to prevent the silent join failures that caused bugs in the first place. Pricing updates went from days to minutes.

Beyond revenue: the full CFO stack

Revenue validation is one pattern. We also build:

P&L dashboards that pull actuals from your ERP and forecasts from your planning models into a single view — with drill-down by product line, region, or customer segment. Not a monthly static report. A live dashboard your CFO opens Monday morning.

Scenario planning for financial resilience. At eBay during COVID, we rebuilt forecasting models across five markets when every historical baseline broke. CFOs used weekly scenario dashboards — optimistic, baseline, pessimistic — to adjust budgets in real time instead of waiting for quarterly reforecasts.

M&A due diligence analytics. For eBay’s sale to Adevinta (and later Adevinta to Quinto Andar), we built the data backbone powering buyer decisions — market sizing, competitive benchmarking, portfolio performance analysis using Semrush, SimilarWeb, government data, and internal metrics.

What you walk away with

Audit-ready financial models with complete lineage from raw source to final number. Self-service tools that let Finance update inputs without engineering dependencies. Anomaly detection that flags discrepancies before they accumulate. And documentation rigorous enough for an acquirer’s due diligence team.

When this is overkill

If your revenue model is straightforward (single product, single pricing tier, no multi-currency), a well-maintained spreadsheet might genuinely be enough. This service pays for itself when you have pricing complexity: multiple tiers, usage-based billing, multi-currency, contractual overrides, or historical rate changes that nobody tracks. If your CFO says “I trust our numbers completely,” ask them when the last independent validation was run.

Questions your CFO should be able to answer

When was the last time your revenue calculations were validated against an independent model — not just checked against last quarter? If Finance needs to update a price, how many people and how many days does it take? Could you produce a complete audit trail from a raw transaction to the revenue number in your board deck — today, not after a two-week scramble?