SaaS financial model: the drivers that matter

The LTV/CAC ratio is the most-trusted number in any SaaS financial model and the easiest to inflate. The four ways LTV lies, the drivers that don't, and why a flattering ratio can still end a company.

The LTV/CAC ratio is the most-trusted number in any SaaS financial model and the easiest to inflate. The four ways LTV lies, the drivers that don't, and why a flattering ratio can still end a company.

Generative AI should never compute your financial statements, and it would be a waste to keep it away entirely. Where the line falls — and what a chess experiment teaches about the division of labour.

An arithmetic error is a wrong cell; a structural error is a wrong theory of the business — and it computes flawlessly. Why models fail in the structure no one inspects, from LTCM to a downloaded template.

A base, optimistic and pessimistic case mean nothing if your plan is identical across all three. What Shell's scenario planning got right — and the one question to ask before you build them.

Before you deliver a financial model to a client, run it past 20 checks across integrity, traceability, robustness and deliverability — and the story of why experience alone never catches the error.

An NPV built from average assumptions is not the average NPV, and even the correct expected value is not a decision. Why the number you trust most can hide the risk that matters.

Walking a real business idea — a padel club — through FinModeler, from first assumptions to a feasibility verdict you can actually defend before committing any capital.

A base case is a single guess about the future. Monte Carlo shows you the full range of outcomes your assumptions allow — and why a positive NPV can still be a fragile bet.

Your spreadsheet is not a financial model. That sounds sharper than it is. I am not trying to dismiss spreadsheets. They are useful, familiar and still the most practical surface for many kinds of financial work. But a spreadsheet is…

We’ve been working hard to remove friction between a business idea and professional financial models by running Azure Functions financial modeling fully in memory and persisting Dataverse SDK for Python financial models as structured data. We’re calling this new approach…