Operational Excellence Consulting
in Fintech

The short answer

Improvement programmes reliably improve the merchant features and reporting layers that were never the constraint, because those are the places that are easiest to improve. For fintech companies, this shows up in a particular place. The numbers that carry the answer are blended take rate and charge-off rate, and the complication specific to this industry is that lending fixed the P&L and converts revenue worth a 7x multiple into revenue worth a 2x multiple. The general version of this problem and the one you are actually in have different first moves.

Every fintech has one thing that limits TPV at any given time — a risk model, a warehouse facility, an approval rule. Work done anywhere else does not increase blended take rate or contribution margin; it increases the volume waiting at the constraint. This is not controversial and has been understood for forty years, and improvement programmes still routinely violate it, for a structural reason: initiatives are generated by the teams that volunteer, and the constrained team is by definition the one with no spare capacity to volunteer.

The result is a programme with excellent hygiene and no effect. Features ship, dashboards appear, charge-off tracking is refined, and net revenue stays the same as last year. Because the activity is real, the response to flat results is usually more initiatives, which consumes more of the capacity of the teams that were never limiting anything.

The second thing that hides in these programmes is that the constraint is often full of the wrong work. A risk engine running at capacity on loans that convert revenue to a 2x multiple does not have an efficiency problem; it has a selection problem wearing an efficiency costume. No amount of method fixes that, and method applied to it makes the low-multiple work cheaper to produce, which increases the volume of it.

Efficiency Transformation Strategy (catalog id T12) starts from the constraint and what occupies it — TPV, contribution margin per unit of the scarce resource, and what would have to be true for the next unit of warehouse capacity to pay at the higher multiple. Where the answer is that the process genuinely is the limit, a lean programme is the right purchase and the analysis will point at where to aim it.

How to tell this is actually your problem

These three together are the signature. One on its own usually points somewhere else.

✓ A large number of completed improvement initiatives and unchanged TPV or blended take rate
✓ Nobody agrees on which step limits contribution margin, or the answer changes by team
✓ The most improved areas are the ones with the most available time, such as merchant support or onboarding rather than risk or warehouse allocation

The move that usually makes it worse. Rolling out a method across the whole operation, which spends the scarce improvement capacity on the steps that were never limiting blended take rate or contribution margin.

Who this is for — and who it is not

It is for you if you run or finance a fintech and a large number of completed improvement initiatives and unchanged output. It is the situation where the numbers are available but nobody has put them in an order that produces a decision.

It is not for you if Percision is the wrong tool if you already know the answer and only need execution capacity, or if the business is pre-revenue — then the constraint is evidence about the market, not analysis of your own figures. Percision is not a lawyer, tax advisor, auditor, licensed appraiser, clinical or regulatory filer, or an AI implementation shop. It does not do HR casework, creative-only brand work, or impersonate a named consulting firm. It is a strategy analysis engine — not a template library. Also wrong if you need facilitation, politics, or someone to sit with a lender or buyer. Those are human jobs.

Percision is not a lawyer, tax advisor, auditor, licensed appraiser, clinical or regulatory filer, or an AI implementation shop. It does not do HR casework, creative-only brand work, or impersonate a named consulting firm. It is a strategy analysis engine — not a template library.

What this looks like when the analysis is actually run

Below is an excerpt from a real run of this analysis on a fintech. It is a sample profile rather than a customer, and it is unedited engine output — this is the format you get, on your own numbers.

The subject is Verrano Pay, a sample company profile used for testing rather than a customer — $84M net revenue, 28,000 merchants, $9.4B of payment volume.

This is one move out of a full analysis. Read a complete report — every page, no email required.

What the engine does with this question

This question routes to Efficiency Transformation Strategy, one of 29 engagements the platform runs. For fintech companies it works through blended take rate, charge-off rate, contribution margin and CAC by channel, then produces the sequence rather than a list of options — which move first, what it funds, and the observation that would say the sequence is wrong.

You watch the analysis get built before paying anything. Read a complete report here if you would rather see the depth first.

Questions people ask about this

Is lean or six sigma the better method?

They solve different problems and the choice matters less than the aim. Lean attacks flow and waiting; six sigma attacks variation and defects. If your problem is that things sit in queues, lean. If it is that outputs are inconsistent, six sigma. If you do not yet know which, the method choice is premature and either one will produce activity.

What does an operational excellence programme cost?

Assessment phases run roughly £40k–£120k. Full deployment with embedded practitioners and training is commonly £250k–£1m over a year, often quoted against a promised multiple of savings. Ask how the baseline is set and who verifies the savings, because self-verified benefits are the norm and they are systematically generous.

Can this be done without consultants?

The method can — the material is public and cheap, and plenty of firms have taught themselves. What is genuinely hard to self-supply is the outside judgement about where to aim it and the willingness to say that a favoured department is not the problem. That is the part worth buying, and it is a much smaller purchase than a deployment.

Is this different in fintech than in other industries?

Materially, yes. Lending fixed the P&L and converts revenue worth a 7x multiple into revenue worth a 2x multiple — which changes both the diagnosis and the order of the fixes. The metrics that decide it here are blended take rate, charge-off rate, contribution margin, and an answer built on industry-general benchmarks will usually point at the wrong one first.

What data do I need before this analysis is worth running for a fintech?

Less than most people expect. Your last twelve months of revenue and cost split the way you already split it, plus whatever you hold on blended take rate and charge-off rate. The analysis is explicit about what it is assuming where your data stops, which is more useful than waiting for numbers you may never have.

When is Percision the wrong tool?

Percision is the wrong tool if you already know the answer and only need execution capacity, or if the business is pre-revenue — then the constraint is evidence about the market, not analysis of your own figures. Percision is not a lawyer, tax advisor, auditor, licensed appraiser, clinical or regulatory filer, or an AI implementation shop. It does not do HR casework, creative-only brand work, or impersonate a named consulting firm. It is a strategy analysis engine — not a template library. Also wrong if you need facilitation, politics, or someone to sit with a lender or buyer. Those are human jobs.

Does Percision replace a lawyer, tax advisor, auditor, or AI implementation team?

Percision is not a lawyer, tax advisor, auditor, licensed appraiser, clinical or regulatory filer, or an AI implementation shop. It does not do HR casework, creative-only brand work, or impersonate a named consulting firm. It is a strategy analysis engine — not a template library.