Problems › Where Should We Invest Next? › Fintech
Capital allocation goes wrong when the loudest line gets funded rather than the one with the best return on the next dollar. This page works through it for fintech companies specifically — including an unedited excerpt from a real analysis of a fintech.
Capital allocation goes wrong when the loudest line gets funded rather than the one with the best return on the next dollar. 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.
Most businesses allocate by history and by advocacy: the lines that got money last year get it again, and the person who argues best gets the increment. Neither has anything to do with where the next dollar earns most.
The analysis that helps ranks each line on two things — what it returns on incremental investment, and how durable that return is. A line that returns well but decays in eighteen months is a different proposition from one that returns modestly for a decade, and treating them as comparable is how businesses end up funding decline.
The output should be a sequence with a stopping rule, not a budget split. Which one first, what it funds next, and the observation that would say the sequence is wrong.
These three together are the signature. One on its own usually points somewhere else.
✓ Budgets are set by last year plus a percentage
✓ Nobody can rank the lines by return on incremental investment
✓ Investment decisions are defended by strategic importance rather than by arithmetic
The move that usually makes it worse. Spreading capital evenly to keep the peace, which underfunds the one thing that would have compounded.
It is for you if you run or finance a fintech and budgets are set by last year plus a percentage. 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.
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.
Excerpt from a real Percision run · Customer Value Architecture · sample company profile
The move. Triple the lending book from $110M to $260M using existing merchant data and warehouse capacity.
The leak it closes. Reduces partner-rev-share leakage by shifting revenue mix from 78% payments (subject to 26% rev-share) to 38% lending (zero rev-share)
The assumption it rests on. Charge-off rate remains below 9.0% covenant through Month 18 — the engine put the probability at 0.82.
| Investment required | $0 incremental equity; utilizes existing $40M warehouse headroom and $52M cash runway |
| Expected return | Risk/Reward 2.8 on $28M upside versus $9.9M downside; payback <6 months on incremental contribution |
| Revenue, year 1 | $98M total net revenue (+17% YoY) |
| Revenue, year 2 | $112M total net revenue (+14% YoY) |
| Revenue, year 3 | $126M total net revenue (+13% YoY) |
| Exit criteria | Terminate move if charge-off exceeds 8.5% for two consecutive quarters OR if any vertical-SaaS partner terminates integration |
This is one move out of a full analysis. Read a complete report — every page, no email required.
This question routes to Growth Portfolio Framework, 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.
Price the durability explicitly. A return that decays needs a stated half-life; once each option carries one, options with different horizons become comparable rather than a matter of taste.
Usually the strongest, because that is where a marginal dollar compounds. Fixing the weakest is worth doing when it is a constraint on the strongest, and not otherwise.
Then decide on reversibility. When two options return similarly, take the one you can stop, because the value of the information you buy exceeds the difference in the estimates.
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.
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.
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.
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