Estimated annual leak · modeled range
$0a year
Modeled midpoint, prorated. Not a measured loss.
Fintech · margin leak estimator
How much is your Fintech marketing leaking?
Use your revenue, marketing spend and answers to explore a modeled annual opportunity range. Free, with no login or account access.
Use the results on your own, or choose a paid audit or a fit call. Both next steps are optional.
Free · No login · Nothing leaves your browser
Model reference: $83k/yr. Published cases: 7, lower median $83,000/yr. Separate acquisition from risk adjusted contribution, fraud, servicing and retention. Lending, payments and wealth businesses have different economics; the shared model does not capture those differences.
Live reading · updates on every answer
Leak risk score
Appears after your first answer. Based on your answers, not on the dollars.
Pick an industry to sharpen the range.
Directional model output. Not a measured loss or promised recovery. Formula and rates are disclosed below.
Step 1 of 7 · Tell us about the Fintech business
Rough numbers are fine.
Tell us about the Fintech business
Three quick inputs set your baseline. Rough numbers are fine, and nothing leaves your browser.
Quick start
Industry
Advanced: blended ROAS and site conversion rate (optional)
Optional, and it stays in your browser. Either number narrows your range instead of widening it: the model stops guessing at your efficiency and uses yours.
Choice steps advance on click. Nothing leaves your browser.
In their words · 6 Fintech client statementsAll 60 client statements →
FINTECH
$96k a year of wasted spend cut in 7 days
App installs that funded a real account: 24% → 63%
“Installs looked great and funded accounts stagnated. David followed sign ups through to funding, and the bonus was buying registrations from people who claimed it and never transacted. Incentives now pay on activation, not the download.”
VP of Growth · Fintech · Consumer
Written approvalUnder NDA7 days to findings
David JacksonSenior Auditor · signed this audit offFINTECH
−27% risk adjusted CAC in 7 days
Risk adjusted acquisition cost per loan on the high default channel: $540 → $400
“Our cheapest channel was our worst credit. David split default rates by acquisition source: the low CAC channels brought borrowers who defaulted materially more often. Budget now follows risk adjusted cost per loan, not just CAC.”
CRO · Fintech · Lending
Written approvalUnder NDA7 days to findings
David JacksonSenior Auditor · signed this audit offFINTECH
$83k a year of wasted spend cut in 7 days
Referral rewards on genuine, nongamed volume: 67% → 98%
“Referral payouts grew faster than real users. David examined the volume behind the rewards: self referrals through second accounts, circular trades, wash volume. Integrity checks now run before any payout; gamed rewards were clawed back.”
Chief Risk Officer · Fintech · Exchange
Written approvalUnder NDA7 days to findings
David JacksonSenior Auditor · signed this audit offFINTECH
$83k a year found in 7 days
Interchange margin on the worst channel: +0.4% → +2.4%
“Every channel cost the same per merchant, so we treated them as interchangeable. David split profitability down to the interchange line: some channels brought merchants who earned us a fraction. Budget now follows margin, not just CAC.”
VP of Risk · Fintech · Payments
Written approvalUnder NDA7 days to findings
David JacksonSenior Auditor · signed this audit offFINTECH
$72k a year found in 7 days
Portfolio margin across the product mix: 11% → 17%
“One flat commission across very different products steered brokers to the wrong mix. David set commission against each product’s margin and loss ratio; thin lines were being sold near unprofitable. Commission now follows the margin band.”
VP of Risk & Growth · Fintech · Insurtech
Written approvalUnder NDA7 days to findings
David JacksonSenior Auditor · signed this audit offFINTECH
$61k a year found in 6 days
Support cost vs fee on small accounts: 140% → 85%
“Small accounts used as much planner time as large ones for a fraction of the fee. David modeled cost to serve by tier: below a certain balance the support ran at a loss. Human planning now sits with the tiers whose fee covers it.”
Head of Product · Fintech · Wealth & robo
Written approvalUnder NDA6 days to findings
David JacksonSenior Auditor · signed this audit offThe calculator is free. An optional paid audit checks your account data and produces evidence for its findings.
What is the next step?
Keep your estimate, explore the case studies or request a paid audit. The calculator does not connect to your accounts. A fit call can help you assess whether an audit is appropriate.
Model assumptions and limitations
This calculator applies model assumptions to your inputs. Its range, comparison position and score are directional scenarios, not measured account losses, verified peer percentiles or a recovery promise. The industry reference amounts are model references, distinct from the lower medians of published case figures. Underlying calibration budgets and validation evidence are not published.
- Monthly marketing spend is multiplied by 12 and the selected industry rate band. Monthly revenue is multiplied by 12 and 0.84% to 1.63% for the second term. These two modeled terms are added, adjusted by your answers, and rounded.
- Higher spend changes the marketing term; higher revenue changes the pricing, margin and retention term. These terms may describe related economic effects, so their sum is a scenario for investigation, not additive proven savings.
- The comparison uses the marketing term only. Its reference is annual marketing spend multiplied by the middle point of the industry model curve. A position from 10 to 90 on that curve is not an observed peer percentile.
- The 0 to 100 score summarizes the selected answers. Category scores reflect allocated shares of the estimated midpoint, not independently measured health.
- Optional ROAS and conversion inputs scale the range against model reference values and narrow it by a fixed factor of 0.70 before rounding. A narrower interval does not establish greater statistical confidence.
- When spend exceeds half of revenue, a midpoint limit of 6% of annual revenue can activate. Rounding and minimum interval width still apply. This is a model safeguard, not an observed business limit.
Input and coefficient sensitivity are model behavior. Calibration periods, eligible budgets and validation errors are unavailable in the published cases.
Directional model estimates, not a diagnosis of your accounts. Nothing leaves your browser to produce this result.
Behind the Fintech estimate
What the model assumes for Fintech
The Fintech model reference is $83k a year. Among the five modeled categories, Fintech gives Attribution & tracking a 15% heavier weight in the category split and a head start as the first area to investigate when your answers point two ways.
The 7 published Fintech cases are a separate statistic: a lower median annual highlight figure of $83,000, computed from the cases listed below, not from the model. The largest of them is Incentive spend acquired users who never funded, −$96k a year, found in 7 days.
What the Fintech estimator asks
Every version of the calculator starts from monthly revenue and monthly marketing spend. Three of the seven questions then carry Fintech options, listed here as the wizard shows them. Each option still maps to the same five leak categories, which is what keeps a Fintech estimate comparable with any other.
Where does most of your marketing budget go?
The Fintech channel mix. The answer moves weight between wasted paid spend and attribution.
- Paid search & LinkedIn
- SEO & content
- Outbound & ABM (SDRs): Sequences, SDRs & target account lists
- Product led / referral: The product & happy users do the selling
- Events & partnerships
- Honestly, I’m not sure
How do you mainly make money?
The Fintech revenue model. The answer moves weight between pricing and retention.
- Subscription / seats
- Usage / consumption based: Billed by what customers consume
- Transaction / interchange fees: You earn a slice of each payment processed
- Freemium → paid
- A mix
- Not sure / it varies
Where do you suspect you lose the most?
The Fintech vocabulary for the five categories. The answer orders the checklist; it never moves the score.
- Spend on signups that never transact
- Attribution & tracking
- Signup, KYC & first transaction conversion
- Pricing, packaging & discounting
- Churn & expansion (NRR)
- Not sure: that’s why I’m here
Tracking and the optional inputs
Fintech answers the tracking question on the web analytics scale, from a modeled, reconciled first party setup down to patchy or not sure.
Advanced, optional: a blended ROAS, placeholder 4.0, and a site conversion rate, placeholder 1.5%. Either one narrows the Fintech range instead of widening it.
Three Fintech leak patterns from the published cases
Each card names the cases it rests on; open one for its evidence. Together the cards cover all 7 published Fintech cases. The Fintech marketing audit page explains each pattern and shows the before and after of its largest case.
Acquisition
Paying for sign ups, not profitable users
4 of the 7 published cases · $57k to $96k a year
- Incentive spend acquired users who never funded, −$96k a year
- CAC payback was twice what the board believed, +$57k a year
- Interchange margin varied wildly by acquisition channel, +$83k a year
- Acquisition ignored default rate by channel, +$88k a year
Incentives and commissions
Rewards paid regardless of what they bring
2 of the 7 published cases · $72k to $83k a year
Cost to serve
Service costs above what small accounts earn
1 of the 7 published cases · $61k a year
What an audit checks after a Fintech estimate
- CAC scored on funded, transacting users
- Referral payout reconciliation against genuine activity
- KYC drop off funnel economics
- Lifecycle coverage of the compliant, funded cohort
- Attribution integrity across app stores, paid and referral
The estimate points at a category; the audit tests these 5 Fintech checks against your own account data. Compare industries in the 2026 benchmark.
Why trust the estimate
A wasted ad spend calculator with explicit assumptions.
01
Industry model assumptions
The calculator uses industry rates and your inputs. Published case lower medians are shown separately so you can compare their definitions.
02
Understand the range
The interval describes a model scenario. It does not establish the percentage of comparable businesses that achieved that result.
03
The audit makes it real
An estimate can’t be acted on by itself. The audit names each leak, proves it with your data and hands you the fix. $10,000 to $50,000 of findings, or your money back.
Next step, optional
Turn estimates into evidence.
Fixed fee. 5 to 7 working days. $10,000 to $50,000 of findings, or your money back.
Questions about the Fintech estimator.
Is the estimator really free, and what’s the catch?
Yes. The Fintech calculator uses your inputs and the Fintech model assumptions, with no account access. You can keep the results or choose an optional paid audit or fit call.
Does the calculator need access to my ad or analytics accounts?
No. It runs entirely in your browser from a few situational inputs, with Fintech preselected as the industry. No logins and no account access, by design.
How accurate is the estimate?
It is a directional model using your inputs and Fintech industry assumptions. Its range and comparison position are not verified peer percentiles or measured account losses. The 7 published Fintech cases are a separate statistic, with a lower median annual highlight figure of $83,000 and a largest published case figure of $96,000 a year. An audit checks your own evidence.
What does the Fintech estimator ask that the general calculator does not?
Three of its seven questions carry Fintech options. Where the budget goes offers Paid search & LinkedIn, SEO & content, Outbound & ABM (SDRs), Product led / referral and Events & partnerships. How you make money offers Subscription / seats, Usage / consumption based, Transaction / interchange fees, Freemium → paid and A mix. Where you suspect the loss offers Spend on signups that never transact, Attribution & tracking, Signup, KYC & first transaction conversion, Pricing, packaging & discounting and Churn & expansion (NRR). Each answer still maps to the same five leak categories, so a Fintech estimate is comparable with any other.
Why does the Fintech calculator ask for a blended ROAS?
It is optional. The Fintech version offers two advanced inputs, a blended ROAS with 4.0 as the placeholder reference and a site conversion rate with 1.5% as the placeholder. Either number narrows your Fintech range rather than widening it, because the model stops guessing at your efficiency and uses yours. Leave both empty and the range stays wider.
Fintech wasted ad spend calculator: model and case evidence
This calculator applies model assumptions to your inputs. Its range, comparison position and score are directional scenarios, not measured account losses, verified peer percentiles or a recovery promise. The industry reference amounts are model references, distinct from the lower medians of published case figures. Underlying calibration budgets and validation evidence are not published.
Separate acquisition from risk adjusted contribution, fraud, servicing and retention. Lending, payments and wealth businesses have different economics; the shared model does not capture those differences.
Scroll horizontally to compare all columns on a narrow screen.
| Industry | Published cases | Model reference / year | Case lower median / year |
|---|---|---|---|
| Fintech | 7 | $83k | $83,000 |
The population is the 74 published case studies, with one selected highlight figure per case. It is not a representative sample of all SMBs or a total of every finding in each audit. A lower median is the middle value after sorting, using the lower of the two middle values for an even count. Published annual figures include different outcome types; they are not all collected cash, profit or recurring savings. Case publication dates do not establish common observation, implementation or recovery periods; use each case for its supported timing and outcome.