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MonnyThe first AI money coach that actually works.
The problem we solve

3.8 billion people have no access to personalized financial coaching.

(how we got this)
Approximation. There are ~5.7 billion adults worldwide. Roughly 16% can afford a financial advisor, and ~1 billion are excluded from formal finance altogether and need inclusion first. That leaves the middle 67%, about 3.8 billion adults, with no realistic access to personal financial guidance. Sources: World Bank Global Findex, S&P Global FinLit Survey, WEF 2024. ×
World EU US
the gap ~17% 67% ~16% 29% 56% 15% 27% 46% 27% in financial trouble: debt help, budget coaching getting by, but no one to turn to well served: advisors, optimization & estate planning high financial stress no financial stress the gap ~17% 67% ~16% 29% 56% 15% 27% 46% 27% in financial trouble: debt help, budget coaching getting by, but no one to turn to well served: advisors, optimization & estate planning high financial stress no financial stress
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The market

This market is huge. (and growing)

(how we got this)
Approximation. Left: revenue of the debt collection industry alone (Cognitive Market Research). Right: personal financial advice only, hourly planning and estate work, not asset management returns (IBISWorld, Research Nester). Middle: people in the gap × $10 per person per month, our approximation of scalable AI coaching. ×
Years of income to buy a family home (US)
3.5x 4.1x 5.6x 1985 2019 2022 record high, 12.5x in LA
Source: Harvard JCHS
Money keeps getting more complex
400 pages 26,300 74,000+ 1913 1984 2014 pages of US federal tax law
up for grabs ~$31B/yr ~$460B/yr ~$117B/yr ~$9B/yr ~$25B/yr ~$30B/yr ~$12B/yr ~$14B/yr ~$60B/yr earned on financial trouble (debt collection alone) scalable coaching at just $10 per month earned on personal advice (planning & estate work) high financial stress no financial stress
Seen bigger
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HUGE!
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So, what do you say? Vote to see the results → Seen bigger HUGE!
This is how we serve them

AI money coach for the masses. (human-level coaching, app-level scale)

anatomy of our AI coach
Daily cards with financial insights · based on the user's actual transactions
👀 Budget check · 9 days left
Groceries: $80 over budget
Left unfixed, your Trip to Italy goal slips 3 weeks
Fill the gap from another budget →
doom swiping just got useful
⇆ swipe left or right
20 card types live, 100+ on the roadmap
triggers
Meaningful conversations with the AI coach
You're $80 over on groceries with 9 days to go. Dining out has $120 left. Want me to cover it from there?
Do it. Does my Italy trip stay on track?
$80 moved
🍽️ Dining out−$80
🛒 Groceries+$80
Done. Trip to Italy stays on June 14, fully funded.
+
Ask your coach anything…
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mini apps inside the coach
Mini app Live
Connect your email, surface your debts
Scans your inbox for debt-collection mail, and lets you snap a photo of physical letters with your phone. Every outstanding debt lands in one clear overview, tied to a payoff goal your coach tracks with you.
no more unopened scary envelopes
Mini app Roadmap
Benefits eligibility checker
Checks national and local benefits against your real income. Qualify for housing support? We tell you to apply. Earning more this year? We warn you to switch it off before the clawback letter arrives.
money people are owed but never claim
Mini app Roadmap
Buy now, pay later, all in one view
Every BNPL plan in one timeline, so nothing stacks up unseen. Connected to goals, so the coach can step in before the fourth installment plan becomes a problem.
54% of BNPL users are financially vulnerable
Mini app · US Roadmap
Credit card payoff coach
Sees all your cards and balances, then tells you exactly which one to pay off first to save the most interest, and keeps the plan on track month by month.
the avalanche method, without the spreadsheet
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The business model (before our banking pivot)

The bigger vision: from Monny coach to Monny bank.

1 · Get trust
Monny coach
A free AI coach that earns the user's trust, one good call at a time.
we are here, and it works
2 · Make it easy
Monny manager
AI coach + AI money manager: it doesn't just advise, it arranges.
3 · Do it for them
AI-first bank
Your money lives where your coach works. Peace of mind with your money, by default.
let's turn Monny into the Revolut of the future
Revolut
Scaled on the promise of a better user experience: quick account setup and free international transactions.
Monny
Scales on a coach and manager at the core: a Monny manager that actually manages your money for you.

"So you want to make money selling to poor people?"

Not exactly. The user never pays. The sponsor who carries the cost of financial stress does.
(how we got this)
The costs of sliding left. EU: Financieel Fitte Werknemers puts the hidden cost at €13k per financially stressed employee per year in the Netherlands; we apply it EU-wide since NL sits mid-pack on financial health. About 1 in 10 European households can't meet payment obligations, and the European Commission estimates every €1 spent on debt advice yields €1.4–€5.3 in benefits. US: Valoir 2025 ($1.1T productivity loss), Manulife John Hancock ($2,726 per employee), $160B credit card interest.
Efficiency gain: a budget coach runs €80–120 per hour; a light trajectory is ~20 hours per year (~€2,400). Monny coaches all year for roughly the price of one hour (~€120). Same year of support for ~20x less money ≈ ~1,900% efficiency gain.
The 1%: at ~€120 per user per year, a municipality needs to keep just 1.2% of users out of a formal debt trajectory (€8,000+, NL) to be ROI positive; for an employer avoiding €13k per stressed employee it's only ~0.9%. We rounded the average to 1%. Industry-wide prevention rates for tools like this typically run 3–5%, so the margin is wide. ×
Employers, coaches & non-profits: fixed subscription for all their people. €20 – €50 per employee per year · 85% gross margin.
Banks, insurers, debt collectors & municipalities: fixed base + pay-per-use. €96 per active user per year · 85% gross margin.
1 YEAR of Monny coaching
=
1 HOUR of budget coaching
~1,900% efficiency gain!
EU US
free for the user stops the slide what sliding left costs €13k per stressed employee per year, for the employer 1 in 10 EU households can't meet payment obligations €1.4 – €5.3 saved per €1 spent on debt advice $1.1T per year in lost productivity for US employers combined $2,726 per stressed employee per year, absence + lost focus $160B per year in card interest paid by US consumers 1% fewer people sliding left = ROI positive for the sponsor
Traction

The proof is in the pudding.

pudding (click the pudding to reveal)
pudding, opened
2,000
users in the first 8 weeks
31%
7-day retention
28.6%
14-day retention
14.3%
30-day retention
retention doubled in just 1 month
Deliberately engagement-first: retention gates everything else in this business. Finance apps average 4.2% day-30 retention; we run ~3x that.
and in the pipeline: 5 employer contracts signed 1 debt-collection pilot 2 non-profit pilots running advanced talks: largest NL insurer advanced talks: 1 municipality partnership talks: software provider to 320 municipalities
and it's not just the numbers:
Defensibility

Great, but what's the moat? (there are two)

1 · The harness 2 · The data 3 · vs the field
We built an AI agent harness for personal money coaching before the term "harness" even existed.
The model is 2% of the work. The moat is everything we built around it to make it a proactive coach. Swap tomorrow's best model in, the harness stays ours.
2 years of building 3 versions tested 128 user interviews
The AI harness · 13 proprietary systems AI model · swappable
Remembers everything
You never tell your story twice.
Never invents a number
Facts are computed, not generated.
Works in the background
Categorization & pattern detection, always on.
Knows the local system
Benefits, schemes and help, per market.
Takes initiative
A proactive scheduler taps you on the shoulder.
Adapts to you
Your language, reading level and pace.
Categorization nobody catches up with.
Banks
One model, ~130 fixed categories
The same for everyone: your corner store is "groceries" for everybody.
Monnybeats bank accuracy
Fully custom categories, per person
Our own few-shot LLM categorization model. The user only sees categories that match their life. No one else does this yet.
and it compounds
1Users & coaches label transactions in daily use
2Every label is human-validated: real ground truth
3The system learns per person, categorization sharpens
4More users, more validated labels, the flywheel spins faster
the most accurate personal-finance dataset, and it can't be caught at scale
Not another money chatbot. A coach that comes to you.
Our users are stressed and avoid their money. A tool that waits for the right question never gets asked one. Monny opens the conversation.
And education tools (Zogo & co) inform, but can't prove behavior change. We know: our founder built two of them.
Cleo & co
Bank app + AI chat, reactive
Smart answers, but you need to know what to ask. Built for the already-engaged user.
Monnyproactive by design
A proactive coach that creates the journey for you
Designed for low-agency users: daily cards come to you, the coach opens the conversation and walks the steps with you.
The team · I hear you thinking

"But are they the right team to scale this?"

we think so, here's why
3 founders 7 people in total Amsterdam · remote-friendly
Olivier van Dijk
Founder
Olivier van Dijk
CEO & Partnerships
2x exit as a founder, both in the personal finance space.
Life's mission: making people financially healthy. Started with education, now going after behavior.
Before founding: private equity & banking.
"education informs, but a coach changes behavior"
Don Rico Saluveer
Co-founder
Don Rico Saluveer
CTO
AI & backend engineer, AI entrepreneur. Architect of the agent harness.
Was already engineering with AI before GPT-3 was even a thing.
Passionate about physics.
Pieter Witteveen
Co-founder
Pieter Witteveen
COO
Operations & project management (Pon). Multiple ventures of his own.
Has experienced financial stress firsthand.
His personal ikigai pointed to starting a personal finance brand, on the very day Olivier asked him to join.
Michal Rada
Michal Rada
Front-end developer
10+ years React Native at startups and scale-ups.
Joined the team because of the mission.
"dedicated to the best user experience"
Sanne van der Wal
Sanne van der Wal
Product designer
Trained anthropologist: worked with people in financial stress at one of the Dutch banks.
Since become a UX/UI designer: the perfect background to design Monny's product.
Tim Bleeker
Tim Bleeker
Sales
6 years of B2B sales in the social domain.
Passionate about helping people: previously in physical health, now putting those skills to work for financial health.
"every partner enables us to have a larger impact"
Jarreau Oehlers
Jarreau Oehlers
Budget coach
Budget coach at the municipality of Hilversum, ran his own budget coaching practice before.
Ideal expertise on our ICP and what they need.
Tests our coaching-platform proposition and sells to municipalities.
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The round

How much we're raising, and what it buys.

Status
€850K pre-seed raised last year, led by Shaping Impact Group (VC).
In the room
In conversation with Dutch strategics: insurers & banks.
The playbook
NL first: Europe's strictest market, sponsor model proven. US next: Plaid-linked from day one, entering through the same employer channel.
The details are one email away.
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talk soon
Monny Financial Technology B.V. · AmsterdamRegulated by DNBBank-linked via PlaidAnonymous & aggregated by designolivier@getmonny.com