Theses

Six theses. Four of them are hiring founders now.

A thesis is a claim we are willing to fund. Each one sits in financial services or the infrastructure underneath it, and each one names a market, a failure inside it, and the reason the window is open now. You bring the market knowledge. We build the company around it.

You do not need to have founded anything before.

Hiring now

Identity as a state, not an event

The market: Video identification costs a few euro per completed check, needs a person in the loop, and loses a meaningful share of applicants at the moment they most want to sign up. Its real defect is conceptual: it produces a snapshot. Sanctions status, beneficial ownership and signing authority all change between snapshots, so firms run re-verification campaigns that are expensive, irritating, and structurally late. Verifying a company is worse than verifying a person — registers across jurisdictions, ownership chains, signing authority, mostly by hand.
Why now: European law is replacing the national anti-money-laundering patchwork with a single rulebook, and a certified digital identity wallet arrives alongside it. One product will serve every member state instead of twenty-seven configurations, electronic identification will rank above video, and the rules put an outer limit on how stale customer data may be. The incumbents are priced per check, so continuous verification is the one thing their business model cannot want.
What we provide: The company, the capital, the regulatory roadmap, and every function that is not product and market.
Looking for: Ten years in compliance, onboarding or identity at a bank, an insurer or a regulated fintech. You know where onboarding breaks because you have watched it break.

Hiring now

Credit risk measured in days, not letters

The market: B2B credit assessment sits with a handful of bureaus selling a grade on a proprietary scale, built mostly on filed annual accounts that are six to eighteen months old by the time anyone uses them. It fails three ways at once: it is late, it ranks rather than measures, and it carries no horizon — a credit limit says how much, never when. The academic alternative needs listed equity, and almost all trade credit risk sits with unlisted companies. Trade credit insurers run private models and withdraw cover without warning, which is the opposite of a planning tool.
Why now: A model of how long a company can last needs cash in and cash out, not profit — and those inputs now exist outside the company’s own accounting department. Observed payment behaviour between counterparties, bank transaction data where the counterparty consents, and electronic invoicing mandates turning invoice flows into machine-readable streams. Private credit has meanwhile grown faster than its risk infrastructure and needs a view it does not buy from a bureau.
What we provide: The company, the capital, the data partnerships, and every function that is not product and market.
Looking for: Ten years in trade credit insurance, risk modelling, or receivables. You have explained a credit decision to someone who disagreed with it.

Next, once the credit thesis has customers

The forward cash view, live

The market: Treasury systems serve the top of the market: six-figure licences, implementations measured in quarters, and a treasury team to run them. Below that line the forecast lives in a spreadsheet owned by one person, refreshed monthly at best, and backward-looking by construction. The gap is companies between 20 million and 1 billion in revenue — complex enough to run several banks, currencies and legal entities, too small to carry a treasury system. The current crop of forecasting tools predicts payment dates and stops there, which is the wrong end of the problem. The forecast is not the product. The decision it triggers is.
Why now: Multi-bank balances and transactions, and mid-market accounting systems, are reachable by interface without a project. The hard part was never the time series — it was reconciling heterogeneous, badly labelled, multi-entity, multi-currency data into one structure, and that is what language models now do well. Rates are above zero again, so idle cash and an unplanned overdraft both cost visible money, and faster settlement has compressed the float that used to hide planning errors.
What we provide: The company, the capital, the banking interfaces, and every function that is not product and market.
Looking for: Ten years in corporate treasury, a CFO office, or cash management at mid-market scale. You have built the spreadsheet this replaces.

Next, once the cash view has customers

From exposure to instrument

The market: A mid-size finance chief facing a three million euro gap in sixty days has a dozen live options: overdraft, revolver, factoring, reverse factoring, receivable sale, sale-and-leaseback, inventory finance, private credit, a shareholder loan, or simply stretching payables. Almost nobody compares them. The decision goes to the bank that happened to call, or to last year’s habit. Hedging is the same story with worse optics: forwards, options, collars and swaps quoted at a spread the client has no way to benchmark, so companies hedge the wrong exposure or decline to hedge at all. Comparison layers exist for consumer credit. Nothing exists that knows the exposure, spans funding and hedging, and executes.
Why now: Rate and currency volatility put a price back on a badly funded or unhedged position. Lending marketplaces, currency platforms, leasing providers and receivable platforms can all be queried and transacted programmatically — what is missing is the layer that decides. And the part that made this undoable is now tractable: exposures hide in credit agreements and their covenants, in leases, and in supply contracts with currency and index clauses. Those documents can finally be read at scale.
What we provide: The company, the capital, the provider relationships, and every function that is not product and market.
Looking for: Ten years in corporate banking, structured finance or treasury advisory. You have sat on both sides of one of these decisions.

Open, start depends on the licensing path

Tokenization without the blockchain

The market: A decade of capital went into chains, token standards and custody, and issuers still do not care. They care that issuing a bond or a fund unit takes weeks and a chain of intermediaries, each charging basis points for what is a database write. The fee floor makes issuance below roughly 50 million uneconomic, which pushes mid-size issuers back into bilateral bank debt. The blockchain-native competitors cannot serve those issuers either: institutional buyers will not hold crypto securities, custody is unresolved, and the regimes that permit them cap size. The demand is for cheap, fast, legally clean issuance. Nobody is bidding for decentralization.
Why now: German law has made a register entry legally constitutive for several years, through a central register that requires no blockchain at all. The scope has widened twice and now covers the full capital stack. The euro cash leg settles in real time, so delivery against payment no longer needs a token to be atomic. And the drafting cost — terms, prospectus, register entries — has collapsed. The window is the gap between a legal regime that is finished and an incumbent stack that has not repriced.
What we provide: The company, the capital, the licensing work, and every function that is not product and market.
Looking for: Ten years in debt capital markets, paying agency, or securities operations. You know what the intermediaries actually do.

Open, start depends on the register thesis

Capital markets services at a tenth of the cost base

The market: A bank is three things bundled together: a balance sheet, a licence, and a very expensive layer of people. Most fee income is earned in that last layer, and almost no capital is tied up there. The pattern repeats across every capital markets service — the product is only economic above a certain deal size, because the human process carries a fixed cost. A 15 million euro bond issue is declined not because it is unattractive but because it does not cover the analyst hours. Drop the fixed cost and the threshold collapses, which opens a segment that has never been served rather than one that has to be won.
Why now: Models crossed the threshold on exactly the work that dominates these cost bases: document review, diligence, drafting, structured extraction, synthesis. The incumbents cannot follow, because their cost base is their headcount, and compressing it breaks both their compensation model and the revenue attribution that holds their desks together. We start with debt capital markets, on the register the previous thesis builds.
What we provide: The company, the capital, the register, and every function that is not product and market.
Looking for: Ten years on a debt capital markets desk, in syndication, or in issuance advisory. You have run the process you are about to automate.

The process

How this works

01
One conversation
Forty-five minutes. You tell us where our reading of the market is wrong, and we find out whether the thesis survives contact with someone who knows the ground.
02
Then the plan
If it holds, we write the implementation plan together — the product, the first customers, the regulatory path, the resourcing. This happens before anyone resigns from anything.
03
Then the company
We incorporate, we fund, and we take over finance, legal, people, controlling and regulatory from the first day. You build the product and the market.

The bottleneck is no longer money. It is access and timing.

Write to us. One email, in your own words, about the thesis you want. We read every one.

partner@fintech-studio.com