This is the first candidate dataset for the ICP defined in report #5. Brighty is building a licensed EMI with a two-person compliance team, and it keeps re-posting the MLRO, CISO and chief accountant roles — meaning it can't fill its key seats through ordinary search. We took the role with the sharpest pain — AML / MLRO / Financial Crime — and built a live, verified, contactable pool from the same fintech feeder companies that already supply Brighty with people. Not a raw list scraped from open search — data engineering for a specific hiring problem: who, why now, and how we found them.
prepared 2026-06-28 · MEASURED · Outricher data
In report #5 the pattern is clear: Brighty's hardest roles are its regulatory core. The MLRO role was re-posted ×4–6, CISO ×4, chief accountant ×3. Re-posting the same vacancy over and over is a plain "can't find them" signal. Meanwhile Brighty's compliance team is just two people, and the company holds an EMI licence: the regulator requires a designated MLRO. This isn't "one more hire" — it's a structural risk.
The standard way to close a role like this — posting the vacancy or external recruiting — runs straight into a narrow, overheated market. Below are 882 targeted AML specialists already working at Brighty's feeder companies, named and verified against the data.
Current AML / Financial-Crime / Compliance specialists at Brighty's feeder companies (the ones its team already came from), in the geographies where Brighty actually hires (EU/EEA + Switzerland + UK + UAE). This is an honest floor for the named set of companies — the full graph is larger.
| Feeder company | AML core (current, in hiring zone) |
|---|---|
| Revolut | 486 |
| Crypto.com | 186 |
| TransferGo | 55 |
| Bitpanda | 54 |
| Paysera | 52 |
| Nexo | 33 |
| kevin. | 18 |
| Total unique | 882 |
A note on honesty: we deliberately excluded one feeder's large offshore AML center in South Asia (640 people) — it's a geographic mismatch for a company with hubs in Vilnius and Dubai. One feeder (a major payments service) returned no AML rows in our dataset — that's an honest gap, and we're not hiding it.
Exactly what was asked for: the best, but not necessarily the most expensive. The pool of 822 candidates is split into two primary tiers — each with its own hiring economics — plus 23 adjacent profiles (risk / fraud / onboarding) kept separate. 155 + 644 + 23 = 822.
Already held an MLRO / Head of Compliance / Compliance Director role at a licensed fintech. Can be Brighty's designated MLRO from day one — closing the regulatory requirement with no ramp-up. Of these, 95 currently hold the registered-officer title. More expensive, but you're buying readiness, not potential.
| Candidate | Current role | Feeder | Geo | Time in role | Score |
|---|---|---|---|---|---|
| Vytautas (Vito) Danta | Chief Compliance Officer Europe | Revolut | Lithuania | 5.6 yr | A+ 15 |
| Greta Leganovic | Deputy MLRO | Revolut | Lithuania | 4.3 yr | A+ 15 |
| Konstantinas Vaškevičius | Money Laundering Reporting Officer | Revolut | Lithuania | 0.7 yr | A+ 14 |
| Naledi Ngubeni | Head of Compliance - Africa Region | Crypto.com | UAE | 4.8 yr | A+ 14 |
| Elan Faidel | MLRO Germany | Revolut | Germany | 3.7 yr | A+ 13.5 |
| Laurent-Guy Germain | Head of FinCrime / MLRO - Spain | Revolut | Spain | 5.4 yr | A+ 13.5 |
| Dimitrios Sachinidis | Senior Legal Counsel and Head of Compliance - Wealth & Trading | Revolut | United Kingdom | 3.7 yr | A+ 13.5 |
| Nelson Y. | Regional MLRO APAC | Revolut | Cyprus | 5 yr | A+ 13.5 |
Top of the funnel — real people from the dataset. #1 is a Chief Compliance Officer Europe from Revolut, based in Lithuania (Brighty's regulatory home, zero relocation). Not a hypothesis — a row in the file.
AML analysts, Financial Crime Analysts, Compliance Officers, KYC Leads with tier-1 fintech training but "one rung below MLRO." The career ladder KYC → AML Analyst → AML Officer / Deputy MLRO → MLRO is standard; a strong analyst with 2–4 years is a candidate for Deputy MLRO with room to grow. Far cheaper than senior, trained to world-class standards. Of these, 446 have been in the same role for ≥3 years — a structural "stuck, ready for the next step" signal.
| Candidate | Current role | Feeder | Geo | Time in role | Score |
|---|---|---|---|---|---|
| Ana Kirejeva | Financial Crime Analyst | Revolut | Lithuania | 4.7 yr | A 12 |
| Okesola Sanusi | Support Specialist (KYC/ATO) | Revolut | Lithuania | 3.9 yr | A 12 |
| Fausta Stankeviciute | KYC support specialist | Revolut | Lithuania | 4.5 yr | A 12 |
| Ruta Prendiukaite | Financial Crime Analyst AML/CTF | Revolut | Lithuania | 6.4 yr | A 12 |
| Tatenda Chagonda | Senior Financial Crime Data Analyst | Revolut | United Kingdom | 6.3 yr | A 11.5 |
| David Backhouse | Business Transformation Manager - Financial Crime Product Expansion Operations | Revolut | United Kingdom | 4.5 yr | A 11.5 |
| Danielle Coyle | Senior Legal Counsel, Financial Crime | Revolut | United Kingdom | 5 yr | A 11.5 |
| Ryo Fujita | FinCrime - Senior Ⅱ AML/CTF SME (QC and L&D) | Revolut | Poland | 3.8 yr | A 11.5 |
CAVEAT: the middle tier fills AML Officer / Deputy MLRO, but not the licence's named MLRO — the MLRO seat itself needs Tier A. Don't mix the two roles in one funnel.
Risk / fraud / onboarding — functions next door to AML. In the dataset they're marked with a separate tag and never mixed into the target funnels A and B. Included for completeness of the pool — some of them convert into an AML track if you want them to.
Readiness to move isn't a guess — it's detected structurally from career data.
446 of 822 have been in their current role ≥3 years with no title change. At a large fintech the AML team is hundreds of people; promotion is slow and you're "one of 486." At Brighty the same person is compliance hire #3, with a direct path to Head / MLRO. This is the strongest pull trigger.
444 candidates come from Revolut, where Brighty's team already came from (9 people on the team). Outreach with the reference "your former colleague is already here and happy" removes the main barrier to moving — trust in a young company.
261 already work in crypto fintech (their feeder is a crypto company): they understand the travel rule, on-chain analytics, the crypto specifics of AML. For a crypto-fiat neobank that's a precise fit, not generic compliance.
118 are already in Lithuania — Brighty's regulatory home. A move with no relocation, with knowledge of the local regulator and the language of the Baltic licence. The lowest-friction hire there is.
By function within the pool — you can see this isn't "everyone under the word compliance" but a structured funnel.
| Function | People | Share |
|---|---|---|
| AML / Compliance specialist | 328 | 40% |
| KYC / onboarding specialist | 201 | 24% |
| Senior AML / Compliance manager | 115 | 14% |
| Registered officer (MLRO / Head of Compliance) | 95 | 12% |
| AML / FinCrime leadership | 60 | 7% |
| Adjacent (risk / fraud / onboarding) | 23 | 3% |
The full dataset: JSONL / CSV / Excel + ready-made segments. Each profile carries career depth, education, skills, location, contacts (where available), score and tier. Quality is measured, not claimed.
| Quality metric | Value |
|---|---|
| Profiles in the dataset | 822 |
| Fields per profile (min · avg · max · union) | 91 · 129 · 147 · 148 |
| Outreach-ready (email / phone / profile) | 100% |
| Email (combined) | 31% (255) |
| Hot A+/A | 185 |
We only provide email and phone from verified sources — where there is none, the value is NULL; we don't invent contacts. Depth can be raised with targeted contact re-enrichment for the tier you choose.
This is a sample of what we do for any of the 6 roles in report #5 — and for any company. Name the role and the tier, and we'll build the next dataset in the same format: a verified pool, scoring, segments, contacts, evidence.
Tell us your target company or ICP and we'll deliver the dataset plus a short analysis in this exact format — verified pool, scoring, segments, contacts, evidence.