Synthetic KYC Data for Compliance Teams
Your Compliance Systems Are Tested Against Fiction
Every compliance team hits the same wall. You need realistic KYC profiles to test your onboarding workflows, train your risk models, and validate your screening systems. But the data you actually need — complex, high-risk profiles with PEP exposure, multi-jurisdictional structures, and elevated risk ratings — is exactly the data your legal team will never let you touch.
So your dev team generates random data. Names that don’t match nationalities. Risk ratings uncorrelated with PEP status. Source-of-wealth fields that say “business” for every profile. Sanctions screening results that are uniformly clean.
You test against fiction. And when a real UHNWI with a three-layer beneficial ownership structure hits your onboarding workflow in production — it breaks where it costs real money and real regulatory exposure.
The fines speak for themselves:
| Institution | Violation | Fine | Year |
|---|---|---|---|
| Starling Bank | AML control failures | £29M | 2024 |
| Block Inc (Square) | Transaction monitoring gaps | $120M | 2024 |
| OKX | KYC/AML deficiencies | $504M | 2025 |
| N26 | Compliance system failures | €9.2M | 2024 |
| Revolut | AML remediation orders | €3.5M | 2024 |
| Monzo | Compliance control gaps | £21M | 2024 |
Every one of these started with inadequate testing. Systems that passed QA with clean, simple profiles — then failed when real-world complexity arrived.
We built the solution.
29 Fields That Actually Correlate
Generic synthetic data generators produce each field independently. A 25-year-old with $50M net worth and a fast-food employment sector. A “Very High” risk rating with a “Clear” sanctions screening result and “Standard” due diligence level.
Our KYC/AML Enhanced datasets contain 29 interlocked fields across three layers — and every field correlates with every other field.
Identity Layer (14 fields)
Culturally accurate identity data across 6 geographic niches. A Swiss private banker doesn’t share name patterns with a Saudi merchant family or a Silicon Valley founder. Names, nationalities, tax residencies, and jurisdictions are internally consistent — generated from 31 cultural archetypes.
Financial Layer (5 fields)
Net worth follows verified Pareto distributions — because real wealth follows power laws, not normal curves. Asset allocations reflect actual investment patterns: a Pacific Rim semiconductor dynasty allocates differently than a LatAm agribusiness baron. Balance sheets are algebraically locked: assets minus liabilities equals net worth, every time.
KYC/AML Compliance Layer (10 fields)
This is where generic synthetic data fails:
- Risk classification correlated with archetype, geography, and PEP status
- PEP and sanctions screening distributed realistically across profiles
- Beneficial ownership structures — direct, trust, holding company, foundation
- Enhanced due diligence triggers — present only when risk warrants them
- Source of wealth and source of funds — distinct narratives, archetype-appropriate
- Periodic review dates — realistic review cycles aligned with risk tier
A Very High risk profile has a PEP-Adjacent status, an Enhanced CDD level, a specific EDD trigger reason, and a source-of-wealth narrative that explains why the risk rating is elevated. Every profile is a coherent entity, not a random assembly of fields.
Six Geographic Niches
KYC requirements vary dramatically by client geography. A compliance team testing European private banking workflows needs different profiles than one testing Middle Eastern sovereign wealth structures.
| Niche | Profile Type | Key KYC Characteristics |
|---|---|---|
| Silicon Valley | Founders & VC | Concentrated equity, liquidity events, startup holding structures |
| Old Money Europe | Dynasties & Private Banking | Multi-generational trusts, conservative allocation, Liechtenstein foundations |
| Middle East | Sovereign Families & Merchant Houses | Energy wealth, Sharia-compliant structures, philanthropic vehicles |
| LatAm Barons | Agribusiness & Infrastructure | Commodity-linked wealth, political exposure, cross-border holdings |
| Pacific Rim | Semiconductor & Shipping Dynasties | Industrial conglomerates, APAC structures, family governance |
| Swiss-Singapore | Offshore Wealth & Multi-Family Offices | Multi-jurisdictional structures, privacy vehicles, custodian networks |
Purchase a single niche or a mixed dataset across all six.
Born Synthetic vs Anonymized KYC Data
Most synthetic data starts from real customer records — then strips, masks, or transforms them. The original data is still the foundation. Re-identification attacks on anonymized financial data have been demonstrated by multiple research teams.
Born-Synthetic data is different. There is no original. Every profile is generated from mathematical distributions and cultural models. No real person’s data was ever input, processed, or referenced.
| Factor | Anonymized Data | Born-Synthetic Data |
|---|---|---|
| Privacy risk | Residual — re-identification documented | Zero — no real person exists |
| GDPR status | Contested — regulators disagree | Clear — not personal data by construction |
| Legal review required | Weeks to months | None |
| Data volume | Limited by source dataset | Unlimited — generate to specification |
| Field correlations | Degraded by anonymization | Mathematically preserved |
| Cultural accuracy | Generic | 6 niches, 31 archetypes |
| Provenance documentation | Derived lineage | Certificate of Sovereign Origin |
The Compliance Advantage
Born-Synthetic KYC data is not personal data under any regulatory framework. It was never personal data. There is no “original” to trace back to.
- GDPR Article 25 — Data protection by design, achieved by construction
- EU AI Act Article 10 — Training data governance with fully documentable provenance (enforcement August 2026)
- DORA Articles 24-25 — Resilience testing with realistic but safe data (in force January 2025)
- PCI DSS 4.0 Req 6.5 — No real financial data in test environments (mandatory March 2025)
Your compliance team can use this data without a single privacy review. That’s not a feature — it’s the architecture.
Use Cases
Onboarding workflow testing
Feed synthetic KYC profiles through your onboarding pipeline. Test how your system handles high-risk clients, PEP-adjacent structures, and complex beneficial ownership. Find the edge cases before they find you in production.
AML model training
Train transaction monitoring and suspicious activity detection models on diverse, realistic profiles. Our KYC data provides the population diversity that production data lacks — especially for UHNWI segments that represent your highest-risk, lowest-volume clients.
Vendor evaluation
Evaluating a new KYC platform? Feed it synthetic profiles from all six niches and compare how different vendors handle the same complexity. No NDA required. No production data exposed.
Regulatory sandbox testing
DORA requires resilience testing with realistic but safe data. PCI DSS 4.0 bans real payment data in test environments. Born-Synthetic KYC data meets both requirements by design.
Demo and training
Show your team, your board, or your regulators how your systems handle complex client profiles — without exposing a single real client record.
Pricing
| Tier | Records | Price | Per Record |
|---|---|---|---|
| Compliance Starter | 1,000 | $999 | $1.00 |
| Compliance Pro | 10,000 | $4,999 | $0.50 |
| Enterprise | 100,000 | $24,999 | $0.25 |
All tiers include: CSV delivery, Certificate of Sovereign Origin, all 29 KYC/AML fields, your choice of geographic niche or mixed dataset.
No subscription. No recurring fees. No seat licenses. One-time purchase, immediate delivery.
Try Before You Buy
Download a free 100-record KYC sample — all 29 fields, full Certificate of Sovereign Origin, no registration required.
Not sure if your current testing data creates compliance risk? Take our 2-minute assessment:
Q: What format is the data delivered in?
A: CSV files, ready for ingestion into any system, database, or training pipeline. No proprietary formats, no SDK required. JSON and Parquet available on request for enterprise packages.
Q: Can I get a custom field schema?
A: Enterprise customers can request custom field configurations. Contact us to discuss your requirements.
Q: How quickly is the data delivered?
A: Immediately upon purchase. You download the CSV file directly.
Q: Is this data GDPR compliant?
A: Born-Synthetic data has zero lineage to real individuals. It is not personal data under GDPR. No processing obligations, no lawful basis required, no data subject rights apply.
Q: Can I use this data for AI model training under the EU AI Act?
A: Yes. Born-Synthetic data with a Certificate of Sovereign Origin provides the documented data governance that Article 10 requires for high-risk AI systems. Enforcement begins August 2026.
Q: What’s the difference between UHNWI and KYC/AML datasets?
A: UHNWI datasets contain 19 core financial fields focused on wealth profiling. KYC/AML Enhanced adds 10 compliance-specific fields (risk rating, PEP status, sanctions screening, beneficial ownership, etc.) for a total of 29 fields.
Q: How is this different from tools like Mockaroo or Faker?
A: Random data generators produce statistically meaningless records — fields are generated independently with no correlation. Born-Synthetic data enforces algebraic constraints across all 29 fields, ensuring every profile is internally consistent and statistically plausible.
