Starling paid £29M. Monzo paid £21M. Your compliance team is testing with production data.
Traditional banks face a paradox: regulators demand rigorous testing of KYC, AML, and sanctions systems, but every test dataset created from production data creates a new compliance liability. A single leaked test environment can trigger the same fines you were trying to prevent.
Born-synthetic data eliminates this paradox. Every profile is generated from mathematical models — Pareto distributions for wealth, algebraic constraints for financial consistency, cultural onomastics for realistic naming. No real customer was ever involved. No anonymization can be reversed. No data lineage connects back to your production systems.
These 9 specialized datasets cover every compliance testing scenario a traditional bank encounters, from onboarding through ongoing monitoring.
Available Datasets for Traditional Banking
Each dataset is available in three tiers: 1,000 records ($499–$999), 10,000 records ($2,499–$4,999), and 100,000 records ($12,500–$24,999). All datasets include a Certificate of Sovereign Origin documenting the generation methodology.
| Use Case | Description |
|---|---|
| KYC Testing | 29-field synthetic customer profiles for identity verification workflows. Test onboarding, document validation, and risk-tier assignment without exposing real PII. |
| AML Training Data | Synthetic transaction histories and customer profiles with embedded suspicious activity patterns. Train detection models on realistic scenarios without regulatory exposure. |
| Enhanced Due Diligence Simulation | Complex wealth structures, multi-jurisdictional holdings, and PEP-adjacent profiles. Stress-test EDD workflows on edge cases that rarely appear in production. |
| Transaction Monitoring | Synthetic financial flows with realistic volume patterns, cross-border transfers, and layering scenarios. Calibrate alert thresholds without production data leakage. |
| Sanctions Screening | Profiles with culturally accurate naming conventions across 6 geographic niches. Test name-matching algorithms against realistic patterns without touching watchlist data. |
| Model Validation | Statistically controlled datasets with known distributions for backtesting risk models. Validate under Pareto-distributed wealth and algebraically constrained fields. |
| Stress Testing | Extreme-scenario profiles and portfolios for resilience testing under DORA and regulatory stress frameworks. Push systems to breaking points safely. |
| Risk Scoring | Profiles with calibrated risk indicators across wealth tiers and geographies. Validate and tune risk scoring models with known-distribution inputs. |
| Onboarding Simulation | End-to-end customer lifecycle data from application through approval. Test digital onboarding pipelines, form validation, and conversion funnels. |
Why Born-Synthetic for Traditional Banking?
Basel III/IV capital requirements, PSD2 compliance, and MiFID II reporting obligations add layers of data governance that make production-data testing increasingly untenable.
Born-synthetic data addresses all of these requirements simultaneously. Every profile is generated from mathematical models — no real data input, no anonymization that can be reversed, no data lineage that connects to production systems. The Certificate of Sovereign Origin documents exactly how each dataset was produced.
The Born-Synthetic Difference
| Approach | Real Data Risk | GDPR Status | Re-identification Risk | Audit Trail |
|---|---|---|---|---|
| Production data in test | 🔴 Full exposure | 🔴 Requires full DPIA | 🔴 100% | 🔴 Same as production |
| Anonymized/masked data | 🟡 Residual risk | 🟡 Contested | 🟡 3–87% reversible | 🟡 Lineage preserved |
| Born-Synthetic data | 🟢 Zero | 🟢 Not personal data | 🟢 Impossible | 🟢 Certificate of Origin |
Get Started
Free sample — no registration. Download 100 synthetic profiles from any of our 6 geographic niches. Run your own validation. Check the Balance Sheet Test. Then decide.
Download Free KYC Sample → | Check Your GDPR Risk Score →
Frequently Asked Questions
What types of synthetic data does Sovereign Forger offer for banks?
We provide 9 specialized datasets covering KYC testing, AML training, sanctions screening, enhanced due diligence, transaction monitoring, model validation, stress testing, risk scoring, and onboarding simulation. Each dataset includes 19 UHNWI fields or 29 KYC/AML enhanced fields.
Is born-synthetic data accepted by banking regulators?
Born-synthetic data is compliant by construction under GDPR Article 25, EU AI Act Article 10, and DORA resilience testing requirements. Since no personal data is processed at any stage, standard data protection obligations do not apply to the generated datasets.
How does synthetic data help with DORA compliance?
DORA Articles 24-25 require financial institutions to conduct resilience testing with realistic scenarios. Born-synthetic data provides the controlled, repeatable test environments DORA demands without the regulatory overhead of using production data.
Can I test the data before purchasing?
Yes. Download 100 free synthetic profiles from any geographic niche — no registration, no credit card, no sales call. Run your own validation against the Balance Sheet Test.
Related Resources
- What Is Born-Synthetic Data? — The methodology behind zero-lineage data generation
- Compliance Testing Data — Full KYC/AML product overview with 29 enhanced fields
- GDPR Risk Assessment — Free tool to evaluate your current test data exposure
- Download Free UHNWI Sample — 100 profiles, 19 fields, no registration
- Download Free KYC Sample — 100 profiles, 29 fields, no registration
- Platform Comparison — How Sovereign Forger compares to Mostly AI, Tonic, Gretel, and others
- Glossary — 50 essential terms in synthetic data and financial compliance
- Regulatory Guides — EU AI Act, DORA, and data protection frameworks
