Skip to content
Contact Us

Synthetic Credit Data

Generate realistic credit portfolios with Deeploans

Deeploans Synthetic Data Generator creates reproducible, schema-aligned loan datasets with coherent amortisation, delinquency, prepayment, default and property-value dynamics. 

Build, test and train without exposing sensitive customer data.

deeploans-image

Synthetic loan data for training, testing and assurance

  • Built for financial institutions and technology providers
  • Generate large, longitudinal loan panels without exposing confidential borrower data
  • Test AI systems using controlled scenarios, known outcomes and repeatable benchmarks

Built for consistency

  • Schema and domain constraints
  • Static-field coherence across cutoffs
  • Seasoning and remaining-term progression
  • Lifecycle rules for arrears, default, charge-off and redemption
  • Pool integrity and distribution sanity checks

Use Cases

Model Development

Build and validate with realistic data.

Data pipeline QA

Test pipelines and monitor data quality.

Scenario Generation & Testing

Evaluate portfolios under specific scenarios.

Research and Training

Teach with realistic loan lifecycles.

Purchase Options

Test Data Pack

For testing and validating AI systems

€4,950/ pack

Includes

  • 3,000–4,000 curated records
  • Normal, edge and failure cases
  • Controlled variations
  • Expected outputs and ground truth
  • Evaluation scripts
  • Scoring methodology
Request a test pack

Training Data

For training credit models and developing data applications

€9,500/pack

Includes

  • Up to 1,000,000 synthetic loans
  • 24 reporting periods
  • ESMA schema
  • Configurable credit behaviour
  • Reproducible datasets
  • Data dictionary and validation suite
  • Methodology and limitations report
  • Commercial internal-use licence
  • One technical onboarding session
  • 90 days of support
Start a data pilot

Custom Data

For institutions requiring bespoke calibration and deployment

From €30,000/pack

Includes

  • Custom portfolio distribution
  • Multiple asset classes
  • Institution-specific schemas
  • 12–60 reporting periods
  • Integration of licensed real-world vendor data
  • Custom test scenarios
  • Rare-event oversampling
  • Stress scenarios
  • API integration
  • Methodology workshop
  • Enterprise support
Contact sales