generate-synthetic-data

Synthetic transaction data for testing credit scoring models is generated by simulating mobile money, utility, and telco transactions. This creates structured, anonymized datasets in a designated directory for developers to validate model performance.

Simulating mobile money and telco data without exposing real user information involves generating anonymized synthetic datasets. These scripts create realistic transaction histories and diverse profiles suitable for secure test environments and demo scenarios.

Yes, you can generate reproducible test data for credit scoring applications. The synthetic data generation uses a fixed seed to ensure that transaction outputs remain consistent and can be reliably replicated across multiple test runs.

Synthetic data generation works for validating utility payment credit models by producing simulated utility transaction histories. These structured outputs provide realistic yet anonymized data to test how your credit scoring system processes utility payment behaviors.