Beta client

    Completing your test data strategy

    Anonymized data and synthetic data each have strengths. Koivu fills the gaps they can't cover.

    The missing piece

    A real client with banking secrecy waiver

    Koivu GmbH complements your anonymized and synthetic data, covering use cases they can't.

    Banking secrecy waiver

    Koivu signs a formal waiver of banking secrecy with your institution. This gives your dev, QA and operations teams full access to Koivu's account, unrestricted in production for the specific scenarios where anonymized and synthetic data fall short.

    “Anonymized for volume. Synthetic for safety. Koivu for production reality.”

    When to use what

    A complete test data strategy. Each approach excels in different scenarios; use them together for full coverage.

    Best for

    Compare anonymized data, synthetic data, and Koivu as beta client

    Use caseAnonymized dataSynthetic dataKoivu as beta client
    Volume / load testingExcellentExcellentLimited
    Pattern / behavior analysisExcellentLimitedExcellent
    Privacy-safe developmentLimitedExcellentYes
    Production feature rolloutsLimitedLimitedYes
    Mobile / 2FA / SMS testingLimitedLimitedYes
    Pennytest PaymentsLimitedLimitedYes
    Full team access without restrictionsLimitedYesYes
    Realistic screenshots / demosLimitedLimitedYes
    Scope and limitations

    Koivu's scope

    What Koivu complements and what it does not replace

    One client

    Koivu is one client. It complements, not replaces your volume testing with anonymized or synthetic data.

    Real business activities

    Transaction patterns reflect our business activities, not a statistically representative sample.

    Targeted testing

    Best for targeted production testing, not comprehensive regression suites.

    Why Koivu as beta client

    What you can safely do in production

    Koivu's own account gives you a real client for testing, demos and analysis without touching customer data.

    Feature rollouts

    Deploy new features to Koivu's accounts first via feature toggles. Test in production before general release.

    Production debugging

    Reproduce and investigate production issues using Koivu's account without privacy concerns.

    Mobile and 2FA testing

    Koivu has a real mobile phone. Test SMS verification, push notifications, and mobile app flows end-to-end.

    Documentation and training

    Create guides and training materials with real screenshots. Onboard new employees with realistic scenarios.

    AI/ML training data

    Train fraud detection, recommendation engines or analytics models with real transaction patterns, compliantly.

    Sales demos

    Show prospects real banking features with real data, not "John Doe" placeholders that look unprofessional.

    External system testing

    Koivu exists in production. Test integrations with SIX, TWINT, card networks, and correspondent banks using a real account.

    Audit demonstrations

    Show auditors your testing and monitoring processes using real workflows without exposing customer data.

    Two approaches, one strategy

    Each approach can benefit from Koivu.

    Approach 1

    Anonymized Customer Data

    Valuable for realistic testing, with some inherent constraints

    • Compliance Overhead

      Requires careful anonymization processes to meet DSG (Switzerland), DSGVO/GDPR (EU), and banking secrecy requirements. Re-identification risk must be managed.

    • Environment Restrictions

      Typically restricted to controlled test environments. Can't be used in production or shared with external partners for cross-system testing.

    • Access Controls Needed

      Even anonymized data may require access controls and audit trails. External contractors and offshore teams may be excluded.

    • Data Freshness

      Anonymized snapshots can become stale. Keeping test data in sync with production patterns requires ongoing effort.

    Anonymized data remains essential for scale testing and pattern analysis. Koivu complements it for specific use cases.

    Approach 2

    Synthetic Test Data

    Safe, scalable and privacy compliant, with some inherent constraints

    • No Production Presence

      Synthetic clients don't exist in production. Feature rollouts and production validation require a different approach.

    • No Mobile Device

      Synthetic clients can't receive SMS for 2FA, push notifications, or verify mobile app flows. End-to-end mobile testing requires real devices.

    • External Partners

      TWINT, SIX, correspondent banks, card networks don't have your synthetic clients. Cross-system integration testing has limits.

    • AI/ML Training

      Machine learning models often need real-world edge cases and behavioral patterns that synthetic data may not capture fully.

    • Documentation Realism

      Screenshots with "John Doe" and "123 Test Street" can look unprofessional in training materials and sales demos.

    • Production Debugging

      Reproducing production issues often requires access to real production data and transactions.

    Synthetic data is excellent for volume testing, load testing, and privacy-safe development. Koivu fills the gaps where production presence is needed.

    Complete Your Test Data Strategy

    Let's discuss how Koivu can fill the gaps in your existing testing approach.