How One UK Insurer Accelerated Testing and Achieved GDPR Compliance with GenRocket

A leading UK-based health and life insurance provider transformed its Test Data Management by adopting GenRocket’s Design-Driven Synthetic Data platform. Faced with the complexity of testing in a microservices environment, the insurer struggled with slow, inconsistent, and manual test data creation. Traditional approaches couldn’t keep up with the demands of dynamic, API-driven workflows—and posed increasing risks under GDPR.

Health and Life Insurer Transforms Test Data Management

By transitioning its TDM approach to GenRocket, the insurer now generates real-time synthetic test data that is injected directly into microservices via API—no data storage required. Using GenRocket’s self-service Test Data Cases, testing teams simulate complex insurance workflows, including lifestyle-based underwriting, claims adjudication, and wellness reward programs—all with full referential integrity and automated data delivery.

The result? Test data provisioning dropped from days to seconds. Test coverage expanded to include edge cases and business rules, while full GDPR compliance was achieved by eliminating the use of production data entirely.

This case study illustrates how Design-Driven Synthetic Data is reshaping quality engineering—empowering teams to test faster, smarter, and more securely in today’s agile and regulated environments.

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Why Enterprises Are Replacing Production Data with Synthetic Data

Design-Driven Synthetic Data is Changing the Traditional Test Data Paradigm

Enterprises are reaching a tipping point. As data privacy concerns rise and production data becomes increasingly inaccessible for development and testing, organizations are seeking smarter, more secure alternatives. The latest blog from GenRocket dives into this shift—and why design-driven synthetic data is taking center stage.

Leading organizations are reducing their dependance on masked production data for testing due to data privacy concerns and data quality limitations. As Quality Engineering teams turn their focus to the use of synthetic data, many are embracing the innovative concept of design-driven synthetic data. This approach allows teams to generate exactly the data they need, tailored to their testing scenarios, with full control over variety, volume, format and complexity.

The result? Higher test coverage, faster delivery cycles, and dramatically improved software quality—all while staying compliant with evolving data protection regulations.

Discover why traditional Test Data Management approaches are being phased out in favor of scalable, intelligent synthetic data generation. Learn how GenRocket’s platform empowers DevOps teams to provision precise, rule-based test data on demand—and why this evolution is essential for the advancement of quality engineering.

Read the full blog article to explore how design-driven synthetic test data is unlocking speed, safety, and innovation across the software development lifecycle.

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Why Design-Driven Synthetic Data is the Future of Quality Engineering

Many enterprise QA and development teams today face a familiar challenge: lack of reliable, compliant, and scalable test data. The World Quality Report 2024 reveals that test data availability remains one of the top three obstacles limiting the speed and quality of software delivery—even as 72% of teams now leverage automation.

While synthetic data solutions are gaining traction, not all approaches deliver the control and precision needed for modern quality engineering. Statistical replica models and AI-generated synthetic data fall short, introducing data gaps and inconsistencies, compliance risks, and lack of enterprise scalability. These methods require access to sensitive production data and struggle to deliver the volume, variety and format of data needed for comprehensive testing.

GenRocket’s Design-Driven Synthetic Data Generation solves these problems. Unlike other solutions, it puts testers and developers in full control—allowing them to design and generate exactly the data they need, when they need it. No production data is required. Every test case can be supported with valid, secure, relational, and repeatable synthetic data, delivered at scale and integrated directly into CI/CD pipelines.

As enterprises modernize their quality engineering practices, a design-driven approach is proving essential. It eliminates the risks and limitations of other synthetic data technologies—empowering teams to maximize test coverage, data security, and operational efficiency.

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Modernize Test Data Delivery for Mainframe Environments

Mainframe systems continue to be the backbone of critical enterprise operations—from financial transactions to insurance claims processing. But testing these systems often relies on outdated methods, slow data provisioning, and restricted access to production data. GenRocket is here to change that.

With GenRocket’s expanded support for mainframe environments, you can now generate synthetic test data that mirrors the structure, encoding, and logic of legacy systems—without compromising speed, compliance, or test coverage. If desired, you can also provision masked production data with synthetic data replacement of sensitive data or augmented synthetic data values.

Our platform supports COBOL copybooks, EBCDIC encoding, VSAM files, and more, allowing you to deliver precise, compliant test data directly into your mainframe testing workflows.

Here’s what you gain:

Eliminate production data dependency and masking delays
Ensure compliance with data privacy regulations
Generate negative, edge-case, and boundary data for robust testing
Achieve complete test coverage with controlled, on-demand test data
Seamlessly integrate into CI/CD pipelines and DevOps frameworks
Support hybrid environments involving both mainframe and distributed systems

Whether you’re testing complex transactions, batch jobs, or integration data flows, GenRocket gives your teams the precise data they need—fast, flexible, and fully automated.

It’s time to bring agility and precision to mainframe testing.

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Seamless Integration for COTS Systems with GenRocket

Organizations today rely on major Commercial Off-The-Shelf (COTS) systems like PeopleSoft, SAP, Salesforce, Guidewire, and Workday. GenRocket empowers these organizations to generate and manage secure test data for any COTS application through innovative integration methods.

Flexible Integration Options

GenRocket offers two key approaches for integrating with COTS systems:

Web Services Integration: Generate real-time synthetic data using GenRocket’s Design-Driven Data methodology. This approach leverages REST and SOAP APIs for continuous data provisioning without relying on sensitive production data. Teams can create endless automated test scenarios—supporting complex data patterns and maintaining referential integrity—all while modeling only the specific domains they need.

CSV Export with File Masking: Replace sensitive data in exported CSV files with synthetic data using GenRocket’s file masking technology. This ensures 100% data privacy without reversible algorithms, offering faster, more secure data provisioning.

Enterprise-Grade Scalability & Security

GenRocket’s platform is built for enterprise-level performance, with self-service access to test data, life cycle management, and analytics. This scalable solution eliminates data bottlenecks, integrates with CI/CD pipelines, and ensures compliance with GDPR, HIPAA, and other privacy regulations.

By generating synthetic data on demand, GenRocket helps organizations reduce storage costs, streamline testing operations, and ensure security across their ecosystem.

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Unlock the Power of Design-Driven Data with GenRocket

Software development teams face ever-growing challenges in provisioning secure, scalable, and precise test data. Traditional Test Data Management (TDM) solutions often fall short, exposing sensitive data and creating data quality limitations that slow down the development lifecycle.
The Risks of Using Production Data

Production data offers realism but comes with critical privacy and security risks. Copying sensitive information into test environments increases exposure, potentially leading to compliance failures and costly breaches. Moreover, production data rarely includes edge cases, complex data patterns, or negative testing scenarios—essential elements for comprehensive quality assurance.

Beyond Statistical Synthetic Data

While many synthetic data generation solutions replicate production data statistically, they lack the flexibility and variety needed for full testing coverage. This approach can limit the effectiveness of testing program logic and complex system integrations, risking undetected defects.

Automate and Orchestrate Test Data Delivery

It’s Time to Reimagine the Test Data Paradigm

GenRocket’s Game-Changing Approach

GenRocket’s “Design-Driven Data” methodology transforms test data creation. By modeling data from production metadata, GenRocket generates synthetic test data tailored to specific testing needs—on demand, without storage overhead. This innovative platform seamlessly integrates with CI/CD pipelines, providing precise, scalable data for any test scenario.

Why It Matters

With GenRocket, teams can eliminate data privacy risks while boosting test data quality. This unified data provisioning platform ensures enterprises can modernize testing while maintaining business continuity, driving faster and safer software releases.

Read the full article and discover how GenRocket can redefine your test data strategy.

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GenRocket 2024: A Year of Technology Innovation

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Happy Holidays from GenRocket

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GenRocket Optimizes SAP Test Data Management

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Achieving Data Security Excellence with GenRocket: A Case Study

A leading Japanese insurance provider, serving over 2 million policyholders, faced challenges in securing sensitive policyholder data while managing software quality in a fast-paced environment. Central to their operations is the Guidewire system, which integrates policy, billing, claims, and contact data. However, its complex data structure—spanning 12,000 tables—posed significant hurdles, particularly for maintaining data integrity and ensuring compliance with strict data security standards.

To address these challenges, the provider chose GenRocket’s Test Data Automation platform. Key highlights of the implementation included:

In-Place Masking: GenRocket secured sensitive production data directly within the environment, eliminating the need for duplicate datasets and minimizing security risks.

Maintaining Referential Integrity: Across interconnected modules like PolicyCenter, ClaimCenter, BillingCenter, and ContactManager, GenRocket ensured accurate and reliable testing workflows.

Japanese Character Support: GenRocket adapted seamlessly to Kanji and Kana requirements, crucial for applications serving the Japanese market.

Cost Efficiency: By streamlining data management, GenRocket reduced infrastructure costs, enabling reinvestment into future data initiatives.

The collaboration delivered transformative results. The provider achieved enhanced data privacy, high-volume test data provisioning, and substantial cost savings. Moreover, GenRocket’s support for Guidewire’s ecosystem and focus on quality ensured accurate integration testing, setting a benchmark for efficiency and security.

This case study exemplifies how GenRocket empowers enterprises to overcome data challenges and scale for future demands. Read the full case study to learn more.

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