Organization
Leading Dutch Insurer
Location
The Netherlands
Industry
Finance, Insurance
Size
25,000+ employees
Use case
Test Data
Target data
Insurance data, claim data
Our customer, a nationally operating health insurance company with more than 650,000 policyholders, believes that everyone is entitled to accessible and affordable care of high quality. This health insurance company is listed in the top 5 insurance companies and is transforming towards digital solutions to optimize the organization.
The insurance company has a data-driven strategy to ensure the efficacy of its digital solutions. It manages a complex network of interacting IT systems, supporting multiple applications that require frequent updates and maintenance. Previously, production data was used for testing purposes across various environments (development, test, and acceptance environments). In this process, this insurance company relied on personal data from real customers. As this data is private and sensitive, there is a risk of exposing sensitive customer information.
As for solving this risk and complying with regulations, the compliance department had announced that this leading insurance company should get rid of using personal data from production and should introduce privacy-protective solutions, with a strict deadline before the end of the year. Existing data anonymization and fake data approaches are not flexible enough to keep data up to date and replicate data relationships.
The insurance company incorporated the usage of Syntho’s AI-generated synthetic data platform for software development and testing processes. It enables them to create secure and privacy-compliant datasets and keep the test data easily up to date. Now, the company ensures that its software solutions align with customer needs and industry standards, ultimately delivering robust and reliable products to its clients.
By providing consistent and privacy-compliant synthetic data across all environments that looks like production data, Syntho enables seamless and more efficient testing and development cycles.
This leading insurance company is relieved from the challenges associated with traditional data management approaches that could take up a lot of time by creating new, representative synthetic test data. Synthetic data ensures continuous availability of up-to-date and accurate data for testing and development purposes. As production data changes frequently over time, now this leading insurance company could easily update the test data by using the power of AI to keep the development, test and acceptance environments up to date.
Ensures compliance with data privacy regulations by minimizing the use of real personal data, without hindering developers due to representative synthetic test data.
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