There is something different about Merkur Versicherung AG. It’s the oldest insurance company in Austria, but it doesn’t feel like it.

For starters, there’s the Campus HQ in Graz. An Illuminous race track lines the floor of the open plan space. The vibrant lobby is filled with eclectic artwork and unconventional furniture. And there’s a beautiful coffee dock beside the fully functioning gym in the lobby.

Then, there’s the people. One team in particular stands out amongst the crowd: the Merkur Innovation Lab. A group of self professed “geeks, data wizards, future makers” with some “insurance guys” thrown in for good measure. Insurance innovation is born right here. Daniela Pak-Graf, the managing director of Merkur Innovation Lab — the innovation arm of Merkur Insurance, told us in the Data Democratization Podcast:

“Merkur Innovation Lab is the small daughter, the small startup of a very old company. Our CEO had the idea, we have so much data, and we're using the data only for calculating insurance products, calculating our costs, and in the era of big data of Google, of Amazon, Netflix, there have to be more possibilities for health insurance data too. He said, "Yes,  a new project, a new business, what can we do with our data?" Since 2020, we are doing a lot.”

Oh, and then there’s synthetic health data.

The Merkur Innovation Lab has fast become a blueprint for other organizations looking to develop insurance innovations by adopting synthetic data. In the following, we’ll introduce three insurance innovations powered by synthetic data adoption.

Insurance innovation no. 1: data democratization


Like many other data-driven teams, the Merkur Innovation Lab team faced the challenge of ensuring data privacy while still benefiting from valuable insights. The team experimented with data anonymization and aggregation but realized that it fell short of providing complete protection. The search for a more comprehensive solution led them to the world of synthetic data.


According to Daniela Pak-Graf, the solution to the problem is synthetic data:

"We found our way around it, and we are innovating with the most sensitive data there is, health data. Thanks to MOSTLY."

Merkur didn’t waste time in leveraging the power of synthetic data to quickly unlock the insights contained within their sensitive customer data. The team has created a beautifully integrated and automated data pipeline that enables systematic synthetic data generation on a daily basis, fueling insurance innovations across the organization. Here’s how they crafted their synthetic data pipeline:

  • All “active customer” data (=600k rows, 55 columns) is extracted from a source Oracle database
  • That original data is uploaded to MOSTLY AI’s synthetic data platform via a data catalog tool
  • The synthesization process is triggered by a REST API
  • Apache Airflow then writes the output synthetic data to the destination PostgreSQL database


The end-to-end automated workflow has cut Merkur’s time-to-data from 1-month, to 1-day. The resulting synthetic granular health data is read into a dynamic dashboard to showcase a tailored ‘Monetary Analysis’ of Merkur’s customer population. And the data is available for consumption by anyone at any time. True data democratization and insurance innovation on the tap.

Insurance innovation no. 2: external data sharing


As we know, traditional data sharing approaches, particularly in sensitive industries like health and finance, often faced complexity due to regulatory constraints and privacy concerns. Synthetic data offered a quick and secure solution to facilitate data collaboration, without which scaling insurance innovations would be impossible.


According to Daniela:

“ of the biggest opportunities is working with third parties. When speaking to other companies, not only insurance companies, but companies working with health data or customer data, there's always the problem, "How can we work together?" There are quite complex algorithms. I don't know, homomorphic encryption. No one understands homomorphic encryption, and it's not something which can be done quickly. Using synthetic data, it's a quick fix if you have a dedicated team who can work with synthetic data.”


One exciting collaboration enabled by synthetic data is Merkur Innovation Lab’s work with Stryker Labs. Stryker Labs is a startup focused on providing training management tools for professional athletes. The collaboration aims to extend the benefits of proactive healthcare and injury prevention to all enthusiasts and hobby athletes by merging diverse datasets from the adjacent worlds of sport and health. Daniela explained the concept:

“The idea is to use their expertise and our knowledge about injuries, the results, the medication, how long with which injury you have to stay in hospital, what's the prescribed rehabilitation, and so on. The idea is to use their business idea, our business idea, and develop a new one where the prevention of injuries is not only for professional sports, but also for you, me, the occasional runner, the occasional tennis player, the occasional, I don't know.”

This exciting venture has the potential to improve the well-being of a broader and more diverse population, beyond the privileged few who make it into the professional sporting ranks.

Insurance innovation no. 3: empowering women in healthcare

Another promising aspect of synthetic data lies in its potential to address gender bias and promote fairness in healthcare. By including a more diverse dataset, synthetic data can pave the way for personalized, fairer health services for women. In the future, Merkur Innovation Lab plans to leverage synthetic data to develop predictive models and medication tailored for women; it marks a step towards achieving better healthcare equality. According to Daniela:

“ could be a solution to doing machine learning, developing machine learning algorithms with less bias. I don't know, minorities, gender equality. We are now trying to do a few POCs. How to use synthetic data for more ethical algorithms and less biased algorithms.”

The insurance industry and innovation

Insurance companies have always been amongst the most data-savvy innovators. Looking ahead, we predict that the insurance sector will continue to lead the way in adopting sophisticated AI and analytics. The list of AI use cases in insurance continues to grow and with it, the need for fast and privacy safe data access. Synthetic data in insurance unlocks the vast amount of intelligence locked up in customer data in a safe and privacy-compliant way. Synthetic healthcare data platforms are becoming a focal point for companies looking to accelerate insurance innovations.

The Merkur Innovation Lab team of “geeks, data wizards, future makers” are only getting started on their synthetic data journey. However, they can already add “synthetic data trailblazers” to that list. They join a short (but growing) list of innovators in the Insurance space, like our friends, Humana, who are creating winning data-centric products with their synthetic data sandbox.