Data is a sensitive but especially important topic when it comes to privacy and anonymization of it. How can companies guarantee their customers to keep their data safe? The Berlin based company Statice offers a solution with their data anonymization tool for businesses. Their mission: to enable companies to unlock the potential of their data while safeguarding individuals' privacy. We talked to co-founder and CEO Sebastian Weyer about how their AI works and about Berlin as a dynamic and central AI hub in Europe.
Hi Sebastian, thank you for taking the time for this interview. Statice offers a data anonymization solution for businesses. How exactly does your software work?
Hi, thank you for the opportunity. At Statice, we built a data anonymization solution to help businesses remain innovative and compliant when working with sensitive data.
Our core technology is an anonymization engine. It relies on deep-learning algorithms and state-of-the-art privacy techniques. The engine generates synthetic data that is fully anonymous. But it also preserves the statistical properties of the original data to a very high degree.
Organizations can use synthetic data for any statistical analysis that they would like to use the original data for. Our synthetic data guarantees data privacy. That means organizations can work in a compliant way without the risk of exposing sensitive information.
How did the idea for Statice come about? How did your team come together?
We founded Statice on two core beliefs. First, the fact that data privacy is becoming an increasingly important asset for companies to provide trust. Secondly, we believe that innovation will build on collaboration across players, with data as the main resource.
The founding team of Statice wanted to build something that would encompass these two elements. As a result, in 2017, we founded Statice to both protect individuals and empower data-driven innovation.
In which areas is the software most popular? What kind of businesses or fields especially require anonymized data?
We’ve seen great applications in the finance, insurance, and healthcare industries, as well as in larger consumer brands. In the end, it’s about helping companies deal with large amounts of data in a privacy-preserving way, so it’s as much about the scale and digital readiness of the businesses as the industries in which they operate.
Of course, privacy primarily concerns businesses dealing with sensitive data. Such businesses saw their ability to innovate restricted when the GDPR came into force. Their data teams were slowed down due to heavy regulatory and compliance processes, and their ability to work cross-border and with external parties was limited in many cases.
Additionally, the privacy implications of moving sensitive data to cloud resources have also caused difficulties. These are the core challenges that we tackle at Statice. For example, we worked to enable safe data transfer for research on granular migraine data without risking the individual privacy of any of the study participants.
In another case, we helped a leading Swiss insurer future-proof their data science operations by equipping them with the tools to work on privacy-preserving synthetic data for their data analytics team. Another case is the work we’re doing with a large European bank to enable compliant cross-border AI development between multiple IT hubs.
One of your basic principles is to keep the human being in the center. How can humans, AI, and technology in general best work together?
That’s a good and also difficult question. Individuals have a right to privacy but also desire modern experiences. Data and AI unlock leaps forward in what companies can offer to consumers. But while this represents a huge opportunity, it also brings risks.
As we’ve seen, storing and using data is not without hazards. Just in recent months, we had several examples. In March T-Mobile’s data breach exposed customers and employees’ information for the second time in six months. Or more recently, a cyber-attack exposed 9 million’s of EasyJet customers' details.
While we believe in the potential of technology to improve products and experiences, we hope that organizations take the responsibility associated with the data they hold seriously.
We see Statice as one piece of the puzzle of making data and AI use cases safer and more feasible, especially in enterprise environments.
Another very important part of your work is sticking to the GDPR. Did you come across any obstacles when integrating the laws?
From our perspective, the laws are relatively clear. For instance, the GDPR draws a clear line between personal data, that falls under data privacy protection laws, and anonymized data, that doesn’t.
What has been harder to deal with, is the practical understanding and application of the laws. Interpreting and complying with today’s requirements still represent a challenge for organizations. DPOs and compliance teams have the responsibility of evaluating the legal and technical aspects of a myriad of approaches, including ours.
The GDPR was an important step forward in the protection of consumer data. Now, we’re looking forward to the development of certifications and technical guidelines to help businesses implement privacy measures.
How would you describe the importance of data privacy in Germany and Europe compared to the rest of the world? Does the situation in e.g. China worry you, especially regarding the freedom of competition?
European privacy law is the lighthouse for most other privacy laws. It offers one of the strongest legislative frameworks for data protection and privacy. With the implementation of the first European data protection law, Germany contributed to the emergence of personal data regulations. Privacy and personal data protection hold strong meanings for the country. For us, this is an important signal about the future of privacy technologies.
There are a lot of concerns about privacy in today’s world. The technological response to the on-going health crisis, for example, raises many privacy challenges. Governments and organizations are rushing to release COVID-19 tracking applications. We see many ML and AI applications leveraging shared personal healthcare data. This must raise questions about the use and the privacy of data.
AI becomes more and more relevant in Berlin´s landscape and there are a lot of young as well as established AI companies at the location. How do you feel about Berlin as an AI location?
In recent years, we’ve seen the city grow into a dynamic and central AI hub in Europe. Berlin’s ecosystem is developing, supported by research and governmental policies. The number of AI companies keeps on growing, attracting investors and tech talents.
Besides its vibrant ecosystem, the city has a lot to offer. While access to capital is perhaps not as good as in the US, London, or Israel, there is a lot of talent here. It’s easy to provide a high-quality of life to the team, regardless of the lifestyle they choose to live.
This ability to have a good work-life balance at comparatively competitive spend levels means you can build happy, productive, diverse teams. This, in turn, builds resilience and offers opportunities for founders that are sometimes not possible in other cities.
One thing Berlin could improve, is providing opportunities for collaboration with industry. If you compare to Zurich for example, corporates play a much larger and more meaningful role in the ecosystem.
What are yours and Statice´s plans for the future?
Statice is on a mission to enable companies to unlock the potential of their data while safeguarding individuals' privacy. We aim at becoming the partner of choice and privacy backbone for all data-driven businesses.
So far, we’ve done a great job at building a strong team, and our core technology provides the best-in-class replication of statistical information from original data to the synthetic data. Our near-term focus is taking this technological advantage we’ve built up, and making it faster and easier to use, for more people.
At the end of the day, to achieve our mission, we need to empower teams across our client organizations to work safely with data, and that means we need to improve our tool set for non-technical users.
Thanks for your time, Sebastian.