Antal Nusselder, Lead Data Scientist, with:
OHRA is one of the largest direct insurers in the Netherlands and has been providing customers with 'surprisingly positive' experiences since 1925. OHRA customers can easily arrange all their insurance matters themselves when it suits them: by telephone or directly and easily with the OHRA App or via the website ohra.nl.
Prior to using Dataiku, the process of building models within the central OHRA Data team in collaboration with other teams (e.g., the Actuarial team) and handing it over to IT to be deployed was manual, time-consuming, and difficult. With growing enthusiasm and demand for data products and data-driven solutions from colleagues outside of the Data team, OHRA was challenged to address both their desire to accelerate and their obligation to ensure that their solutions are responsible towards their customers and regulators.
The challenge to speak the same language
The Data team members come from different backgrounds with varying skill levels in programming and data science best practices. They had previously been developing models individually, each in their own way. This regularly led to differences in definitions. When collaborating with other modeling teams and even external collaborators it is now also much easier to work together and share and reuse code and model components that were previously not easy to integrate to tell one cohesive story.
Bottlenecks in the handover to IT to productionalize
When it came time to hand over their models to IT to be deployed in production, IT would often have to put in additional effort to retrofit, test and oftentimes rebuild the models in their own systems. Even though the responsibility and expertise of testing and validation of data products rests within the Data team, there would be an additional testing effort to ensure that the version of the model in production gave the same results as the version of the model built by the Data team.
Minimizing risks ahead when using AI and ML
On top of this, governing data products built on users’ laptops was entirely manual. If OHRA wanted to increasingly leverage AI and ML technology, it would be crucial to do so in a way that ensured they could be compliant with emerging European AI regulations as well as to be transparent and accountable towards their customers.
The solution to the business challenge was to develop an integrated ecosystem that builds robustness while accelerating the time to value of their data projects. Within a year of adoption, they built this solution using the Dataiku platform.
The solution is made up of several parts:
OHRA customers also benefit. OHRA can now test, build and deploy solutions that help our customers much faster. For example, automations in the claims process makes the claims handling more efficient and helps customers get answers quicker. With governance now standardized and embedded in the development process, OHRA can ensure their customers are treated responsibly and fair.
Business Area: Communication/Strategy/Competitive Intelligence
Faster time to value & scalability