Knowledge Sharing: A Necessity for Understanding the Customer
The Insurance business has always had a clear business model that relies heavily on analyzing and understanding customer related data. In a highly competitive industry, survival and competitive advantages are heavily depended upon utilizing the data that is being collected. If Insurance, the leading property and casualty insurer in the Nordic region, is actively sharing its insights and learnings with the business.
For more than a decade, analysts at If Insurance have met at the Nordic Analyst Network Seminar (NANS), an internal conference to share success stories and insights, and to learn more about how the insights are used in If. The purpose of the conference is to get a feel for the trends in data analytics and to strengthen the analytical community and promote the collaboration between analysts and their colleagues in IT and other business units. In the past, it has always been arranged with a physical attendance, but due to covid-19, it took place online this year.
This year the conference took place in October and lasted for two days. With a record-high attendance of over 140 people across the Nordics and Baltics, from several units, working with product development, marketing, sales, claims and IT. Since this year’s conference was online, attendees sat at their own laptops through both days, while they listen to 16 different topics and a virtual social activity.
Some of the topics were naturally about data. Both in terms of understanding the data journey from source to target tables, but also about Data governance: who to ask or report to, about specific data needs. An always high anticipated area, at the conference is Advanced Analytics, and this year didn’t disappoint. We had two interesting cases in different business areas. The first case was about classifying data by using Natural Languages Processing (NLP), an important learning was, that it can be difficult deriving context, when working with NLP. The second topic was on image analysis and how it potentially could automate some of the processes, we have today.
Finally, some of the Analytical tools that are being used daily, were also displayed and best-practice were shared. How to avoid some of the common pitfalls with data visualization in Tableau and showing how to move forward with a modern data platform using Python and Jupyter Notebook, enabling more possibilities for collaborating and sharing analytical work.
Even as a online conference, it still provided an opportunity to network and share experiences within the analytical field. We expect that sharing information, and showcasing best practices in working with data and analytics, can stimulate innovation as well as improve our understanding of our customers and their needs.
