Data Analytics within the Dutch Insurance industry
Insurance Analytics: Organizing Analytics capabilities to get value from Data Analytics solutions
The use of data is at the heart of each Insurance firm. For a very long time, insurers have for example been using data in underwriting. More recently, technology developments, like more computing power and readily available predictive algorithms, allowed to build more sophisticated Data Analytics solutions, like: improving the customer experience by better customer segmentation and targeted offers, enhancing risk assessment in underwriting, reducing the cost of claims and identifying new sources of sustainable growth.
Insurance companies are facing six challenges
Over the last years most insurers have invested in Data Analytics solutions and understand that investing in Data Analytics is key to survive in a fast changing environment. However, a recent study among 68 EMEA Insurance companies showed that 90% of interviewed EMEA insurance firms struggles to see a positive business case on data analytics solutions. Insurance companies are facing multiple challenges that prevent them for reaching the potential of Data Analytics solutions:
- Data Analytics experts are scattered across the organization; each unit or function has their own expertise and activities are not optimally coordinated.
- There is a gap between Data Analytics expertise and business sense.
- Data Analytics solutions are not implemented into business processes, therefore using the solution is too cumbersome and people stop using it.
- The value of Data Analytics solutions is not defined or not measured structurally, therefore it is unclear if the investment and maintenance is justified.
- There is no company-wide vision and strategy for Data Analytics, therefore direction and drive for initiatives is missing.
- New technology developments like Big Data and AI give even more potential of using Data Analytics. Insurers feel that they have to jump in to not get behind of competition or behind of InsurTech startups, but forget that in order to profit from these technologies they will need a solid Data Analytics capability first.
Explaining the challenges for insurance companies
This blog series is set up to answer on the challenges described above. This first blog aims to explain the process and options for the design of the Data Analytics operating model. Secondly, the process for selecting the most valuable use cases will be discussed.
Our next blogs will give real world examples by explaining how Data Analytics has delivered value to our clients. After describing these use cases, the difference between Data Analytics, Big Data and Artificial Intelligence will be explained, as well as the added business value. This blog series will end with a concrete roadmap to become an Insight Driven Insurer and the role of a Data Analytics manager in an Insurance firm.
Do you want more information about data analytics within the dutch insurance industry? Please contact Robert Collignon via the contact details below.
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