Insurance Analytics: Organizing Analytics capabilities to get value from Data Analytics solutions | Insurance | Deloitte


Data Analytics within the Dutch Insurance industry

Insurance Analytics: the business case for Data Analytics 

The use of data is at the heart of each Insurance firm. More recently, technology developments, like more computing power and readily available predictive algorithms, allowed to build more sophisticated Data Analytics solutions. Read our blogs to enhance your understanding of the key challenges insurers are facing and discover our business case for Data Analytics.

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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:

  1. Data Analytics experts are scattered across the organization; each unit or function has their own expertise and activities are not optimally coordinated.
  2. There is a gap between Data Analytics expertise and business sense.
  3. Data Analytics solutions are not implemented into business processes, therefore using the solution is too cumbersome and people stop using it.
  4. The value of Data Analytics solutions is not defined or not measured structurally, therefore it is unclear if the investment and maintenance is justified.
  5. There is no company-wide vision and strategy for Data Analytics, therefore direction and drive for initiatives is missing.
  6. 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.

Insurance Analytics part 1: How to set up a data analytics organization?

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. 


How to set up a data analytics organization?

Insurance Analytics part 2: the business case for Data Analytics

“Insurers have invested in Data Analytics (DA) but see a limited return in business value”. This is one of the outcomes of a research amongst Insurers in EMEA. This second blog on Data Analytics within the Insurance Industry focuses on the business case for Data Analytics. It describes an approach for setting up the business case, types of required investments, expected benefits and provides guidelines.

The business case for Data Analytics

Insurance Analytics part 3: Increased efficiency at a Dutch insurer by applying Operations Analytics

This third blog will give a concrete example of how Deloitte’s Operations Analytics approach resulted into value for a Dutch insurance organization. The case described is from our Operations Analytics approach which was implemented in multiple Dutch and International Insurance organizations. We’ll describe the details of this approach and explain how we have reached a positive impact at a large Dutch insurance organization in terms of managing stock levels, increasing efficiency and optimizing capacity.

Increased efficiency at a Dutch insurer by applying Operations Analytics

More information?

Do you want more information about data analytics within the dutch insurance industry? Please contact one of our experts via the contact details below.

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