The EU’s new Insurance Distribution Directive (IDD) comes into force in October this year, and will regulate how insurance products are designed and sold across the EU. The thinking behind the directive is both to provide fairer competition in the market place and to improve the protection available to customers. It therefore requires insurance companies to be much more customer-focused.

I caught up with Laura Melas from SAS partner BID to find out more about what this will mean in practice, and how analytics can help insurers to implement the directive.

Laura, how do you define the role of analytics in implementing IDD?

The European insurance regulator, EIOPA, sees analytics as fundamental to the successful implementation of the directive. It suggests that analytics can help at all stages of the insurance process, from product design, through testing, to sharing information, product monitoring, and analysing potential mis-selling. The thinking is that analytics will enable insurers to understand much more about their customers. It should therefore mean that customers are only sold suitable products, protect them from potential mis-selling.

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That sounds impressive, but how will it work in practice?

Well, take data governance. The Directive means that organisations need to get better at managing the flow of information, both for the purposes of monitoring and reporting, and also to ensure that sales teams have the right information. Analytics tools and platforms can really help with this, because they allow information to be integrated from several sources, and models to share information more widely across the organisation. Visualisation techniques also make it easier to understand the outputs from models, and new machine learning and AI algorithms can even integrate the outputs from models into decision-making.

So the main areas are likely to be customer profiling and product performance assessment?

Yes, very much so. Insurers need to be able to identify different types of customers for particular products, including a target market, and those for whom the product is very definitely unsuitable, which we are calling the ‘negative target market’. This information needs to be shared with distributors so that they can make the right decisions when selling products. Analytical models, particularly machine learning and data mining models, will be useful in identifying both the target market and the ‘negative target market’, and can be highly sophisticated, segmenting customers in really quite a detailed way. Visualisation techniques will be helpful in sharing this information with the distribution network, because they allow data and insights to be presented clearly, in ways that everyone can understand. Scenario analytics is also essential for assessing the performance of products under different conditions, a key part of the directive.

Customer protection is a key focus of the directive. How can analytics help to prevent mis-selling?

Mis-selling is defined as the sale of products that are not suitable for the customers. The directive requires insurers to take reasonable steps to ensure that each product is distributed to the identified market. In practice, that means they have to first identify the right target market, through profiling, which we mentioned before. Insurers also, however, have to check that sales teams and distributors really understand the target market, and are taking the right action. This checking can be done through text mining techniques, to extract keywords from unstructured data such as notes made by call centre and sales agents, complaints, and evaluation questionnaires. We can create models that help us to understand the intrinsic meaning of words and create patterns through associations of recurrent words. We can also assess customer reaction to products through sentiment analysis, so that we get a really clear picture of who is buying the products, and whether they are happy with them.

And insurance companies also have to monitor products, so how does analytics help there?

The regulator requires insurance companies to understand and review their products on a regular basis. Companies need to look out for events that may affect the potential risks for the target market, and therefore assess whether the product remains suitable for the needs of the target market, or whether the target market has changed. They also need to see whether the planned distribution strategy continues to be adequate. Companies can do this by structuring customer journeys, and identifying significant events to map the needs of the customer. These techniques are always central areas of development of analytical models used for profiling.

Laura, thank you very much.

To learn more about the Insurance Distribution Directive and implementation, please listen in on this recorded webinar (in Italian).