What Artificial Intelligence brings to distribution for insurance products

Artificial Intelligence (AI) brings us a myriad of new opportunities! Processes can be up to 15 times more efficient with AI technology than without it. Each insurer must logically identify his or her application fields.

Artificial Intelligence is not one unique technology, but rather a group of technologies. They include big data, RPA (Robotic Process Automation), machine learning, chatbots, etc. Though their ability to process and automate worries many people in terms of jobs that could be lost, the transition of jobs into technological developments has always existed. Using AI does not necessarily mean that jobs will be destroyed.

We can wonder about the benefits that insurers have when putting in place Artificial Intelligence technologies in their distribution departments. What different steps are involved in setting up AI for distributing insurance products?

You would think that insurers try to control/reduce their operational costs, above all. But putting in place AI requires an expensive technological investment. Insurers and insurance agencies who decide to apply it to their processes have two goals: firstly improvement of their customer experience, then contextualization of offers they propose to their customers.

To achieve this, Artificial Intelligence technologies use three stages of technicity to distribute products in the insurance field.

The first one consists in using simple rules to propose offers to clients or leads. Before we had AI, encoding had to be done so that the system could generate offers. Thanks to this first level of Artificial Intelligence, rules are applied to pinpoint patterns and propose an offer.

The second one includes a layer of machine learning in offers made to clients. This requires a huge data base to make the most of it. Insurers use AI systems that will identify similar models, meaning they look into the customer’s history to see what had been proposed to similar customers, and then propose an offer that could interest the current client to obtain this level of personalisation. This stage means that data must be ‘clean’ but also that its confidentiality must be ensured, in particular since Data Protection Regulations were enforced in Europe.

The third level allows insurers to be able to anticipate, and predict the optimal proposal based on a client’s profile, and this in real time. AI thus brings in visibility and advice in real time to insurers.

The emergence of Artificial Intelligence includes four challenges: management of a gigantic volume of data which implies the possession of relevant data; authenticity of algorithms used; a strong relevance of contextualization from the very beginning; and lastly, the implication of confidentiality elements.


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