Personalized Insurance with Big Data & AI

Big data at insurances

Digital transformation is happening at a killer pace. And one of its main consequences is the production of incredible amounts of data. Anyone carrying a cell phone is constantly revealing their location, smart meters can transmit a home's energy consumption by the minute, and sensors in your car can give the leasing company real-time insight into your driving habits. And may we dream even further perhaps? A health insurance company that uses your electric toothbrush to track how often you brush your teeth and thus calculate your risk?

Leaving aside the privacy debate that irrevocably accompanies the collection of such Big Data, the big question, of course, is how all this data can be used to serve consumers better, more relevant and more personally.

Usage Based Insurance
But with the exponential growth of available Big Data outlined above, simply pulling together data from various back-office systems is far from enough. Customers now require insurers to offer customized policies that are based on actual usage and where risk prevention is directly rewarded with lower premiums.


Within the Corona lockdowns, after all, many a car owner was confronted with the fact that it doesn't feel nice to have to pay the full insurance premium for a car you barely drive. Wouldn't it be much fairer - in addition to a limited base amount for insuring the vehicle itself - to relate a car insurance premium to its actual use? Customers demand the ability to take out so-called micro policies and expect the insurer to offer pay-as-you-drive options. And subsequently, wouldn't it also be fair that someone who drives more safely - for example, by keeping neatly to the speed limit - pays less premium than a reckless savage in traffic? So not just pay-as-you-go, but pay-how-you-drive. Also known as Usage Based Insurance.

But in order to offer such personalized premiums, the insurer must be able to combine data coming from the sensors in the car with information about the prevailing speed limit on the route driven, and that data must all be combined with customer and policy information. And all of this, of course, preferably in real time....

Business Intelligence

You read it already; a lot of data being collected, through various ways and channels. But how do you act on that data in such a way that you are able to recognize and visualize each individual with her or his behavior? Many companies have already invested in Business Intelligence (BI) in recent years. BI tooling indeed have the power to tap into various sources and turn data from the level of zeros and ones, into insights and information. But what characterizes this BI tooling is that it has primarily an enterprise-level reporting function. As the name implies, it is about Business Intelligence ... not Profile Intelligence. It shows how you performed as a company over the past period: how much revenue, how many new policies, how many customers in a particular region?

CRM Systems

In an attempt to fill in the 'Profile' Intelligence part, insurers have also invested in CRM systems in recent decades. In these, they built customer cards that provide insight into who a customer is. For many companies, this was already a step forward. Customer advisors already had contact moments with their customers in this way to have a fairly good understanding of who the customer is and what insurance they purchase.

But for dealing with big-data, such as the input for Usage Based Insurance, CRM is not the solution. The load of millions of movements, visits and interactions is far too heavy for the CRM system to handle. The CRM system is primarily an administrative or registration system, such as recording the correct NAWTE data, contact moments or handling (claim) processes. Not the big (customer) data platform to combine all the information around the (prospective) customer into one profile.


Customer Data Platforms


Customer Data Platforms (CDPs) are. And indeed, not only can they process and analyze large amounts of data in real time, but they can also, by using artificial intelligence (AI), make predictions about a customer's behavior based on the aforementioned data. For example, consider expected risks and cross-sell opportunities to strengthen policy coverage based on customers with similar profiles.

Or conversely, personalized offers through co-marketing based on unique socio-demographics and characteristics of each individual: a donation to the children's sports club for families and a discount on an e-bike for seniors.

And moving on to the future ... it enables the principle of Usage Based Insurance: Renewed business models, where premiums are based on consumption and risk averse behavior.

Competitive Advantage

In this highly competitive world with new (online) providers, loyalty has long since ceased to be a given. Just think of all those people who 'hop' from one health insurer to another towards the end of the calendar year. Companies with the competence and vision to transform big data into personalization in every phase of the relationship life cycle will gain a solid advantage over the competition. And the CDP will be a key driver in the future to enable this within insurers.

Let's see how that works?

With Intouch365 we developed a CDP solution specifically applied to the world of insurance companies with Microsoft Dynamics 365 Customer Insights. On our website there is a webinar in which we show you how data science and machine learning through a Customer Data Platform can contribute to understanding, engaging and binding the customer in order to strengthen the commercial power of you as an insurer.