During the last years, the majority of the insurers have invested in building data analytics departments and teams. These units are working on applying complex models to improve loss ratio, reduce fraud, and offer a more accurate price to their clients, and they are actually achieving it. This investment does represent a substantial ROI for these corporations and it is difficult to find an insurer that has not made this step yet. Because nowadays, it is clear to everyone that data is a valuable asset.

But, what is next for Data Analytics?

Using and implementing external data in their procedures. When we meet with an insurer, one of the most frequent questions we are asked is ‘why do we think the insurer cannot do what we are offering if they already have a data analytics department’. At this point, it is very important to make crystal clear what is the difference between internal and external data. In other words, clarify that they currently use traditional data (and do it very well), and our solution is based on enriching traditional with non-traditional data. Of course, we also must highlight other aspects such as the multilingual capability, our expertise in the field, and the speed and efficiency in implementing new data sources.

The majority of the data analytics departments are currently using internal data and base their models on historical data of claims and losses. Some of them even gather external data from specific sources. We believe the ability to mix and implement different types of sources is the next milestone data analytics departments must pursue.

How do external data add value to data analytics departments?

There are two main aspects in which external data can help improve data analytics processes:

1.    Update Data

The problem is global: for example in commercial lines, 47% of the customers on average have at least one basic data point outdated or inaccurate, (commonly the business activity or the address). The reason behind this is that insurers renew their policies every year, but they do not update their customers’ data. External data is generally more recent than internal. In commercial lines, for example, it is the business itself and its customers who make updates on their website, google for business, social media profiles, platform reviews, etc.

2.   Improve Risk Control

Having more customer data means knowing customers better. We have demonstrated that online data points such as bad opinions, low cybersecurity levels, bad online reputation, and the background of the managers, have a strong correlation with loss ratio levels. This data also enables the insurer to have better customer segmentation as they can differentiate between two customers that previously had a similar risk level. Or even use this data to gain efficiency in marketing campaigns, for example, identifying who of their customers is now selling their products online for an online retailer insurance campaign without having to ask them.

How can insurers use external data in their processes?

3 steps: updating, verifying, and enriching data.

Wenalyze platform scheme.


The use of external data is the new trend in the insurance industry

Update and verify: the first step is to clean the current data. This process consists of comparing the insurers’ data with online data. Verify it when it matches and update it when it does not coincide. This increases the data quality, which is key before even considering adding any more complexity. We need to have a clean kitchen before cooking.

Enrich data: external data is added to improve predictive models. These models which are currently being applied during renewals and new business quotes will see an increase in their accuracy and prediction levels when adding the enriched information. It is the salt and pepper of the data (I really am hungry right now).

The idea is not to change models or procedures, but to make them more precise and increase the economic improvement they are currently having. In some cases, we have reached a 2% loss ratio improvement when applying external data during renewals and new quotes processes, which is translated into relevant savings.

The use of external data is here to stay the same way data analytics did back in the day. Those insurers who are the first implementing the use of external data will see themselves a step ahead of their competitors. In comparison, they will know their customers better, have better-priced portfolios, a higher risk control, and will manage to reduce even more their losses.

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