While it may seem like a modern phenomenon, insurance is the original big data industry. The industry has always used vast amounts of data to calculate the premiums customers and businesses pay to insure their items and assets – pricing was born from data.
We are now living in an age where the amount of data available about people, businesses and risks is increasing every day. With the vast quantity of data generated, more is known and can be validated today than could be yesterday.
Now with data enrichment, the next wave is upon us. Insurers are exploring how they can supplement clients’ application details using a plethora of data from third-party sources and their own knowledge, as well as data from distribution partners and channels. This can provide more accurate pricing and rating, and also validate the information originally received from customers.
Insurers can use the insight derived from data to manage risk beyond the traditional rating factors. For example, an insurer can determine a business’s likelihood to fail in the next 12 months based on credit and payment data. If a business suddenly starts using more credit lines and slows down on repayments for services, is it struggling or is it expanding? Either way, the data points towards the need to gain a greater understanding or to proceed in a modified way, as it highlights there is a behavioural shift at the business that could increase the claims propensity.
Aggregating data from different sources not only makes it easier to recognise trends and patterns that might otherwise be missed and enables informed decision-making based on risk profiling – it also eliminates the moral hazard risk of fraud at point of sale. As a result, both the premium lost due to consumers changing their risk data to get the best price and the resultant claims leakage can be reduced.
The time is now
Real-time data enrichment was introduced to personal lines motor insurance over seven years ago, and many elements are now seen as hygiene factors. Although there is a lack of joined up data in commercial lines compared to personal lines and the sources are different, the data is still available to be used for risk enhancement.
As a result, data enrichment is evolving into commercial lines and is forecast to become a hygiene factor within the next 18 months. Already the principles of micro SME insurance, such as the way it is priced, packaged, distributed and sold, are the same as in personal lines, so it requires the same fast flow, no touch model that thrives from data enrichment.
Commercial insurers who start the augmentation process now will gain market share at the expense of laggards. Indeed, in five years’ time, we will look back and wonder how underwriters wrote risks before they had all this additional insight.
What data is available in commercial lines?
As insurers look to adopt a customer-centric approach, there is wealth of knowledge available on each business. While this has historically been messy data in a number of different formats, the tools now exist to embrace this information and make the most of it.
The wide range of data sources already available to augment insurers’ information includes:
The important thing when bringing all this data together is to focus on what it is telling us, rather than why something has occurred. For example, if a company has filed a large number of mortgage documents, the reason for this is less significant than the insight it provides into the current borrowing/debt levels.
By building up a complete picture of their customers, insurers can accurately understand the risks involved and price accordingly. So how can insurers apply this data to the risks they handle on a daily basis?
You can read the full report here: Enhance risk and pricing with data enrichment
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