Augmented underwriting processes make insurers more effective, more profitable and more prepared for the future, writes Cytora’s Matthew Churchill
The earth is round, space goes on forever and the universe is resting on a load of turtles. Depending on who you ask, all these may be true, or false. But what is difficult to deny is that every day we generate and store information at an incredible rate.
We produced 2.5 quintillion bytes of data every day in 2020. When spread across the population, that means we each produce 1.7mb of digital data every second, the equivalent of 100,000 short novels every day – each!
What exactly are we doing with all of this information? Well, for the world’s most successful companies, it’s everything and can be the difference between success and failure.
Businesses like Google and Facebook were built on this ever increasing pile of data and have grown with it. These companies continue their inexorable quest to get us to keep producing even more.
However, many industries – including insurance – have struggled to take advantage of this growing ocean of information, and some have barely dipped the proverbial toe into the Pacific.
Taking steps towards data-driven underwriting
It’s surprising that insurers have not done more with all this data. In this industry, business success is so dependent on knowing the likelihood of unlikely things happening, and estimating the impact these events will have. Lots of data would seem to make this easier.
On the flip side, it’s understandable. Insurance hinges on the relevance and accuracy of information, so that you can trust your inputs and clearly understand how they relate to risk.
Until recently, the use of third-party and external data (some of that 2.5 quintillion bytes) has been used to support the underwriting of risks. This presents more and more data to underwriters in the hope that they can make better decisions, save time and reduce claims. Underwriters can analyse and understand information, so it makes sense that more information is good, right?
Well, not necessarily. Many insurers are still getting to grips with what all this data actually means to pricing and coverage. And figuring out how to use masses of data, especially when it is not complete enough for underwriting, is proving to be a big challenge
But what if all this data was applied to the process of underwriting a risk? Where the data is not being used to determine a price but instead to manage the flow of the risk through the insurer. Today many underwriters across the market are spending time looking at information to determine if a risk is in appetite, or how big the opportunity is, or even if it has been sent to the right mailbox. They’re doing all this before they even start underwriting the risk itself. These tasks are not adding measurable value and add up to a huge resource burden for insurers.
This presents the opportunity to use external data to solve a key expense problem, not to make single risk underwriting choices. There are many ways to reduce expenses in the insurance process, and augmenting risk information during submission and renewal can produce significant benefits.
It’s true: Augmentation equals profit
Insurers are starting to see how, when treated correctly, data can be used to automate the selection of in and out of appetite risks, route risks to the most appropriate team or person, and even prioritise risks based on lifetime value or expected growth. These tasks can be done in a fraction of a second using the latest machine learning and AI capabilities to collate the vast amounts of applicable data and turn it into unique, actionable insights for an insurer.
This goes beyond the traditional information underwriters currently have available to perform these actions. It benefits the operational function of an insurer, and can break the ever-present link between top line growth and the expense ratio.
Insurers have understanding risk down to a fine art. You only need to answer 20 questions about your business and they’ll take a £10m bet on you. But with all this data now available, the smart players are using augmentation to make themselves more effective, more profitable and more prepared for the future.
To read more about how you can augment submissions with external data, take a look at Cytora’s Data APIs here.
