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How data enrichment can reduce risk PDF Print E-mail
Friday, 27 November 2015

Enriched data is enabling more precise new pricing strategies in the insurance industry as actuaries increasingly take commercial data into account.

By Craig Evans, Head of Business Development at Graydon

Enriched data is enabling more precise new pricing strategies in the insurance industry as actuaries increasingly take commercial data into account

Reduced risk and more competitive pricing – how enriching data analysis with commercial information is improving the outlook for insurers. I remember once meeting an actuary who’d just been to a big dinner for his profession. “What on earth do you talk about at a do like that?” I asked him. “Oh,” he said, “we tell jokes about chartered accountants.” Maybe actuaries need something to laugh about – non-stop number crunching to quantify risk and set general insurance premiums is an immense challenge, and the penalties for errors of judgment can be fearsome. But the likelihood of error is diminishing fast, and that’s because the actuarial profession is at the forefront of a growing number benefiting from the dawn of the Big Data era. It’s all part of what’s known as ‘data enrichment’ – the process of refining and improving the information that’s available to an organisation so that they use it to reduce risk and add value to their operations.

Considering new risk categories
This can include simply checking factual accuracy and weeding out spelling mistakes. But it’s in the area of selecting new strands of data to interrogate that I believe the greatest strides are being made at the moment. Today’s actuaries, for example, have unprecedented access to a constant flow of new information on which to base their calculations, enabling them to link different strands of data and take whole new categories of risk into account.

One example of this happening in action is taking place right now as general insurance companies increasingly consider commercial factors when setting their premiums. It doesn’t matter so much at the lower end of the market.

Take the case of a plumber - a sole trader -who wishes to insure his van. The level of risk he represents is determined by not much more than the kind of vehicle he runs, his postcode, his likely mileage and his driving record. So the potential downside to setting the wrong premium is relatively minor.

Widening the data-capture net
But what of a large, nationally-networked business that runs hundreds if not thousands of vehicles? Suddenly, the premium – and the risk involved – is very substantial indeed. And actuaries are quite understandably casting their data-capture nets more and more widely to take further strands into account.

For example, they can now ask, how well is the business performing? Are its turnover and profits heading in the right direction, or are there any signs of financial distress on the horizon? What of the industry or sector in which it operates – is the overall business cycle a healthy one, or are there indications across the market of crumbling confidence and declining company performance?

Most important of all, is there a discernible correlation between difficult business conditions and the number of insurance claims made? I can answer this last question myself. Yes, there is.

Defusing the fraudsters
When you look at the right data sets, you’ll invariably see a very close relationship between business performance and claims activities. This is probably no surprise to many of us. Every time a commercial building goes up in flames, it’s only natural for most people to wonder just how accidental it was. But having this knowledge to hand, proven in hard data terms, means that action can be taken in the form of setting higher premiums to cover the increased risk of fraudulent behaviour.

Of course, greater knowledge and deeper insights don’t always mean that premiums will go up. They can go the other way too. Having access to new datasets that enable accurate pricing based on the deeper understanding of the risk factors at play can enable insurers to compete harder on price with their rivals.

An increasing influence
So the return on investment delivered by taking commercial data into account can be immense, rising to millions of pounds for large insurers. But general insurance is only one market where the use of enriched data can have such massive impact – it’s also becoming increasingly influential across the commercial property and financial services sectors, for example, where understanding and managing risk is essential.

I believe that interrogating new strands of commercial data will soon be standard practice for any profession in any industry where the consideration of risk factors plays a role in setting prices and deciding whether or not to take on a customer’s business. In short, it’s set to play an increasingly significant role wherever companies need to consider and refine their customer strategies.

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