Insurance Edge caught up with Dan Dingley Head of Insurance Business Development and Matt Elsom VP of Risk from Artesian Solutions recently to learn more about how tech is transforming underwriting. In particular, how their ARCH software product can help underwriters assess risk faster and with more accuracy.
It’s all about the data – and how you use it.
IE: Has underwriting been relatively unaffected by insurtech so far, and if so why?
ART: Yes in some ways it is still quite a traditional process, driven by legacy systems and high-touch manual processes. Whilst in the personal lines sector the high volume, low margin nature of transactions has made the market ripe for disruption, in the commercial lines sector where transactions are more nuanced and complex technology, specifically automation, has been slower to permeate. ARCH was designed with an appreciation of this.
IE: Tell us a bit more about the value of structured vs unstructured data – where’s the value?
ART: The increasing availability of data in itself isn’t always a good thing, it can be hard to find the pinpoint the commercially valuable intelligence when there are just so many data sources. Underwriters and brokers need to pull out the right information and make it actionable, whatever the source. Layering over unstructured data from news and social media to structured data sources and adding in to that underwriting/broking skill in calculating risk provides the most comprehensive picture.
Everyone in the insurance underwriting sector is looking to sift as many gold nuggets from the data mine as possible. What we are doing with ARCH is essentially taking the data and applying the insurer’s own policies to it, to present not only a clear summarised view of risk to the underwriter but also raising flags for any potential issues that require further investigation without flooding them with unnecessary data. ARCH is fully configurable in order to reflect company policy or even specific policies for an individual book of business, enabling underwriters or brokers to make decisions aster, improve their ability to segment risks, improve customer experiences and reduce costs.
IE: The `know earlier’ feature sounds very useful, tell us more on that front;
ART: Everyone has got certain standard hygiene processes if you like, for example let’s say you’re underwriting commercial risks, the first things to look for as regards structured data are things like disqualified directors, receiverships, general company finance news or statements etc. You can find out those risks very early in the process when using ARCH.
It’s a process that only takes seconds usually, and you can instantly drive the enquiry in particular directions.
Find out more about identifying risks, claims, key people and managing your client data, request a demo by clicking the image above.IE: Can’t people simply Google a great deal of this financial info nowadays though?
ART: Yes they can, but not everyone searches Google in a rigorously scientific way; you can easily get side-tracked, or ask for results in the news section, rather than searching all channels, in all countries.
It is also worth considering that Google, or other websites, may well put more a positive, slightly corporate slant on some of the data online, companies use SEO and PR tools to bring positive news stories to the top and bury negative stories deeper in searches. It isn’t necessarily the exact information that an underwriter might want to find out. For example, you may find a great deal of news stories on C-Suite executives moving jobs, having roles re-defined, or working across new territories etc. Interesting, but does that have an underwriting impact, is that truly useful data? Google Page Rank is not always insurance industry Page Rank. ARCH isn’t impacted by this or cookies/ads etc. it looks deeper.
IE: So this is a more insurance centric, bespoke kind of data mining?
ART: Yes that’s right, ARCH is a data research tool, with an insurance related focus. We have spent quite a few years building ARCH and we’ve done so in consultation with some of the UK’s leading insurance businesses. Insurers, MGAs and brokers alike need something that can automate a great deal of the insurance delivery process, yet still allow that human flexibility when it is needed. You will always want that fine balance.
Commercial risks can be very complex and involve multi-national companies, with assets in different locations, so it makes sense to use algorithms to process as much data as possible, and raise flags if necessary, before there is a human intervention. We’ve listened to people working within MGAs and insurers so that the batch processing of data that ARCH does is integrated into a coherent overview of risk. It doesn’t try to replace what’s gone before, but it certainly does enhance the process.
IE: You talked earlier about sifting the gold nuggets from the base metal when it comes to data, how does work with things like renewals?
ART: The great thing about ARCH is that you don’t have to wait until renewal time on a policy to do the data analysis. An insurer or intermediary can run their client’s history through ARCH every day and see things like financial statements, disputes, regulatory changes in a particular market and so on, and then reassess the overall risk.
That means long before issuing the renewal they have the data to make a judgement on new circumstances surrounding the overall risk elements; and review whether they need to change the price based on specific events or factors that are essentially being noted in real time, with any adjustments to pricing being made along the way.
IE: So ARCH isn’t just a handy tool for analysing new business, it can be applied throughout an underwriting book?
ART: Exactly. It can screen an entire book of existing customers and within that search, hone the criteria in specific directions, so an underwriter can pull out the stuff that matters.
The thing about underwriting is that it always has been a case of interpreting the information to assess the true risk. What ARCH does is blend the traditional art or skills or the underwriter with science, compressing years of experience and skill into a few seconds of searching. The great benefit of InsurTech in general is that it is automating a huge amount of the unseen processing, as well as the actual gathering of data.
IE: Of course all this has a healthy impact on the bottom line when it comes to profits too?
ART: Absolutely. Ultimately ARCH is all about increasing the accuracy of underwriting all kinds of risks, not just the speed of offering quotes. The more AI and machine learning algorithms can understand about the variety of risk that underwriters deal with on a daily basis, the bigger the boost to the profit ratio in the long term.
IE: Thank you for the insights.
This feature was produced in association with Artesian Solutions
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