Lead Forensics


Reducing the Underwriting Cycle Time

05.04.22 AdvantageGo

Underwriting is coming under a lot of pressure for change, especially during the last two years. Driving change in Underwriters’ (or any individual’s) thinking is a challenge; Underwriters, by their nature, are conservative thinkers.

What are some of the biggest challenges to overcome the “traditional underwriter” way of thinking when starting a change management project? What are some of the common misconceptions in regards to digital transformation in underwriting? How can best practices in change management enable Underwriters to underwrite more efficiently? These were some of the questions discussed during the ´Reducing the Underwriting Cycle Time´ panel held at the InsurTech NY – Customer First vs. Digital First conference.

Forces are disrupting commercial insurers from inside and outside the industry – many, underway before Covid, were accelerated by the pandemic. Insurers recognise the need to invest more in modernised underwriting platforms, and as core technology transformation projects proceed, how can Underwriters fuse their way of underwriting with algorithms and AI?

Kicking off the discussion, moderator Jeff Goldberg, SVP, Aite-Novarica asked the panel how the industry can support Underwriters through technology. Tom Anderson, Director of Sales, NA, AdvantageGo, explained that as a tech provider, one constant hurdle is this underlying fear that technology will replace the Underwriter, which won’t happen. Underwriters have a wealth of tacit knowledge and experience, which are essential. However, Tom explains that analytics-driven insights throughout the decision-making process are a game-changer, “What they might need is additional data; they might need additional run time, and, or, less pressure on them to return that submission back to the brokerage or portal or whatever it might be… we’re not trying to, as a solution provider, remove the Underwriter, we’re trying to make them exponentially better, faster, stronger, through technology, through data and all of that.”

The human mind is creative and full of imagination, but it gets tired and cannot perform at constant peak levels, according to Eugene Shafronsky, Head of Strategy, Thinktum. The underwriting process is complex, requiring the collection and assessment of enormous amounts of data. Eugene discussed how AI and algorithms are liberating Underwriters to focus on more stimulating and higher-value tasks, “So augmentation and the role of technology and AI is really designed to help Underwriters to really perform those boring tasks, and in return, they can deal with things that maybe require more creativity, more imagination, and more fun. I agree with you; it´s not about replacing Underwriters but augmenting them. If you look at the future, the future of underwriting will be different. My opinion, personally, I don’t think Underwriters will do much underwriting; they will do it with tech support, though will be involved in analysing data… and even more so, I believe, they’re going to be more involved in strategic decisions the company is going to be making, planning product development and so on.”

Empowering Underwriters

All panel participants agreed that algorithms and data-led decisions enable Underwriters to understand risk at new levels of granularity, but how do Underwriters get there? Tom believed it’s about empowering Underwriters, “Technology needs to empower Underwriters to provide insights and data and anything back to that agent-broker market so that they can go back the end insured. I’m still floored at the lack of knowledge that an end insured has about a lot of the policies that they have, and ultimately, I think that’s where the buck stops at the Underwriter to ingest, if you wish all of this data, use their experience, use all of that intellect that they have and then push that data back down the downstream cycles so that it can educate those end users.”

How does this work in practice? Brent Hammer, Innovation Officer, Grange, spoke about an experiment his company did where they were testing and validating solutions in a contained lab. Once the Insurtech was vetted, they would “throw it over the wall” to the Underwriters to see if it would stick. However, Brent explained that the method didn´t exactly work, “In the process, you have to involve the Underwriters, the stakeholders from the beginning.” Brent discussed a POC the company ran with where Underwriters were responsible for developing one routine chatbot question. Despite some hesitation from the start, they became advocates after getting involved.

Speaking further about Underwriting engagement, Brent emphasised that no matter how valuable the data is, if the technology isn’t easy to use, Underwriters will not adopt it. “Getting the data is one thing – if the Underwriters don’t adopt it, and Underwriters can be fickle creatures of habit. We actually had the Underwriters working together building a dashboard and designing the UX that the data was going to feed into. So on one end, we’re validating the data; on the other end, the Underwriters are validating the UX, and we married the two together.”

Moving onto how data supports better business, Jeff asked Eugene about the potential big opportunities for using better data and algorithms in the underwriting process, Eugene said, “Imagine an environment where Underwriters can create models for Underwriters, and imagine a world where you don’t need to use or utilise lots of resources or none at all from project management, from development from QA. When it’s done so fast and so quickly, imagine a world where Underwriters can experiment different flows and different sequences without having significant resources – how much time you’re going to save, how much faster and agile we can be.”

Adding to the discussion, Tom remarked, “You look at studies out there, continuously they’re saying Underwriters spend up to 40% of their time on low-value tasks. If we can reduce that by 25% or even 50%, how much more time now do the Underwriters have to go and actually do business value added by actually going in and helping us build out those workflows, or helping us build out use those UXs, that at the end of the back side from a low code no code or low perspective, or anywhere, we can fit that into the mold. If the Underwriters are bought in already on the UX, that´s easy; that´s the ultimate side of it. So reducing those low-value tasks to me, in my opinion, is probably one of the top things we need to do as an industry.”

Wrapping up the panel, Jeff outlined the key takeaways from the session:

  1. Empower Underwriters
  2. Get rid of the low-value work that Underwriters are currently doing
  3. Involved Underwriters from the start in the creation of algorithms
  4. Turn the black box into a transparent box – it´s about making smarter, not faster, decisions