This latest piece by Rory Yates, Global Strategic Lead, EIS, looks at underwriting transformation and utilising the true power of data. Insurers have to get it right on pricing, claims and more.
This year, I was lucky enough to participate in Capgemini’s world property and casualty insurance report. Titled ‘How to Become an Underwriting Trailblazer’, the report asked why underwriting transformation has failed, and what needs to happen for it to be successful? Unsurprisingly, it was clear quite quickly that underwriting’s future will be increasingly machine-augmented. It’s also clear the transformation potential is centered around data.
The likely efficiencies in automation and processing power, driving greater accuracy and new insights. All in a bid to form the ever-more adaptive underwriting model. However, using technology to drive transformation is all well and good, but it doesn’t happen in a vacuum. Successful technological transformation is the result of change being embraced by the people operating in that area. Certainly, this isn’t something that’s confined to underwriting but is prevalent in complex areas such as this that are highly regulated and where mistakes can cost the organisation dearly.
When you transform, you’re pitching tried-and-tested technologies, processes, and partners against the unknown. Changing long-engrained behaviours is never easy, especially when those systems and processes are there to protect the people operating that role. To overcome this, it’s important for them to be included in the process of change, to understand their points of view, and help them see why the change proposed will deliver a better outcome for them.
This is because people’s mindsets only really change when you can answer the question, what’s in it for me? Change often raises concerns. Such as the potential erosion of job value. It also highlights the universal truth that having a silo’d and specialist role like underwriting has led to high degrees of control for underwriters.
Some of this is important and useful control. Humans need to be accountable and responsible, even with the advent of advanced technologies such as AI. After-all, AI can’t be a black box. It must be transparent, founded on good data, and set around humans who
remain in control and in the loop of every outcome.
The positioning that comes out of this research therefore leans towards an exaggerated frame of cyborg underwriting vs. super-charged human lead underwriting. The latter being rather obviously a better outcome for everyone. However, talent remains a key issue. As a cohort, underwriters are significantly aging and many will be leaving the industry over the next decade or so. In parallel, we’re also facing a
severe gap in the talent needed to fill this upcoming exit through retirement. This gap has then been exacerbated further due to the failure to transform the role and make it attractive to younger talent.
The vision and the clarity of what a transformed future looks like remains unclear for many in the industry. There’s no doubt that insurance relies on capacity, affordability, and availability. Or that underwriting sits at the fulcrum of all three. The big unlock appears to be to address the design of the organization within which the underwriting function sits.
The enterprise design, as I often call it, has to shift as well. This is because the real win is when the underwriting function decreases the time and effectiveness between analyzing data, extracting key insights from it, and acting on it. Which ultimately means getting it into the hands of a customer faster. This shift is about treating data as a perishable asset, constantly mining it for insights, and acting on it, as close to real-time as is possible. It’ll unlock many people’s vision of new propositions in insurance. Risk-mitigating, adaptive, embedded into our lives, and formed around deeper and more meaningful relationships.
Underwriting transformation in a wider context could unlock so much potential, and my key takeaways from this report were therefore:
Insight One: Data fluidity is key
Data has always been at the heart of insurance, but we haven’t always made it as close to real-time as possible treated it as a perishable asset and constantly mine it for insight.
Insight Two: Talent is a problem
Underwriting is the beating heart of insurance today and much more needs to be done to attract the next generation of underwriters who’ll help drive its transformation.
Insight Three: Underwriting has to become more than terms and a price
Prevention is better than cure. So mitigation is always worth more to all parties than products built on a higher risk and potential for payout.
Insight Four: The process between data analysis and product outcomes needs to be dramatically reduced
Intelligence is derived when data is acted on – the time between new data to insights to predictive outcomes to productisation (mitigation or pricing in experiences). This report delved deep into what is needed to unlock underwriting’s future and is fraught with opportunity. A lot of these insights aren’t strictly brand new, though, and a lot of people will recognise them. Rather than dismissing this, we need to understand why they remain true.
This is about unlocking the potential to successfully transform. Putting underwriters back at the heart of products. Getting them to start to develop new propositions and business models like it’s their day-to-day. To do this, we need to make sure they are operating in data
fluid, intelligent, and highly productive environments and organisations. This will take a lot more than just tech.
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