We are currently seeing advances in AI and automation coming at a pace that is hard to keep up with. Underwriters are starting to recognize that they will need to adapt and in many cases acquire new skills so they can thrive in this era of AI.
Just how will we see the traditional skills of an underwriter changing?
A role that will evolve, not be replaced
The first thing to make very clear is that no machine is ever going to replace the human underwriter. It is a role that relies heavily on skills that robots simply cannot replicate, evaluating complex risks, refining portfolio strategy, using creativity and deepening crucial relationships with brokers. But AI allows for automating many tasks that have to date been performed manually and been time-consuming, such as data entry and re-keying.
Those repetitive, more menial tasks, such as sieving through data, reviewing data fields, trying to identify missing data fields, entering data fields to different systems, can take up one-third of the average underwriter's working day. Streamlining this process vastly increases efficiency and enables skilled risk professionals to concentrate on higher-value work.
See also: Insurance Underwriting Will Never Be the Same
Data-savvy underwriters
At a basic level, many underwriters will soon find that their job becomes less admin-focused and less monotonous. This will create the opportunity -- and the need, to keep up with the competition -- to develop a host of new skills. These include skills related to interpreting data, making consistently high-quality decisions and thinking of creative solutions.
To make effective use of data -- to understand it, apply it and make decisions from it -- you need to have, at the very least, a basic data education. Put simply, the next generation of underwriters will be much more data-savvy, applying the insights created by data analysis in a creative and thoughtful way.
Agility and creativity
The old, monolithic tech stacks are giving way to combinations of modular solutions that fulfil specific purposes. These platforms can quickly evolve to fit different needs. Consequently, underwriters will have to be more flexible in the way they work, able to upskill and adapt to different tech solutions.
We are going to see faster feedback loops between changing levels of risk and market conditions and portfolio appetite, which will mean that underwriters need to be adept at identifying emerging risks and opportunities in real time and making continuous refinements to portfolio strategy. Underwriters are going to be met with ever more complex and varied scenarios, with climate change, for example, having a huge impact on the insurance industry.
As volatility increases, the agility to identify changes in risk and operationalize refinements to portfolio strategy will become increasingly important. Underwriters will need to leverage the technology around them and come up with unique solutions to understand, manage and transfer risk. There is no textbook to tackle the challenges we are going to face over the next few decades -= the most creative underwriters will be the ones writing it.
See also: Why Underwriters Don't Underwrite Much
Multi-functional teams
Generative AI may well lead to new roles within the insurance sector, such as "risk flow engineers" and "risk flow experts” -- people who know exactly how to extract the most useful outputs for decision-making and continuously optimize risk flows. There will be digital trading managers skilled in monitoring the health and performance of digital trading -- providing critical human oversight. There will be underwriters who will use the time that has been freed up to further develop their broker relationship skills and develop a broader portfolio view.
Greater digitization and AI will also create more unity among underwriting, data strategy and technology teams. Siloed departments will become increasingly untenable. The best organizations will have multi-functional teams enabled by digital risk flows where information flows throughout the organization. Every team member will need the technical tools and expertise to work together.
The underwriting landscape is changing dramatically as a result of machine learning algorithms, data analytics and other AI technologies. While learning more about AI and technology will be critical for success, it is not as simple as saying there is a checklist of skills you really need to learn. Just as important will be having a curious mind and the will to constantly update your expertise and learn things.
As this transformation progresses, we can expect to see a new breed of underwriter that has developed skills around data analysis, digital literacy and critical thinking, but who is also creative, flexible and adaptable in the way they approach their role.
