The rate of transformation over the past decade has been particularly remarkable. The integration of big data and analytics, predictive models and automated underwriting has forever changed day-to-day work for today’s underwriters.
As with any change, opportunities come with risks, and subsequent trepidation. The fear of technology replacing underwriters, for example, is not a new one – the advent of both automated and accelerated underwriting sparked this now familiar concern. However, years later, we now know that underwriters and their analytical skills are more necessary than ever.
So how will artificial intelligence (AI) shape the future of underwriting? Answering that starts with defining AI and envisioning its potential.
In simplest terms, AI is the simulation of human intelligence by machines. Based on that definition, it is easy to see why concerns over job stability come to mind: If machines can simulate human intelligence, why can’t they replace underwriters?
For one, underwriting is an extremely client-centric occupation. Maintaining strong client relationships and effectively communicating decisions are key attributes of the job. AI lacks empathy and the ability to connect on a human level.
Additionally, AI’s decisioning is only as good as the data those decisions are based on. Bias and proxy discrimination remain a major concern for regulators, underwriters and consumers alike. Stakeholders need to exhibit significant caution or avoid utilizing nonmedical or nontraditional factors as inputs into AI models.
While AI will not be replacing underwriters anytime soon, or perhaps ever, AI is already augmenting and enhancing the decision-making process at many insurers. This will only increase as new digital underwriting evidence becomes more available and more standard.
AI holds great potential for automating and optimizing data-driven processes and facilitating underwriting decisions. For instance, AI can be used to sift through, normalize and de-duplicate large volumes of data to produce summaries underwriters can easily use to assess risk.
Additionally, AI can enhance predictive modeling by analyzing data to predict future outcomes. Predictive AI can provide consistent decisioning with populations for which clinical literature does not address certain correlations or is not up to date with medical advancements.
At RGA, we recently launched a major initiative to leverage generative AI capabilities in underwriting. The focus is squarely on providing efficiencies for the most rote tasks, freeing up underwriters to tackle more complex assignments and operate at the highest levels of their skill sets.
While I don’t think AI will replace underwriters, I do believe an underwriter’s job description will change, as it has many times in the past. But don’t take only my word for it, let’s hear what popular generative AI tool ChatGPT had to say on the subject:
“Future underwriters will need to be equipped with advanced data skills. They will need to embrace technology and have the ability to employ predictive model techniques focused on risk segmentation. They will need to continue to learn and adapt and will prioritize customer experience. They will be able to augment their own expertise with data-driven insights and will play a crucial role in leveraging data to enhance the accuracy, efficiency and profitability of underwriting.”
Even ChatGPT agrees: AI will be a useful tool for underwriters to use to enhance their craft, but the most advanced skill set will continue to be provided by the underwriters themselves.
At RGA, we are eager to engage with clients to better understand and tackle the industry’s most pressing challenges together. Contact us to discuss and to learn more about RGA's capabilities, resources, and solutions.
