The role of AI in insurance claims – and the importance of human input

There’s hardly an industry that hasn’t been touched by AI, and unsurprisingly, it’s also an ongoing topic in the insurance market as businesses look at how to use the tech to simplify their processes. How prevalent is AI in the world of insurance, and crucially, how much room is left for human input? Let’s take a look at the impact of AI on the underwriting, actuarial and claims process, and how this is affecting talent in the industry. 

Overseeing underwriting 

We’re seeing more and more insurers using AI to simplify processes and perform repetitive tasks, thereby eliminating some of the things humans traditionally do. This includes the underwriting and claims process. Claims are tagged according to the various details of the case, and AI and predictive analytics can help to mitigate claims. Some clients or even third-party administrators (TPAs) use AI to expedite the claims process to handle simple tasks for them, instead of doing it manually. This means there is not as much demand for underwriting simpler risk, claims analysis, claims handling and other simple operations that AI can easily take over. 

When it comes to AI, the claimants aren’t being left behind. Customers are increasingly utilizing AI to analyze whether an insurer will fulfil a claim or not. AI allows them to assess and strengthen their case to give themselves a better chance of getting a claim through, and I’ve seen quite a few examples of customers winning their claims as a result. 

Upskilling in AI 

A lot of businesses are finding that you can never quite get ahead of the curve. By the time you’ve decided on a business case for AI, the technology has already moved onto its next stage. Staying up to date requires a balance of bringing in new skills while upskilling the existing workforce, so that you have the foundational knowledge in place and the capacity to adapt to any updates or new technologies. For candidates, upskilling is crucial to remaining relevant, particularly if certain aspects of their role can now be automated.  

We’ve spoken to several clients who are starting to roll out AI pilots, and rather than replacing their people, are introducing training programmes to upskill them to use it. This allows organisations to utilise their people for more complex tasks and, crucially, shows employees that the business is committed to investing in them. 

AI’s effectiveness hinges on data 

AI operates well when there’s a large amount of data to help it analyze, draw patterns and predict. For example, personal lines insurance for a driver, based on their driving history, model of car etc., will have a lot more data to draw from than insuring a building like the Rockefeller Center, as there are more drivers than buildings. We need human judgement for these tasks – and that’s why people are still irreplaceable. 

Human behaviour can be difficult to predict. AI can’t yet accurately factor in the potential impact of inconsistent human behavior and decision-making – the more volatile and unpredictable factors affecting markets. To continue the example of the Rockefeller Center, it’s particularly challenging insuring large buildings in the current changeable political environment, with the potential for risk to increase at any time. 

Again, human judgement and experience are important when it comes to assessing the potential impact of unpredictable events. Insurance, building or engineering surveyors are needed to inspect buildings in relation to insurance claims or assessing the level of risk for new policies. Similarly, it’s people who will price the policy and decide how much risk the company’s willing to take. Actuaries’ expertise will remain crucial in assessing risk and calculating premiums, and brokers will still be required to help customers find the right insurance. AI can’t assess these things just yet. 

Conclusion 

While AI is replacing some roles that are easy to predict and therefore, to automate, it can’t support the more unpredictable aspects of the underwriting, actuarial and claims process – so it’s not going to take over this work anytime soon. But it’s important that insurance professionals and organizations stay up to date with the latest developments and upskill themselves in order to remain relevant. 

AI is helping to free up time for underwriters and claims professionals to focus on more complex tasks. In the future, it might be able to more accurately predict natural disasters like hurricanes or snowstorms so as to prevent losses on insurance, but if and when it does, that will also come with liability. 

If you’d like to talk to me about the potential effects of AI on your role or organization, or you’re looking for your next opportunity or hire in insurance, please get in touch with me for an informal conversation.