Predictions for the claims industry in recent years have been heavy on AI. Even before the rise of generative models like ChatGPT, AI was steadily moving into the insurance sphere. Plenty of research referenced the potential AI had for insurance; the question posed by analysts was whether or not it would be well received. Most agreed that it showed promise: a 2017 paper by Deloitte notes that AI startups increased from 150 in 2012 to 698 in 2016, and McKinsey analysts gave AI in the insurance industry a whopping $1.1 trillion valuation in the same year. However, many decision makers couldn’t see the benefit for claims. 

This isn’t surprising when you look at similar research. According to Deloitte in 2021, most insurance companies still limited AI adoption to chatbots. Sure, it could optimize some of their existing processes, but what about new possibilities when it comes to the actual claims process?

Now, AI’s potential uses in the claims space are enormous. Just as McKinsey analysts predicted in 2019, and again in 2021, the world is experiencing an AI spring. There has indeed been a seismic shift in insurance, and AI supports, not replaces, the human workforce. So what do analysts predict for 2024? 

Here are a few of analyst’s predictions for the insurance industry:

Analysts predict AI will reduce underwriting losses in 2024

One of the biggest issues for the future of insurance is underwriting. Underwriting losses topped $32B in 2023. Factors from inflation to legal costs are putting a squeeze on insurers. Fortunately, AI has a potential solution. Unlike in the past, AI is being used for more than just chatbots and virtual assistants. Claims data and records, the kind of documents that can number into the thousands, accompanies an injury or accident - and needs to be processed by the insurer who is placing the claim. This means paying knowledge workers, and in effect, toppling a domino chain that covers everything from high turnover rates in insurance to reputation-harming delays. 

All of this means that AI is here to stay in 2024, at least when it comes to insurance. The industry might be one of the world’s oldest, but it’s ripe for disruptive change. If insurers won’t go willingly into the new technology frontier, rising costs will take them there - fast. 

Analysts call generative AI ‘a new productivity frontier’ for insurance

Analysts at McKinsey value the impact of generative AI on the insurance industry at $50-70 billion. This is generative AI alone - a subset of the the $1.1 trillion valuation released in 2016. Industry players in claims might be slow to adapt to this change, but the world as a whole is not. Insurance technologies are here to stay, and they’re part of a larger insurtech industry with lots to offer the claims professional. 

Consider this example from Deloitte. A customer looking for a car loan applies on the website of an insurer. A chatbot helps them input their information and the kind of policy that they’re looking for. This is all relatively common today — however, the example stretches to include an ‘anonymizer bot’ created to shuffle in the customer’s digital twin. This digital twin can be used to get insurance quotes (hopefully without calling the real customer), shopped around to underwriters, and expedited when it comes to policy selection. 

It’s not far fetched, especially given the advances we’ve seen technology make over the course of the last few years. Other productivity tools include extracting ‘digital fingerprints’, Edge AI sensors inside a car that are triggered when a customer gets in an accident or fender bender, and methods to extract data far faster and in greater numbers than ever before. This is not only possible, but likely - thanks to generative AI tools available to simulate the human brain. 

Analysts say AI will help catch insurance fraud

Customers who claim insurance coverage they do not need, or do not have, cause extra expenses for insurers. Not only do they need humans to catch fraud when it happens, they also need to assess the risk of this fraud and move forward with consequences. All of this is costly, and all of this impacts not only the movement in policy premiums (up, if efforts to combat insurance underwriting loss continue), but also insurance industry losses all the way down the value chain. 

Machine learning (ML) models capable of generating predictions through data will be at the forefront of change. ML models can scan and learn (in order to predict) patterns in massive volumes of data - which make them ideal for catching fraud and mitigating future risk.

Artificial intelligence is here to stay. Whether or not it gets regulated by governments, analysts suggest the insurance industry landscape will never be the same. As insurance policies shift towards higher priced, more personalized, offerings, the same analysts say this is how the claims industry will recoup its underwriting losses and move alongside life in a digital age.