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Despite artificial intelligence (AI) being one of the hottest trends of 2023, we’re still in the early stages of the technology. 2024 is poised to be an even more impactful year on the AI front, a time when we’ll move from the “what if” conversations of AI and machine learning (ML) to the practical uses for such groundbreaking innovations.
In the insurance industry, AI represents incredible potential to accelerate the speed at which carriers innovate. It can transform customers’ interactions with their carriers, improving each touchpoint by arming employees with relevant and up-to-date information and speeding up onboarding, claims, and more. AI can also directly impact the bottom line for insurers, helping to ensure policies are within the desired parameters for financial performance.
Conversations about AI tend to be forward-looking in nature, but the technology is already putting in the work behind the scenes to improve customer service and financial performance at insurance carriers. Let’s look at a handful of ways that AI is being used today, and see a bit more that explains why McKinsey expects AI technologies to add up to $1.1 trillion in value annually across the insurance industry worldwide.
Data collection and analysis
One of the most common uses for AI is collecting, organizing, and analyzing massive amounts of data and then parsing it into meaningful and understandable data sets. AI systems can be fed a continuous stream of data and a carrier can extract useful insights simply by telling the system what information they’re looking for—for example, claims rates dependent on geography or customer demographics.
Before AI, when reviewing the data, users would be limited to the parameters built into the system—a static, pre-set field of results. But now, users can query the system in plain English with whatever question comes to mind; AI can understand the ask and then provide a dynamic answer pulled from the data. Most insights are just a query away with AI running through the troves of data in mere instants.
Data crunching isn’t relegated to the office, either; it can be useful out in the field. Some auto insurers equip sensors on insured vehicles that can relay crash information to the carrier’s claim system. AI in that system then processes that data and determines if the car can still be used safely or not. If it can’t, the AI can then assist in locating towing and vehicle repair services nearby. These sensors also help in the claims process by providing detailed information on the accident.
Faster employee onboarding during claims
When a customer is waiting for agent assistance during a claim, every second of delay lowers the chance they will walk away satisfied. AI’s intelligent analytics capabilities provide employees with the most pertinent information they need about the customer, their coverage, and the claim right off the bat so the agent can start helping right away. Natural language processing (NLP) functions in AI also make it easy for agents to query the system and get back relevant and accurate information so they can best assist the customer.
Better customer service, underwriting, and personalization
AI is being used to speed up workflows for insurance carriers in many aspects of their business. Those NLP functions that can understand text make it possible for insurance teams to feed into the system custom parameters for underwriting, customer preferences, and risk tolerance and have a policy recommendation come out the other side. The more advanced AI models will also build out workflow processes that carrier employees can follow through with in order to complete the underwriting process. With AI driving the business processes, many insurers have seen their employees work more efficiently and the time to resolution for many customer issues shrink accordingly.
Speaking of onboarding, bringing new customers up to speed in a carrier’s system quickly is one of AI’s most dramatically impactful effects for insurers. Whereas the average amount of time onboarding a new customer can traditionally stretch on for as much as ten weeks, utilizing AI platforms can get that number down to just a day or two. AI is used to efficiently collect information on the customer—whether provided by broker, salesperson, or by the customer themselves—and guide employees through verification, screening, and other due diligence processes.
Ease in maintaining compliance
Regulations are popping up left and right across the US and the broader world around everything from emissions to data security to forced labor prevention. Compliance is an often overlooked risk category, but fortunately for insurers AI’s data-gathering and understanding of context and trends can help with staying on the right side of regulations today and tomorrow. AI can be trained to understand the parameters of a new regulation, analyze a carrier’s data to determine the potential level of risk they’re exposed to (for example, if a new partner being brought on board has a history of noncompliance themselves), and offer recommendations for the changes needed in order to meet requirements.
More AI innovation on the horizon
Unsurprisingly, given the intense amount of attention ChatGPT and similar models have received in the past year, generative AI applications are being brainstormed across many industries; insurance is no exception. Industry leaders expect that insurers will be able to customize and speed up underwriting and claims-assistance services using chatbots and generative AI that knows the customer and broader context inside and out, thanks to having access to (and being trained on) the carrier’s own data.
There’s also going to be an uptick in autonomous vehicles on the road, both personally owned and taxi-like services. Again, this is specific to auto insurers, although automation in other fields like manufacturing and construction is also set to increase. If automated vehicles proliferate as some analysts predict and the technology is as effective as we hope, there might be considerably fewer accidents on the road. As a result, we could be looking at a broader change in the auto insurance landscape, according to McKinsey.
AI might also have a major hand in helping property insurers account for the effects of climate risk during the underwriting process. This would help carriers adapt to a changing world faster and risk fewer losses due to otherwise unforeseen changes, particularly in the real estate space.
In summation, AI’s already more ingrained in the insurance industry’s day-to-day than most people realize, and the early adopters of the technology are already starting to reap the benefits. But much more is to come, and some of the most exciting AI applications in the industry are just now beginning to come to light.