Change isn’t a new phenomenon for the insurance industry. The introduction of technology alone has led to significant transformations. But with the integration of AI in the insurance industry, the rate of change has only accelerated. Carriers, both large and small, have witnessed how AI can reshape everything from marketing and underwriting to distribution and claims processing, improving efficiency, productivity, and cost savings — as well as the overall experience a customer has with an insurance company.
Automation gets most of the credit, and the reason isn’t unfounded. AI-based customer support is certainly an example of that. A chatbot can field questions, track claims, and even offer assistance in filling out any number of basic forms. This not only reduces response times for policyholders and improves customer satisfaction but allows team members to focus on more complex tasks.
However, it isn’t just AI’s ability to automate a range of responsibilities that are providing greater efficiency, productivity, and cost savings to carriers. In fact, one could argue that automation is just a small piece of a much larger technology trend in the insurance industry. Many of the gains have been found in data analytics — or, more specifically, the analysis of sizeable amounts of data, and then what that analysis and subsequent insights can do to improve the entire customer journey with the provider.
Understanding the Individual
When used strategically, AI allows carriers to become smarter. You can now enter into a relationship with a customer with a better understanding of the individual. With an accurate profile of that customer, you can offer more personalized coverage. As you then take it down the line, you’re also able to do things faster, and perhaps better, for that policyholder.
After all, insurance is in the predictions business. If you’re getting better predictions through AI, you’re making insurance better from the top of the funnel down. And thanks to advancements in AI and machine learning (ML), you can now better predict claims frequency and severity. Needless to say, this has had a significant impact on models — improving underwriting, coverage, and pricing around a policy.
The insurance claims process, in particular, can benefit greatly from the use of AI and ML. The technology can handle much of the process for your operations, adding both efficiency and speed by capturing, analyzing, and validating all the relevant data — even taking into account photographs, accident reports, loss reports, repair estimates, and a wide range of other documents. If then equipped with AI-based customer support, your business will be able to respond in real time with personalized updates for the claimant and provide the highly responsive customer service that most people now expect from all companies.
In other words, AI insurance claims processing ensures that all policyholders get the attention, engagement, and immediacy they need during what’s often a very stressful time. This can easily lead to improved satisfaction, better retention, and ultimately greater customer lifetime value.
The Right Framework for AI in the Insurance Industry
Whether creating your own solution or working with a third-party provider, AI in the insurance industry does require a great deal of due diligence on your part — both in terms of the tech and the people who will be using it. Instituting AI into distribution, underwriting, and the insurance claims process (among other facets of operations) will entail building the right framework for its use. Here are just a few things to keep in mind:
1. Understand the algorithms.
This isn’t about increasing your knowledge of code. Take the time to identify any emerging risks of the algorithms in use, especially when it comes to bias, transparency, and privacy. It’s important to ensure that AI isn’t introducing biases and is in complying with data regulations.
2. Experiment with the technology.
Experimentation doesn’t need to be exhaustive. AI is already improving efficiency and speed. Experiment with the validity of results and where you can utilize AI within your business prior to deployment.
3. Engage with the technology.
What many regulators expect from carriers — beyond evidence of proper governance and use of the technology in terms of data security, protection and retention — is that as you’re engaging with AI while complying with all applicable insurance laws and regulations. This includes unfair trade practices, as well as evolving with the industry, the technology, and the entire ecosystem. You can’t just establish a use case and then let AI run. It’s advancing quickly, requiring ongoing adaptations.
4. Prepare to reimagine the structure of operations.
One of the concerns with generative AI is that it will take away jobs from people, but what the technology will likely do is change the nature of work. If you have team members on staff who are collecting, sifting through, and synthesizing information, that aspect of the role may change. While the role may not disappear, it will likely take on different responsibilities. That may entail reskilling or upskilling of employees. It’s important to prepare and think about how the structure of your organization will look in the future.
As far as technology trends in the insurance industry go, AI is at the forefront. It holds the potential of transforming your business and helping team members provide the products, services, and experiences that consumers have come to expect from all companies — all the while providing greater efficiency, productivity, and cost savings that will directly impact the bottom line.
PIMA® (Professional Insurance Marketing Association®) is a member-driven trade association focused exclusively on the affinity market.
Published on January 29, 2024.
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