AI and the Future of Insurance

At the start of 2023, Artificial Intelligence was just another buzzword in the online space. Over the last couple of months, it’s fast becoming a cornerstone of innovation in the digital age. In the insurance industry, AI can be a handy tool to level the playing field against larger competitors and thrive as the landscape continues to evolve. 

This article delves into how AI is transforming insurance and how it will continue to shape the industry. It also covers real-world use cases showing how mutuals can leverage AI to stay relevant and attract more policyholders. 

Unpacking LLMs: AI’s New Frontier

Large Language Models (LLMs) are statistical models trained on massive data sets of texts. This training is focused on the statistical relationship between words and phrases so that they can generate texts that are similar to the text they were trained on. 

When you engage with an LLM, it's not merely recalling the stored answers like a search result. Instead, it's statistically analyzing and crafting a contextually relevant response. This level of response is so intuitive that it can even appear to make decisions based on inputted data. 

The simplest way to look at AI is as a mechanism that lets you converse with your computer. It's like having a super knowledgeable assistant who has read a ton of books, websites, and other text from the internet and can therefore talk to you about almost anything. 

Used properly, this can be an incredible resource for streamlining both internal processes and client-facing functions within your mutual. 

Democratizing AI For Today’s Insurers 

A few years ago, you'd imagine that this sort of cutting-edge technology was the sole domain of large corporations with bottomless budgets. But today, this is different thanks to AI technology’s open-source nature. 

Open source means the technology available publicly and is free. Certain licenses even allow AI models for commercial use. This means that with some technical expertise, you can store them on your local computer, host them like you host a website, or even develop around them. 

The accessibility of this technology evens the playing field for large and small mutuals alike. Take for example, Hugging Face — a platform showcasing over 300,000 trained open-source models, datasets, and other resources — all of which are readily available for commercial use with free account options. 

Now this might be of little interest to an insurance executive. But think of what you could accomplish with the right professional help. And we’re not even talking about top-tier tech wizards. Many of these LLMs allow you to put things together without coding experience. Plus even if you hire a professional, you usually don't need a big team. That’s why it's such a game-changer. 

Used strategically, even the smallest mutuals have a unique opportunity to improve their internal operations or to blaze new trails in policyholder engagement. And because they're smaller, they are able to move faster and make quicker decisions compared to bigger players. 

AI in Insurance 

AI technology opens up a myriad of exciting opportunities for the insurance industry. Some practical use cases you could explore right now include: 

Connect directly with customers 

Instead of using intermediaries like insurance agents as a primary point of contact, you could leverage AI to connect directly with their customers from the get-go. So it’s like owning or running an insurance agency that is predominantly operated by AI. Not only is this more cost-effective, but it can actually be more attractive for policyholders since there’s no middleman.  

As a practical example, you could get ChatGPT to assume the role of a commercial insurance agent interviewing a prospective policyholder to put together a summary of cover based on their specific needs. Here’s the full thread.

While this is just a simple example, it shows how easily you can put a system together and build on it to automate customer engagement and handle countless interactions simultaneously.

Enhanced customer experience 

In insurance, trust is the most valuable thing you offer your customers. However, that trust doesn't just come from policy coverage or claims processing. It stems from an overall experience that begins the very moment they make contact with you. 

Leveraging AI can help elevate this experience in several meaningful ways, such as utilizing available data to further personalize customer communications. 

For instance, you could train ChatGPT or a suitable AI model on a large data set of your customers' most common inquiries and responses, including answering questions about coverage. Now you have a system that can instantly answer customer questions and respond to inquiries 24/7.

Streamlined processes

You could also get ChatGPT to summarize a policy so its terms, insuring agreements, exclusions, and other relevant details are easier to comprehend. This could then be an option for policyholders to ensure that they fully understand what’s covered under their policy. 

Imagine a scenario where a policyholder has a question about their coverage. Instead of sifting through pages of policy documents or waiting on hold for a customer representative, they can interact with an intelligent system that not only understands their query but responds in clear and understandable language. It’s like having a conversation with their policy. 

Wouldn't it be great if you could give your policyholder this type of customer service? 

Challenges and Limitations of AI

While AI has transformative potential for the insurance industry, it's not without challenges and limitations. The most common ones include: 

   • Hallucination — These are instances where the AI system generates or perceives information that is not rooted in its input data or real-world context. 

   • Data Privacy Concerns — AI applications require vast amounts of data, which raises concerns about data privacy. Insurers must navigate complex regulations and ensure the security of sensitive personal data.

   • Decision Transparency — AI algorithms are often referred to as 'black boxes' due to their lack of transparency. This opacity can be problematic when AI makes critical decisions, such as denying a claim or setting premium rates. 

   • Bias in AI Models — AI models can perpetuate existing biases if they're trained on biased data. This could lead to unfair outcomes, such as discriminatory pricing or unjust claim denials.

Ultimately, these issues will go away over time as the tech advances. 

Next Steps

AI is already impacting many industries and it’s only a matter of time until we see the technology being widely employed in the insurance space. Soon the question won’t be “Are you using AI?” but “What AI are you using?”

Luckily, it doesn't take much to incorporate AI into your mutual’s operations. 

Imagine if a few non-competing mutuals across different states came together to hire one development team to generate the AI structures they need in their organizations. They have similar interests and their respective operations do not negatively impact each other. So why not team up to hire one CTO to oversee the deliverables and pay for it jointly? 

Nearly 30 years ago, Bill Gates said if your business is not on the Internet, it will soon be out of business. Given the spate of innovations in recent times, we can expect the same to happen with AI, except a lot faster. 

Don’t be a spectator. Now’s the time to act!