The Impact of AI on Claims

Episode Notes

Transcript

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Announcer: This is the “Best Insurance Law Podcast,” brought to you by Best’s Recommended Insurance Attorneys.

John Czuba: Welcome to Best’s Insurance Law Podcast, the broadcast about timely and important legal issues affecting the insurance industry. I’m John Czuba, managing editor of “Best’s Insurance Professional Resources.”

We’re very pleased to have with us today expert service provider Dan Thompson, president and CEO of DeeGee Rehabilitation Technologies with offices in Ontario, Canada, and Arizona. Dan has worked within the litigation arena for over 25 years. Dan is a registered rehabilitation professional, registered vocational professional, and a certified life care planner.

His company services include providing expert opinion to insurance carriers, attorneys, and medical professionals by assessing the needs and vocational capabilities for people with disabilities. Dan, always a pleasure to have you with us.

Dan Thompson: Thanks again for having me, John. I’m pretty excited about this topic. AI is going to take over all industries. Thanks for having me.

John: Terrific always having you. As Dan mentioned, today’s discussion is how AI is impacting the insurance industry and claims in particular. Dan, for our first question today, how is AI impacting claims today?

Dan: Sure. Before I answer that question, what is fundamentally important is to discuss exactly what AI is. Most people have a general understanding. I don’t think they quite understand it. They’re probably impacted by AI on a regular basis and don’t even realize it.

For example, AI, or artificial intelligence, it refers to the simulation of human intelligent processes by machines, especially computers. These processes include the acquisition of information and the rules on how that information to reach approximate or definite conclusions and, more importantly, the self‑correction of that information.

The goal of AI is to create systems that can perform tasks that typically require human intelligence, ultimately improving efficiency, productivity, and decision‑making across diverse domains. AI encompasses what we call machine learning. That’s a subset of AI that focuses on enabling computers to learn from data and improve over time without being explicitly programmed.

ML, which, of course, is machine learning I just mentioned, those algorithms can recognize patterns in data and make predictions or decisions based on those patterns. Deep learning, which is also a subfield of that ML, it uses neural networks with many layers, hence the deep, to learn complex patterns from large amounts of data.

Deep learning has been particularly successful in tasks such as image and speech recognition. Of course, I use speech recognition to produce all of my reports. Otherwise, I wouldn’t have the productivity that I have today.

That natural language processing that we talked about, it’s also a branch of AI. That enables computers to understand, interpret, and generate that human language. The natural language processing algorithms, they power the virtual assistants, chatbots, and language transitional services. They also do the sediment analysis tools.

Computer vision, which is another branch of AI that enables computers to interpret and understand visual information from the real world. Police officers use this on a regular basis when they’re looking for character recognition from cameras to identify potential perpetrators.

Robotics is also created intelligent machines capable of performing tasks autonomous or with minimal human intervention. Robotic systems often incorporate various AI technologies or techniques to perceive their environment, to plan actions, and to interact with objects.

Finally, the expert systems, it should be noted that AI is designed to mimic the decision‑making ability of human experts in specific domains. Eventually, who knows, it may even replace me. Now that we’ve established exactly what AI is, I can better answer your first question, John, which is, how is AI impacting claims today?

AI plays a significant role and aspects of insurance claim processing, offering specific benefits to both the insurance company and to their customers. First of all, there’s fraud detection. AI algorithms can analyze large volumes of data to detect patterns is indicative of fraudulent behavior.

By flagging these suspicious claims early on in the process, AI helps insurance providers provide losses or to prevent losses I should say, and to maintain the integrity of their operations, claims processing automation.

Now that basically allows them to create the workflow processing claims. The initial claims submission to the final settlement. That same natural language processing algorithms that we talked about before, it can extract the relevant information from claim documents, reduce the need for manual data entry, and accelerate the decision‑making process.

They can also help in risk management. AI models can assess the risk associated with individual claims by analyzing their history, the policy details, and external factors such as weather patterns, or economic indicators. This helps the insurers prioritize claims and allocate resources more efficiently.

Customer service, AI‑driven chatbots, and virtual assistants that we talked about before can handle customer inquiries related to claim statuses, the policy coverages, and other common issues by providing 24/7 support and personalized assistance. AI enhances the overall customer experience and it reduces the burden on human representatives.

The predictive analysis, basically, AI algorithms can analyze historical claims data to identify trends and predict future claim outcomes. We talked earlier before we got on air about weather patterns and how things are going to get worse, and how they initially predicted there was going to be a lot of snow, and then that the winter season being above zero, so we mostly had rain.

Now this enables insurers to proactively mitigate risk, to adjust pricing strategies, and to optimize resources and where they’re going to be allocated. Then of course, in the settlement optimization, AI can optimize the claim settlement process by determining the appropriate amount to pay based on policy coverages, the damages assessed, and other relevant factors.

By streamlining this process, insurers can reduce administrative costs and improve customer satisfaction. The bottom line is AI empowers insurance companies to streamline claim processing, enhance risk management practices, and deliver better experiences for their policyholders.

John: Now, Dan, you had also mentioned before our time you’re going to be attending a defense attorneys conference in the near future. I very recently was at the PLRB conference up in Boston, and they had two different companies that were pitching their AI technology and services.

One dealt exclusively with workers comp and said they stay out of the life health arena altogether. The other company tended to have a broader reach and covered both sectors. What have you seen AI and more? Was it PC or life sectors? Which sector do you see AI potentially, most impacting?

Dan: I see it being adopted by businesses across various industries. That would be technology, finance, healthcare, retail, e‑commerce, manufacturing, transportation, logistics, media and entertainment, as well as energy and utilities.

Overall, AI is increasingly pervasive across all those sectors as organizations recognize its potential to drive innovation, improve efficiency, and to gain a competitive advantage in today’s digital economy.

Now, we talked about where it might have the biggest impact. The biggest impact, even though it’s in customer service, data analysis, insight marketing, and advertising, but it’ll have the biggest impact in healthcare. In essence, the adoption of AI is going to improve the greatest impact on health sciences because it’s only going to continue.

Look at the Apple Watch. Look at the fact that you can do your own heart monitoring right from your own house and then have all that data transmitted to your doctor. There’s clear competitive advantages in using AI now and in the future as well.

John: You already spoke about a lot of advantages. Are there any other benefits AI could potentially bring to the claims management process?

Dan: Most of what we talked about is it. There’s also potential downside or detriments, I should say, as well. The benefits, we’ve talked about. If you look at the potential pitfalls, there may be biases or fairness. AI in systems can inherit biases based on the data used to train them. They’re only as good as the programming that goes into them.

Again, how many people have been arrested just because of the color of their skin because the system is looking for someone who might be White or someone who might be Black? It’s important to still have human oversight to look at that, the lack of transparency.

Deep learning models in particular can be highly complex and difficult to interpret. It makes it challenging to understand how they arrive at specific decisions or predictions. The lack of that transparency can erode trust in AI systems, specifically in critical applications where transparency is essential. Hence, just look at the “Minority Report” movie with Tom Cruise.

Now, data privacy and security. AI systems often rely on vast amounts of data, raising concerns about privacy and security. The mishandling or the unauthorized access to sensitive data can lead to privacy breaches, identifying them, and other security risks. Just turn on your local newscast. That seems to be happening on a daily basis.

The over‑reliance on AI without proper human oversight, I think it can lead to the complacency and errors. It’s essential to recognize the limitations of AI and ensure that humans remain in control, especially in high‑stakes situations where improper arrests could be made.

We’ve already discussed in previous podcasts, AI will cause job displacement which, in turn, will cause some jobs to become obsolete as AI technologies advance, requiring workforce retraining and adaptation.

Let’s look at the ethical dilemmas. AI introduces new ethical dilemmas and challenges, such as autonomous weapons, privacy infringement, and the impact on social interactions. Addressing these ethical concerns requires careful ‑‑ I should say ‑‑ consideration of the societal implications of AI technologies.

Now, its reliability and robustness. They could be vulnerable to adversarial attacks where malicious inputs are deliberately crafted to deceive the system. Again, just watch “60 Minutes.” They’ve had several featured episodes on alleged Chinese and Russian attacks on, not only US citizens but also on our electoral systems.

Regulatory and legal issues. The rapid advancement of AI has outpaced the development and the regulations and legal framework to govern its use. Clear guidelines and standards are needed to address the potential liability, the accountability, and other legal issues associated with AI technologies.

Now, to address these pitfalls, I think it requires a multidisciplinary approach involving collaboration amongst technologists, policymakers, ethicists, and other stakeholders to ensure that AI is developed and deployed both responsibly and ethically.

John: Dan, you made a comment earlier ‑‑ as we head to our final question here ‑‑ what really resonated is when you said AI could potentially replace me. Now, I have spoken to a couple of adjusters recently. They felt that, regardless of how widespread AI is, it’s never going to replace the human element. My final question is, what do you see for the future, Dan?

Dan: Sure, John. The future of AI holds immense potential for future advancements and transformative impact across various employment fields. Some key trends and possibilities for future AI may include the same advancements in that deep learning that we talked about before.

In that area, basically, what you can do using AI. I can put in one of my reports and I can say, “Clean this report up.” Better still, I can use AI to, say, create a peer‑reviewed paper on AI or create a peer‑reviewed paper on attendant care needs.

I don’t think, I think you still need that human intervention that we talked about before, but I think your adjusters may be incorrect on that because you may only need 1 claim supervisor or 1 adjustment supervisor, as opposed to having 10 adjusters and then having that 1 supervisor.

The AI technology eventually may replace those people and come up with a quicker and perhaps more accurate solution. I don’t think it’s there now, but it may get there in the future.

Then if we look at the human AI collaboration, AI will eventually augment human capabilities in various domains and will empower individuals and organizations to achieve higher levels of productivity, creativity, and problem‑solving.

Again, in previous issues, we’ve discussed how putting a computer chip into a neurologically impaired individual’s brain can overcome those limitations.

Then further still, to demonstrate the power of AI, John, most of the answers to your questions were produced by generative pre‑trained transformer, that is GPT. They’ve advanced to level three now. That’s a type of artificial intelligence language model developed by Open AI.

What Open AI means is that anybody can add to the technology. Instead of being proprietary, you’re going to get new and innovative ideas on how to develop this technology for the future. AI is quite amazing, and I can’t wait for the future to happen today.

John: Dan, thanks so much for joining us today.

Dan: Thanks for having me, John.

John: You were just listening to Dan Thompson, president and CEO of DG Rehabilitation Technologies with offices in Ontario, Canada, and Arizona. Special thanks to today’s producer, Frank Vowinkel. Thank you all for joining us for Best’s Insurance Law Podcast.

To subscribe to this audio program, go to our web page www.ambest.com/professionalresources. If you have any suggestions for a future topic regarding an insurance law case or issue, please, email us at [email protected]. I’m John Czuba. Now, this message.

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