Transcription:
Transcripts are generated using a combination of speech recognition software and human transcribers, and may contain errors. Please check the corresponding audio for the authoritative record.
Patti Harman (00:06):
Welcome to this edition of the Dig In podcast. I'm your host Patti Harman, editor-in-chief of Digital Insurance, and today we're discussing how the insurance industry is adapting to different types of claims technology. The claims process is where insurers have the opportunity to make good on the promises in a customer's policy and handling them quickly and efficiently plays an important role in customer satisfaction. While technology usage permeates every aspect of the insurance industry, claims was one of the first areas to implement technology for filing the first notice of loss. To assess property damage in the wake of a disaster and to help expedite the settlement and payment processes, adoption and usage by both policy holders and insurance professionals is crucial to creating a positive claims experience. Joining me today to discuss the development and implementation of digital capabilities across the claims ecosystem is Lee Elliston Aspen Group claims Chief Operating Officer. Lee is responsible for the global operating strategy for claims for Aspen, including claims service and the extremely important customer experience, and he has over 20 years of involvement in claims leadership and operations. Thank you so much for joining us today, Lee.
Lee Elliston (01:34):
Thanks. Great to be here.
Patti Harman (01:35):
So let's start with a general overview of what you're seeing in the insurance claims space. How has it changed over the last five years or so and how does that compare to what you're seeing in the industry now?
Lee Elliston (01:50):
I think the last five years has seen the most level of disruption that I've seen in my career, and that's probably because of the advancement of InsurTech and speed and the ease that delivering technology solutions and data led solutions for insurers and insurers get the opportunity to almost play and test with different tools and different technology like you would in your personal life and see a benefit or an outcome far quicker than they may have seen historically. So I think that technological advancement has really started to shine through in the insurance industry, particularly in the claims servicing space as well.
Patti Harman (02:39):
Yes, I agree. It's been kind of exciting to see what's going on. What have been some of the greatest challenges in the claims space for insurers, adjusters and policy holders over the last few years?
Lee Elliston (02:54):
I think the biggest challenge is always the strongest opportunity and capability that people have, which is people in their organization. The strongest challenge I think has always been there historically and still is now, is around adoption. Adoption of the new technologies and the new processes and people feeling comfortable that they're in control of the same assessment in the claims process or the same level of responsiveness that their client or insured or broker may be getting, that they've always been getting as part of some manual processes that people have been accommodating for so long. So I think the adoption is still the greatest challenge and I think also as part of the challenge to integrate technology is your data. If you haven't done the work on your core data model and the processes that you've got around keeping data quality at the highest level, then you're going to struggle to get the most out of the technology and then therefore that suffers with the belief and the confidence that people have got in the implementation of it.
Patti Harman (04:12):
That's so true, and you're right, it's a fine balance between managing the data and the technology, but hopefully since people are becoming a lot more comfortable about using technology in their personal lives, that carries over into some of the other areas. I mentioned in my opening that claims is one area where there was some early adoption of technology, and I'm thinking in terms of drones and infrared cameras and other tech that made the claims process safer for adjusters and help to expedite the assessment process as well as the adoption of apps to help with the first notice of loss. Are you continuing to see an adoption of technology in claims and how is that changing the claims process now?
Lee Elliston (05:00):
Absolutely. We are seeing a continuation of technology being adopted within the claims life cycle. I think as you say, the focus has really been on the kind of drone capability or satellite imagery kind or capability for geo-based events that normally support TCA and weather events that we see across the globe. And I think that's been strongly adopted across many different insurers in different jurisdictions. I think the FNOL and the payment digitization has been the one that's probably been most focused on within the claims process, which I get slightly frustrated by because I think there are obviously small wings in the FNOL and the payment process, but it doesn't actually shorten the life cycle enough to make enough of a material difference for both the insurer and the customer and that lifecycle. I'm talking about the bit in the middle of the FNOL and the payment, which is all around what data and technologies can you use to help make informed decisions or a good assessment of the claim at different parts of its lifecycle, which might be assessing the claim past the FNOL stage.
(06:21):
It might be as you walk through the litigation stage and it might be different characteristics that come up in association with the claim as you start to develop and get more information on it. And I think that's the area that I think is still really ripe for having some technology applied to it, some AI-based assistance and rules on top of an organization's data to really start to inform some intelligent decisions that can be made far quicker in the claims process and that will really shorten the biggest part of the claim life cycle in between FNOL and payment. In my opinion.
Patti Harman (07:01):
I would agree with that assessment. I think there are a lot of opportunities there and that is where I think you will see the greatest opportunity. Once we're able to figure out how to expedite that process, that's where you will see the greatest impact, especially I think in terms of customer satisfaction. Are adjusters becoming more comfortable using technology and if so, what kinds of technology are they comfortable with? And is it making their jobs easier? Is it making them harder or a little bit of both?
Lee Elliston (07:36):
I certainly think from my experience, people are starting to get more comfortable with the use of technology. I think the challenge and the confidence has been in data in the more recent years, I think people have been used to getting data within their organization or within a life cycle of the claims process. They've been getting that data from a certain source or a certain individual within their organization and it's probably been coming out to them in some kind of Excel spreadsheet that they can tweak and work with and they've built some trust and confidence around that process. And I think now what we are obviously trying to do is create a lot more structured data in the process. So capturing that data out of unstructured documents that you get within the claims lifecycle and how we can get that in a more structured form and make that data available to people at the right points to make earlier and smarter decisions in the process.
(08:38):
And I think people are struggling with that switch to, well, your data is coming from a different source, it's coming in a different format, it's coming out to you in a very different way, i.e., through a claims platform or a claims system as part of the process rather than coming to you in a kind of staged and static report that you used to get whenever you used to just go to someone and request it. So I think there's a big shift going on there with regard to people understanding how data is so important in the process, how it underpins the technology and how it really is changing the way people consume the data and do something with it to make some decisions or change the behavior in the process.
Patti Harman (09:21):
I think that one of the biggest adjustments is being able to really use the data that's been collected all along and using it proactively so that it has such a positive impact on the entire claims process.
Lee Elliston (09:33):
Yeah, absolutely.
Patti Harman (09:35):
Are there certain technologies that are easier to adapt, whether it's using technology to schedule appointments or respond to inquiries, text messages, chat bots, that sort of thing? And are there others that are maybe a little bit harder when it comes to implementation?
Lee Elliston (09:52):
Yeah, I think the easier ones have been the chat bot technologies that have been used at the front end of the lifecycle, particularly in the FNOL process, the kind of apps and the forms that people have seen where people get the ability to raise a claim. We've started developing that ourselves at Aspen, but we've done so in a controlled way with our own technology internally because we think that we can base any rules and data collection around how we want that to flow for a bespoke line of business, a bespoke product, a bespoke insured or broker, and we've got people that sit around that process and can play a kind of QC role to make sure that the data quality is right, but also the process and the technology flow is running right to make it a lean and light touch process. The more challenging part of it is the AI element.
(10:54):
Now obviously there's a big boom around AI and generative AI with the use of chat GPT, that big boom needs some control and it needs an element of understanding of how can you apply it in the process? Are there risks to applying it in certain aspects of the process? And could those risks cause a consequence to litigation? Could it have an adverse effect to service and what you are trying to do for the broker and the insured or the customer? So there are elements that I think the industry are wrestling with at the moment. We are running a couple of proof of concepts around the use of AI and generative AI to run some decision based models based on closed claim data and that's informing case strategy, reserving strategy, and also some estimates around what a or reserve could be in the process. We haven't gone as far as an automated piece of technology making that decision, but we're providing that intelligence and we're running proof of concepts to provide that intelligence to our people to allow them to have more time to add value to the product and the portfolio that they're servicing, but using the data and the technology in the right way.
(12:16):
But that's where the biggest challenge is right now.
Patti Harman (12:19):
Wow. I love how you describe how you're using the data proactively and how it is supporting what your claims team is doing and helping them focus where they need to and still maintain that relationship with the policyholders. Do you find that policyholders and customers are becoming more comfortable with using technology as part of the claims process?
Lee Elliston (12:43):
I believe certain ones are, yes. I think it needs to be bespoke though. I don't think you can throw a one size fits all process at it unless you are an automotive insurer and that's your single focus and product line. But we are around having a common application of technology and data through the process, but then bespoke how that data comes in and how that process works in the right way for the insured or the broker. And that might mean that we have some of our people-based FNOL team that are working with a particular insured or broker because they haven't got the ability or time to be able to get structured data into an app or a form or we could switch it the other way. So we are making sure that we've got a good hybrid response to technology data and people as part of the process.
Patti Harman (13:43):
You mentioned about the importance of managing the data and what's there. What concerns you the most about the adoption of some of these new technologies?
Lee Elliston (13:54):
I think the biggest concern is that people run before they can walk. I think running after the boom of AI and chat GPT and using that within the process I think could create consequences for an insurer if the data model isn't strong in its foundation, good data quality and rules governance has not applied to the implementation of the AI and the data model that had got in place. And I also think that there needs to be some control in the technology around how people access the AI algorithms or rules as well. So I think they're the concerns that you could really run after this quickly. You could really deploy it in a ungoverned way which hasn't been implemented well, and I think that could cause some consequences for people if they chase it too quickly. We're certainly adopting the proof of concept approach, which I think has two benefits. It comes with control. You see that you can apply it and get benefit from the use of data and AI in the claims process in the right way. You use it with the right intention for the right insureds, the right customers, the right brokers from the outset, and you build the confidence with the internal people that are going to be interacting with the intelligence that the technology is providing or the data is providing in the process.
Patti Harman (15:34):
What excites you the most about the adoption of technology in the claim space now then? It sounds like there are a lot of different possibilities that have arisen for the industry.
Lee Elliston (15:48):
I think what excites me the most is that I think people have really started to understand how we can do it and use it. And I think before there was a bit of resistance around do we really have the change in an implementation capability within our organization to do it and do we feel confident to use it? And I think now, I've certainly seen in the last three to five years there's been a lot more operational focus on change capability, embedding the type of technology changes and data changes in organizations doing so with some structure and governance around it, but also making sure that we're holding the hands of our technical experts in the process. We wouldn't have a claims process or a claims brand if our technical experts weren't part of it and hadn't already built that up. And it's about them feeling like they've got a tool that they can use and they're confident to use as it's implemented. That excites me the most right now.
Patti Harman (16:53):
Wow. I've had a number of conversations with a lot of folks in the claims space, and when you look at the depth and breadth of experience that they bring to their jobs, it's really exciting to see how AI can help them even learn more and be more proactive in what they're doing and creating just a really positive experience for the policyholders that they're working with. And it works well from the insurance side as well because it allows you to identify areas to watch or things to question or as you said, make those decisions faster in some cases. Are there certain technologies that you think have more promise or will have a greater impact than others on the claims space?
Lee Elliston (17:46):
I think the technologies that are looking at the use of AI, the use of Gen AI in the claims process and the ones that are looking at basing that on data models, data algorithms and rules in the specialty insurance sector, I think those technologies are going to advance the industry the most. There's a huge opportunity in the specialty insurance sector, which is obviously moving away from your personal lines or your auto sector, for example. There's some technologies that are really trying to get into that space now. Those technologies need specialty insurers and carriers to work with those technologies to apply some of the more complex scenarios, rules that we have, provisions that we have in our contracts around our unstructured data to make it work. So we are working with some InsurTechs at the moment and we've got a hackathon piece of work that's going on in the wider business within Aspen that's looking at screening for different InsurTechs that can bring their technology and data capability to the specialty insurance sector. And we are doing that in a very business led focus, what's the opportunity and scenario that we can apply and how can we work together in partnership to get the best outcome from the technology under a proof of concept. So those types of technology providers that are really looking at the unstructured data, the structured data, the algorithms and applying Gen AI and AI to it are really, really hot for a discussion and conversation across the sector right now.
Patti Harman (19:50):
Wow. And it's interesting because everybody's trying to figure out how do we use AI and Gen AI in just a really proactive way while still mitigating some of the risks that it can incur. We've covered a lot over the last few minutes. Is there anything that I haven't asked you that's important for our listeners to know about claims and technology adoption?
Lee Elliston (20:14):
I think the real big thing for me as well, I think it's part of what excites me, but I think it's something new that's coming up on the rails for all of this, is the use of the technical expertise, which you mentioned, Patti. We've got it in spades within the insurance sector and in the claims sector with highly technical people with years of experience. And it's getting that years of experience into the process, into the technology and into the rules that we want to create. Now, doing that is not to forego the technical specialists in the sector. What we do want to create is that intelligent assistant process and model and be able to give the intelligent outcomes and recommendations to the experts in the process. And as part of doing that, we also advance the talent in the industry that the industry does have some challenge with trying to get talent into the industry from college or from university and bringing that in to the industry where it's been highly manual or analog in its processes has been a challenge.
(21:32):
Now we can start to bring new talent into the industry when we're technology savvy and data savvy and we've got technical experts that have applied our expertise into the process and the technology, that also means that we are able to provide an operating model to people that are technology savvy when they come out of higher education. They're getting to learn the experience of people from both the people and what has been based in the rules in the technology and the process that we're trying to implement. So I think what we are going through is a really key moment for the attraction of talent, the retention of talent, and the diversification of how we use talent and people in the process.
Patti Harman (22:17):
I'm so glad you addressed the talent piece because that really is an important aspect of the insurance industry, and I agree that the use of technology and the implementation and everything is going to have a huge impact on who we're able to attract to the industry going forward. Thank you so much, Lee, for sharing your insights with our audience. Thank you for listening to the Dig in podcast. I produced this episode with audio production by Kelly Malone Yee. Special thanks this week to Lee Elliston of Aspen Insurance for joining us. If you'd like to learn more about the use of technology in the insurance claims industry, join us at the DigIn Conference in Boca Raton, Florida on June 27th and 28th where we will be showcasing a variety of new technologies and discussing its impact on claims, customer service, and data security. Please rate us, review us, and subscribe to our content at dig in dash com slash subscribe. From Digital Insurance, I'm Patty Harman and thank you for listening.