Global FinTech Series Interview with Gary Hagmueller, Chief Executive Officer at CLARA analytics
Companies that already leverage machine learning technologies are being able to react far more quickly and are more effective at delivering quality service to customers and their own employees, especially those at decision-making levels. “That’s because, by proxy, this also results in better financial results to shareholders and others at the end of the value chain,’’ says, Gary Hagmueller, Chief Executive Officer at CLARA analytics while talking about the effect of Covid-19 on fintech startups worldwide in this chat with GlobalFintechSeries. Catch the complete interview:
Can you tell us a little about yourself Gary? What is a typical day at work like as CEO of CLARA analytics? Over the last few months, as the COVID-19 pandemic has unfolded, how have things changed for the team at CLARA analytics, if at all, and how have you seen other FinTech startup peers adjust?
I’ve been working in enterprise technology for more than 25 years, with the vast majority of that selling software and other high-end solutions to large enterprises. The last eight or nine years I’ve spent in the development and delivery of AI applications, first selling FinTech solutions in the banking, group health insurance, health system, and government sectors, and now at CLARA, laser-focused on the insurance industry — specifically P&C carriers and self-insured enterprises.
In terms of COVID-19, I don’t know that prior experience could fully prepare anyone for what we’ve seen over the last several months. My own job function has changed considerably. I used to spend the bulk of my time meeting with investors, potential and existing customers, as well as recruiting team members. I was generally buzzing around the country, trying to evangelize my company and build support for its products.
In the COVID-19 world, I’m still doing that but in a very different way. I find that my days now are packed with back-to-back Zoom meetings. But, interestingly enough, things have not really slowed down. In fact, I think working remotely has played out as a productivity enhancer. In my case, I’m spending less time in planes or waiting rooms or commuting. The same is true for my team at CLARA; by cutting down on all of the outside movement and distractions, they’re getting as much done now — if not more.
I know there are external parties that miss some of the collaborative and brainstorming aspects that are generally best done in person, but technology takes some of the sting out of it. As a whole, the technology industry has been able to adapt pretty well, and my hope is that we will emerge from this pandemic able to facilitate work in dynamic and productive ways.
How have you seen the global FinTech marketplace evolve over the years, and in what ways do you feel the FinTech segment still needs to innovate? More recently, how are you seeing the COVID-19 pandemic impact the global FinTech marketplace?
What I can report based on my experiences is that the FinTech world has evolved considerably when it comes to deploying advanced technologies as well as what it means to be data aware and data driven. I remember in the early days of my last company, big data was THE thing. Everyone touted: “We’ve got big data!” But no one really understood what “big” data really was and, more importantly, what to do with it, which begs the question: Is “big” even useful?
What I’ve seen happen since those early days is that two sets of companies have emerged. One set has struggled to understand what it means to be data aware, and the other has embraced the journey to use data in new ways. The journey is not easy by the way. You have to try, experiment, maybe fail a bit. But once you see what works and what doesn’t, you can take meaningful strides forward.
In terms of how I see patterns emerging during COVID-19, data is really helping companies that want to use it in new ways to navigate through the pandemic by spotting trends and nuances about what is happening within their space and their business. For example, in the workers’ compensation space that CLARA covers, workers’ comp claims clearly show patterns of a “COVID state.” The types of claims may vary, and the volume shifts so that an organization could see fewer claims as a result of one type of injury but a significant rise in another because people are working in different ways. Without that data, it can be very hard to adjust and assign claims to the right people.
How do you feel emerging technologies (AI/etc.) will play a role in the future of the InsurTech landscape? Can you share a few thoughts on some innovative AI-powered applications being built in the market today?
I think there are a variety of places emerging technologies will be used. To give you the panoply of ways InsurTech is coming into the P&C space as an example, there are the pure-play InsurTech carriers — the people who are building their own vertically integrated insurance platforms and addressing specific needs. These companies have a very interesting niche because they can take a specific piece of data and a specific set of knowledge and use it to outperform carrier-based risk models.
The automation space is the second area where technology is coming into play. Here, technology is applied to handle highly transactional, relatively simple sorts of things. Usually it’s around property damage. For example, if you have personal auto insurance coverage, and you get into a fender bender, you now take a picture of the fender, submit it with your claim to the insurance company, and two weeks later a check shows up. No humans touched it because there was no need — a white car of a certain make and model was insured. The pictures that accompanied the claim are of that white car. The dent in the fender is no more than two inches deep, and we know how much that costs so there is no need for a human at that point. A lot of stuff goes on in the background, but new, smart technologies can figure it out.
There is another area of AI — and this where CLARA comes in. This area takes a look at really complex spaces and phenomena and applies machine learning to many different data elements to determine the weak signals that matter. Machines can spot the correlation between a variety of variables in a way that humans simply can’t, and these correlations can be quite important to an output. So, this form of AI becomes an augmentation or an enhancement tool that sits on top of the data systems that people already use. It essentially provides the people who work on complex claims with the tools to be better, faster and smarter at their jobs while complying with all of the industry regulations. I like to say this type of technology gives workers superpowers.
I am sure there are other niche applications out there, but these are the examples that I think will make the biggest impact in the next 5-10 years.
Could you tell us about CLARA analytics’ product suite and how it’s evolved over the years? What are some of the upcoming plans in store for the platform?
If we zero in on what our product suite has done, over the years, CLARA has evolved from a very simple concept: You can look at a very large number of claims and cohort those claims up by type to gain powerful insights that make individual claim resolution much more efficient for all parties.
Taking an example from workers’ compensation. You can look at knee injuries and figure out the characteristics of people typically getting those injuries — are they male or female? Do they live in a certain geography? Do they have certain comorbidities, like diabetes or hypertension? Then you look at all of this close claim activity across thousands of millions for each cohort and figure out “What does good look like?” We refer to the best way to get to “good” as the optimal path.
By virtue of the fact that you have an optimal path, you can figure out what happens when it deviates and even identify the moment it deviates in real time or the event that could predict a departure from optimal. What are the things that indicate a claim is headed off course? That’s how our platform began. What we’ve realized over time is that once you have that optimal path, you can begin to look at a whole host of things along the value chain, from the time a claim was filed to the point at which it closed, to help keep things moving in the best possible way.
One application CLARA offers sits in a stream of data, and it tells a claims adjuster when things pop up that are aberrant, things that need attention. A lot of times, these flags are coming from systems and places that nobody ever thought to look previously, certainly not proactively. It’s pretty powerful because they now can be addressed much faster to keep a claim on track. CLARA also helps identify the best providers to work on specific claims in order to make sure that your outcomes are positive and cost appropriate. We also have an application that helps identify the best attorney to work on a particular claim if a claim should rise to that stage.
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With an optimal path, you also can predict things like future medical costs. You could use this for settlement estimation or reserve planning down the road. There are a number of other potential uses.
At CLARA, we are in the process of expanding into other lines of insurance that have similar trend lines. We’ll begin launching those in the next couple of months. Beyond that, we also see a variety of use cases that could benefit from our optimal path concept, so we’ll begin to build those out with workers’ comp as well as any of the other lines we pursue in the near future.
How do you feel InsurTech providers will have to adapt to market changes in the new normal: In what ways have you seen companies start catering to changing trends the last few months?
For the people who are selling technology into the insurance marketplace, one of the biggest drivers is on-demand, virtual presence technology. I think legacy technologies, the systems behind the firewall, those that require a VPN to log in — they have struggled and will continue to struggle. We’ve seen a big push from companies that want to get into on-demand or cloud-based applications.
Our sales cycles show the instances of people asking about our security compliance, which we are in a great position to talk about, has almost disappeared — people know our reputation for excellence on that front. As such, the conversation almost universally focuses on whether people have to go to great lengths to access the application or whether it’s easy to use from anywhere in the world. That reflects the fact that so many people are working remotely.
The second thing I’ve noticed take hold is that there are a number of vendors that talk about having AI models, but they don’t really have the A or the I. It’s more of a business intelligence function, like dashboarding or generating other reports that point out something from the data. But it’s not predictive; it doesn’t anticipate or have the powerful attributes of a machine learning-driven application. What I’ve been interested to realize here is the fact that the market now sees through this. As companies develop a better understanding of AI capabilities, they can spot and say, “well that’s not really AI — it’s more of an accentuation of what I already have.” As a result, there is a sort of newfound appreciation of vendors that have true AI.
Given the overview of what FinTech looks like today in 2020 and the pace of innovation, how would you describe this market over the next decade?
One of the things that is most exciting about the FinTech and InsurTech marketplaces is the extreme amount of innovation happening. The concept of doing more with data science, doing more with AI and machine learning is becoming more mature. So, what does that mean?
First, the more we have people who understand what these technologies are, the more we have people who understand where it can be best applied. Conversely, we will also stop wasting time trying to innovate on things that are never going to generate enough signal to give a meaningful sort of result. A concentrated effort on determining exactly how we can move the ball forward is going to accelerate.
Secondly, this will breed disruption as much better ways to analyze and use data begin to surface. The method by which companies succeed will be determined by how effective they are at implementing these technologies. Those that resist are going to fall behind, at first slowly, but once behind, without a major investment in catching up, their “data deficit” will accelerate rapidly.
It’s important to note that by “effective,” I mean finding the right solution for the organization. One of the most powerful lessons companies have to learn is what to build in-house vs. what should be purchased from a best-of-breed vender. Companies that want to innovate quickly don’t need to spend the time and resources reinventing a wheel that is already spinning in a lot of other places. You don’t have to build everything from scratch. There is a lot that you can draw on that will help your company become more successful without requiring any type of shift in focus away from a core competency.
If you think about it, there are so many different and excellent third-party solutions that give you about 99% of what you could do on your own in less time, for less money. I would argue in a lot of cases, it’s closer to 110% because companies purchase this technology from vendors who spend their entire day thinking about particular complex data issues. You can waste an incredible amount of cycles and lose competitive advantage by trying to do everything. Moreover, if you try to do everything, you’ll wind up doing nothing really well.
So, I would say as you look forward in the FinTech and InsurTech marketplaces over the next decade, they’re going to be marked by the companies that adopt leading-edge technology to increase accuracy, efficiency, productivity, etc. Companies that are reticent to adopt and innovate will probably get bought by the aforementioned players.
Before we wrap up, would you like to share specific finance management or business tips for marketing and sales or finance teams struggling through this uncertain time due to the COVID-19 pandemic?
I wish there was some silver bullet I could offer. I would say this much — when you’re looking at marketing and sales functions, the new COVID-19 reality means you’ve got to figure out how to get super creative, very interesting, and incredibly relevant pretty quickly.
What we’ve seen within our own practice is if we come up with thought-provoking ways to present our position and help people understand our technology, as well as how we can make a difference, that is appealing. We try to target our sales and marketing efforts to those companies that could use it best. We’re not taking a shotgun approach.
What I’m also finding is that because people are not commuting or spending as much time doing secondary things that might ordinarily occupy them in the office, they’re more interested in learning and understanding about new technologies. They have a genuine interest in it and now have the time to dig a bit deeper. So, if a vendor can tee up content that is appealing to people, it can bridge some of the sales hurdles that have popped up in this period without conferences, when few people are getting on planes and aren’t taking in-person meetings. The ability to have lunch or coffee or other sorts of activities with your potential buyers or potential market participants is gone, so my piece of advice for anybody who’s trying to exist and thrive in a market timing situation like this: Be as interesting and useful as possible.
CLARA analytics improves claims outcomes in commercial insurance with easy-to-use AI-based products. The company’s product suite applies image recognition, natural language processing, and other AI-based techniques to unlock insights from medical notes, bills, and other documents surrounding a claim. CLARA’s predictive insight gives adjusters “AI superpowers” that help them reduce claim cost and optimize outcomes for carrier, customer, and claimant. CLARA’s customers include companies from the top 25 global insurance carriers to large third-party administrators and self-insured organizations. Founded in 2016, CLARA analytics is headquartered in Silicon Valley in California.
Gary Hagmueller, Chief Executive Officer of CLARA analytics, has been a leader in the technology industry for more than 20 years, with a deep focus on building artificial intelligence and machine learning applications for the enterprise market. Over the span of his career, he has raised more than $1.2 billion in debt and equity and helped create over $7 billion in enterprise value through two IPOs and four M&A exits. Gary holds an MBA from the Marshall School of Business at the University of Southern California, where he was named Sheth Fellow at the Center for Communications Management, as well as a bachelor’s degree in Business Administration from Arizona State University.