5 Ways Technology Is Reshaping the Future of Insurance
The insurance industry’s technology evolution is well underway. Insurtech is making a meaningful impact on risk management and insurance, with plenty of potential left to explore.
Insurers are investing heavily in technology startups and working to develop new solutions and platforms internally.
According to a report by KPMG, there were 13 Insurtech deals worth over $100 million made in 2018. And “between 2013 and 2019, patent filings by insurance companies increased by 116 percent,” said Kate Browne, Underwriters Counsel, Swiss Re Corporate Solutions.
Until this point, application of new technology was limited primarily to claims management and customer service. Easy-to-use portals and straight-through processing of simple claims solved pain points for both clients and carriers.
But bigger change is on the horizon. Big data, artificial intelligence and machine learning are driving a shift in the way insurers approach risk and could fundamentally change the business model over the long term.
Though this list is far from exhaustive, here are 5 technology trends to watch as the industry continues to evolve:
1. Capturing and using data will be a top challenge as volume explodes.
We produce 2.5 quintillion bytes of data every day.
“That’s a 1 with 18 zeros after it!” Browne said. Ninety percent of the world’s data has been generated in just the past two years. That pace won’t slow down as more data sources continue to emerge; the Internet of Things is one of the biggest drivers of the data explosion.
According to Ericsson, a provider of information and communication technology services, “the number of IoT devices is expected to increase 21 percent between 2016 and 2022 to around 18 billion.”
Data from these devices will add to already available sources that insurers draw from, including client data, their own claims data, an array of third-party sources like historical weather data, census data and data pulled from communications like emails, calls, texts and social media.
The challenge posed by exponential growth of data is twofold: Much of it is unstructured and thus difficult for legacy IT systems to capture in a usable format; and the sheer volume is overwhelming from an analysis standpoint.
“There’s a substantial volume of information that insurers do not receive digitally. The current process of data submission to carriers can be a bit messy. There’s often a volume of communication with brokers and clients via email, which may capture partial information; there’s images, PDF files, maybe even paper documents,” said Jonathan Hendrickson, VP and head of Insurtech development at Gallagher.
“It’s difficult to create structured data from this unstructured information, and information can be lost which would be valuable for analytics.”
This is where Insurtech startups are helping carriers stand up to the challenge, providing the technology to ingest and sort the tidal wave of data.
“We build our systems through an iterative process. You’ll see us making changes, building code and testing solutions quickly. So insurers are relying on Insurtech firms, saying, ‘Hey, let’s use your technology, which is built for speed, but you can also teach us how to adopt this iterative process of evolving,’ ” said Dan Colomb, CTO for Snapsheet, which provides workflow platforms for insurance carriers.
By leveraging partnerships with Insurtechs, carriers are working towards building more modular, scalable IT infrastructure that’s better able to adapt to future needs.
But even if a system is equipped to ingest the onslaught of data, the second challenge is sorting the wheat from the chaff to generate actionable insights.
“If I have 1,000 pieces of data, how do I get to the five that make sense for my organization?” said Tom Boudreau, head of Construction & Marine for Middle & Large Commercial at The Hartford.
2. Artificial intelligence will be necessary to make data usable.
Artificial intelligence (AI) and machine learning, while still in their early days of adoption within insurance, will become absolutely necessary in order to take advantage of data-driven insights.
AI assistants — think Siri, Google and Alexa — democratize data by making search easy through natural language query. One doesn’t need training as a coder or data scientist to work directly with raw data and generate models — you only need to ask a question. Machine learning platforms are also designed to adapt and get smarter as new data pours in.
On the risk management side, companies can implement AI to dig further into their claim trends and get more granular in determining what interventions will really drive better outcomes. If data is an expansive landscape, AI is the set of binoculars that lets you focus where you need to.
“We’re already operationalizing AI on the claims side to simplify the process,” said Jamie Yoder, president, Snapsheet
“As we get more data, the machine learns more and can run its own processes; the claim essentially knows its own status — and can make decisions as far as determining whether a person needs to take action, who should take action, what follow-ups are needed, etc.”
Making data manageable will also benefit underwriting. According to Swiss Re’s Browne, “The underwriter of the future will be able to unlock the power of data and analytics to aggressively price the best risks, avoid the poor ones and support growth.”
“If I have 1,000 pieces of data, how do I get to the five that make sense for my organization?” — Tom Boudreau, head of Construction & Marine for Middle & Large Commercial, The Hartford
AI and machine learning may solve the volume challenge and make data more accessible, but there remain technical and cultural roadblocks to adoption. Building on top of and around legacy systems will take time, but shifting the change mentality of an organization is an even taller mountain to climb.
“Implementing this technology means work processes will flow much faster. Internal expectations will change, and customer expectations will change,” Colomb said.
“Change management is easier when people realize and are prepared for something that will affect the culture of the company and the way they work. The mentality has to change first.”
Regulators will also have to evolve more quickly. Currently a major challenge to the adoption of AI is the lack of any regulatory framework to ensure that data privacy and ownership are respected.
“The biggest challenge to the adoption of AI and machine learning is that, too often, it’s a black box that makes recommendations or decisions without explainability. Regulators, lawmakers and consumers need transparency,” Browne said.
Alan Colberg, CEO of Assurant, said the U.S. needs an equivalent of Europe’s GDPR: “It will be a lot of work to get ready,” he said, “but it will be a net positive, because without standards on how we can and cannot use data, its full potential remains untapped.”
3. Loss prevention technologies will bring down claim frequency and severity over time.
Technology adoption may face bigger hurdles at insurance companies, but many businesses are already using data and connected sensors to predict and prevent losses.
Moisture detection systems, for example, help construction companies spot a leak on the 30th floor of a building before it causes water damage in all 29 levels below it.
Wearable sensors help workers improve their ergonomics and avoid overuse injuries, a top driver of workers’ comp claims.
“In the auto space, telematics, cameras and other technology are helping to dramatically reduce claims. We can track distance driven on a per driver basis in real time, for example, which can potentially prevent drivers from being on the road too long and having fatigue,” said Rob Cruz, head of Distribution, Field Operations, for Starr Companies.
Weather tracking and alert systems let companies know when bad weather is approaching so they can move people and assets out of harm’s way and take steps to fortify their properties. The examples alone could fill this page.
As these loss-prevention technologies become more widely implemented, they’ll eventually reduce claim frequency and severity.
“These devices should eventually mitigate a volume of claims in a number of categories,” Gallagher’s Hendrickson said. However, “there isn’t going to be an instantaneous drop in claims,” Boudreau added. “There will be a learning curve associated with new technology and incorporating it into a business’s lifecycle. But the end game is to prevent losses from happening.”
4. Technology will shift the insurance business model.
At the same time, though, new technology will create new exposures. When AI-driven platforms are making decisions, it stretches the traditional boundaries of liability, bringing more scrutiny to OEMs and software developers. As these parties assume more liability, they may make their own forays into insurance to help offset some of the risk.
“As more information comes from the risks themselves — the IoT devices, the vehicles, the machines — it does present an opportunity for new offerings from nontraditional players,” Snapsheet’s Yoder said.
Some OEMs of autonomous vehicles, for example, are getting into the insurance game by bundling policies into the vehicle purchase that provide coverage only when the car is in autonomous mode.
“After all, if they’re going to assume more liability, they might as well get a piece of the premium dollars,” Yoder said.
Technology will also drive insurers to become more service-oriented versus product-oriented. Carriers are already taking advantage of Insurtech platforms that focus on improving the customer experience, and they will continue to leverage Insurtech relationships to connect clients with technology that improves their businesses.
“Clients should see us as not just writers of paper. They should think of us as a resource to prevent claims. We do everything we can from an engineering perspective to help in risk mitigation, including connecting clients to the technology,” Boudreau said.
Assurant is doing the same. It’s an example of an insurer that is shifting its core business model to adapt to changing consumer demands that are shaped by technology.
Through heavy investment in and acquisition of Insurtech firms, the carrier has reshaped itself as a conduit between consumers and the loss-prevention-focused technologies described above. If technology produces the drop in claim frequency that it promises, insurers can still earn a profit from subscription-based access to these platforms.
“That’s shifted the mix of our revenue away from traditional underwriting. Over 40 percent of our earnings today are from income businesses, where we are getting paid a fee per subscriber to the apps that we offer,” Colberg said.
The traditional insurers that stay successful will be the ones that adopt technology the fastest and use data to their advantage. Those that struggle to keep pace will inevitably lose some market share. Despite this bifurcation, however, it’s unlikely that any of today’s power players will get kicked to the sidelines.
“Cracking the insurance market will not be easy for nontraditional players,” Browne said. “The insurance industry leases access to capital and it will be very hard to replace piles of money.”
Cruz echoed that sentiment: “Companies often don’t want to take a risk on a startup; they want to partner with an insurer with a strong balance sheet.”
5. Change will happen in 1,000 small ways.
Perhaps the most important thing to keep in mind is that the collective impact of technology on the insurance industry is less about disruption and more about evolution. Insurance’s technology growth and development is happening slowly in 1,000 small ways, rather than in one big tidal wave of digitization.
It started with customer-facing claims platforms that improved experience for the client. Then predictive analytics helped claim managers identify high-risk claims and better direct their time and resources.
Now AI is helping to sort and stratify risks, enabling smarter risk selection and portfolio management. None of these applications changes the core of what insurance does, but rather makes the processes easier and faster.
It’s not possible to predict what new technologies are on the horizon or anticipate the myriad ways they’ll affect the industry, but given the advances already achieved, it may be time to eschew the industry’s reputation as slow-moving and resistant to change.
“Legacy carriers are all innovating right now,” Cruz said. “Anything that helps us write better risks, we’re interested in.”
It is possible the industry will look entirely different 10 years from now and that executives will look around and wonder how they ever operated without endless streams of data, AI and automation.
“Innovation will continue. We may not know what direction it will go in, but my view is that a permanent part of the business model is innovating ourselves and partnering with people who are innovating in those categories where we do business,” Colberg said. &