Insurtech: optimizing claims, disrupting insurance future
A friend in the property casualty insurance industry asked me how innovators could optimize claims handling and how that related to Insurtech pitches in his inbox.
I offered two answers: First, consider process analysis of critical, value-add processes to identify areas where efficiency can be increased, service levels maintained, and technology applied to improve accuracy and opportunity. I've had the chance to work in this area with industry partners, and work often with some really terrific practitioners.
Second, consider the Insurtech companies in the wider context of future challenges and upcoming trends. There might be new companies advertising their wares, but the forces generating tailwinds aren’t new in this case.
Coverage of technology innovation is usually driven from the supply side, resulting in Utopian promises and predictions based on what technology can produce, transform, or deliver. This creates emotional whiplash along a Hype Curve ranging from "technology trigger" through "trough of disillusionment" that can make it easy to assume threats have come and gone.
But this causes us to overlook potentially disruptive innovations until it's late in the game.
Take my friend's inbox:
The Insurtech companies pitching my friend aren't at the "peak of inflated expectations" but rather on the "slope of enlightenment," with the potential to grow, merge, and challenge insurance incumbents in the near future.
Insurance and related activities factor highly on Growth Innovation Strategy's TRENDWISE disruption prediction engine, itself an AI-powered application. TRENDWISE uses GIS's proprietary disruption prediction algorithm to track risks across 168 factors among adjacent industries, what is driving them, and where and how they will impact industry value chains.
The TRENDWISE Disruption Index from Growth Innovation Strategy ranks disruptive threats to Insurance carriers as near-term, relatively certain, and fundamental to the incumbent industry. Regulatory moats are barriers to further erosion, but hundreds of millions of dollars in lobbying funds are being deployed in the battle to change the landscape.
GIS's analysis ranks Insurance among the most-disrupted industries that we're tracking in the services sector, driven by the impact of competitive dynamics, internal modernization, and a stew of external factors that include the current interest rate environment, climate change and social reactions to it, demographic shifts and the increasing use of connected systems in daily life, and several other factors.
Interestingly, of all the threats facing Insurance -- currently -- it is least affected by the use of substitute products and services.
Disruptive drivers highlight areas of vulnerability in the Insurance value chain. But the Growth Innovation Strategy TRENDWISE Disruption Index also highlights important present-day considerations for carriers to position themselves for the next-generation competitive environment.
However, this could change quickly, and lobbying to alter the regulatory system is a critical battlefield that GIS is monitoring for early indicators of rapid change for the Insurance industry and Insurtech.
Rather than look only at supply-side drivers of change, GIS also considers demand drivers of change. A compelling set of demand side questions is posed by Ajay Agrawal in discussing his new book "Power and Prediction" looks at the demand side of disruptive technologies. That approach asks us to look for disruptions in pockets of well-structured demand, i.e. incumbents using technology to enhance existing practices.
Change may occur more slowly in industries with substantial CAPEX investments, professional networks, and regulatory or lobbying moats that can be reasons -- and means -- for delaying disruption. For example, the insurance industry spends about $160 million a year on lobbying, employing over 800 lobbyists on behalf of more than 170 clients. In response, the Insurtech industry established the Washington-based American Insurtech Council in 2021 to shape ethical and inclusive regulatory policy.
I used to work with a property casualty insurance client, so I periodically check in on the industry as a disruption benchmark. AI, big data, cheap cloud computing, and embedded insurance products are four forces driving huge changes in the industry.
Of those, AI is the newest, and probably the biggest potential disruptor given that it can take advantage of big data and cloud to customize and target profitable services. Embedded insurance products are one resulting point solution you're starting to see now.
AI has the potential to revolutionize casualty operations by streamlining operations, reducing costs, improving overall efficiency, and setting up the potential for new categories of insurance products and business models.
Large insurance companies with well-structured and mature demand are positioned to be the early adopters of AI in their claims-handling processes. By integrating various AI strategies in their value chain, these companies can lower costs and improve efficiency in areas such as product value creation, customer identification, marketing, sales, and service resolution, a costly, time-consuming, and low-value-add.
As well, AI is regularly deployed to enhance data processing and fraud detection. Moreover, AI can be applied to risk assessment and underwriting. The COVID-19 pandemic really accelerated the need for digital channels and innovative approaches, and Insurtech firms rose to the occasion.
Insurtech firms can be categorized into three groups: Creative carriers, data and analytics suppliers, and customer experience enablers. New entrants include Lemonade, Shift Technology, FOXO Technologies, TRUE, Coherent Spark, and EXL, all offering innovative solutions across the insurance value chain. Interestingly, FOXO, TRUE, Coherent Spark and EXL (I believe) are all companies built on the Salesforce platform, which means they’re easy to start up and deploy — so expect the supply side to continue showing up with a vengeance.
That's a short-term impact, applied to the Insurance industry as it is now.
But expect a fuller transition to AI-driven processes will be capable of profoundly impacting the industry as a whole between the medium- and long-term. (McKinsey, which came to the same conclusion via a different process, agrees.)
The disruption will create opportunities for new entrants offering AI-powered claims processing and fraud detection tools to narrow the performance gap between low-performing and high-performing companies in the industry. This same potential for AI-driven improvement can be seen in other industries, such as healthcare, finance, and manufacturing. As mentioned, the adoption of AI in these sectors may be slowed by factors like the regulatory environment, lobbying ecosystems, and capital expenditures invested in core business models.
In insurance, complementary services, such as AI-powered fraud detection, claims management software, and data analytics tools, will become increasingly valuable in the short- and medium-term. Conversely, traditional substitutes, such as manual claims processing and human-operated customer service centers, will face diminishing value.
That affects jobs.
As AI continues to infiltrate casualty insurance claims handling, companies will need to adapt by investing in upskilling and change management to ensure their workforce is prepared for the technological shift.
The upside for companies will be worth it.
Sensors + AI + machine learning algorithms can help insurers detect potential risks, alert policyholders and insurers and even shut down systems to prevent loss in the home or other property. I worked with a company that did just that with industrial clients.
If semiconductors lowered the cost of mathematics, the internet lowered the cost of communication, reach, and distribution, then AI is lowering the cost of prediction. Insurance is an arbitrage business based on uncertainty. And uncertainty is eroding.
At some point, the costs of operating will be so low that the value chain for insurance will get a clean sheet treatment from some future large-scale low-end disruptor. With sufficient scale, why not deploy AI-driven approaches to risk assessment, underwriting and pricing optimization, personalized marketing, loss prevention, and continuous innovation in claims handling processes?
But that threat is also an opportunity.
Why not ride the wave, if there’s time to catch it?
Read more about how Growth Innovation Strategy helped a property casualty insurer rapidly prototype new emerging technology solutions.
Are you looking to improve your innovation KPIs and strategy? Reach out for a consultation to strategy@growthinnovationstrategy.com.
