The digital revolution in insurance, which began in distribution and then spread to claims, has now reached underwriting in a big way.
There are two consistent themes: 1) Advanced AI and ML technologies, paired with big data and sophisticated risk models, are fundamentally shifting the way underwriting is done. 2) Insurers are leveraging low-cost, cloud platforms that are built for scale and agility with new business models.
In this article, we will explore those two themes and show how digitization streamlines the underwriting process for a more efficient and sophisticated outcome. In our next article, we will explore how carriers are making the shift to next-generation underwriting, changes to user journeys and experience, and measuring ROI in these AI journeys.
The age of insurtech has brought a wave of new digital experiences and automation in insurance. From websites that instantaneously compare auto insurance quotes to mobile apps that allow us to submit claims directly by snapping a picture of a damaged window, we continue to benefit from significant improvements to the insured experience.
These improvements in distribution and claims are part of an industry-wide appetite for increased accuracy and efficiency, including in underwriting. Personal lines carriers have already made good strides, and carriers see a similar opportunity to improve loss and expense ratios in commercial lines.
For small business policies that involve a high volume of submissions and lower premiums, the challenge is to enable an efficient, high-throughput underwriting process that complies with exacting standards for quality. In the mid-market, the stakes are even higher for underwriters. They must be diligent about selecting high-quality risk against a backdrop of declining capacity and a tsunami of submissions from brokers who remarket risks in search of better rates.
While the goal of shorter time-to-quote is laudable, and addresses a critical frustration for insureds and brokers, the implementation often overlooks the crucial role that underwriters play. By failing to listen to underwriters’ needs and play to their strengths as expert assessors of risk, technology providers and insurers alike continue to achieve sub-optimal underwriting outcomes.
Commercial underwriters are at the forefront of some of the most challenging and important work in the industry. They serve a multi-faceted role: developing and fostering relationships with brokers, exhaustively reviewing submissions, validating an insured’s business and property information, analyzing exposures and, eventually, rating, quoting and binding policies. Underwriters must bridge the gap between carriers that set aggressive goals for profitable premium growth and brokers who want a quote “yesterday” — and often pair incomplete submissions with demands for a rapid turnaround.
When underwriters conduct a thorough investigation of the risk – executing online searches, ordering inspections and asking tough questions, they’re invariably perceived as being too slow, inflexible and uncooperative. If they compromise on thoroughness to increase throughput, or if too many submissions are superficially passed through, their book may grow quickly, but the quality and profitability will suffer. All the while, underwriters want to deliver a comprehensive policy that best addresses the insured’s needs and grows the relationship. Reconciling these often-conflicting priorities is difficult but sets the most effective and experienced underwriters apart.
Data analytics, artificial intelligence and machine learning can make a big difference but, for most insurers, have failed to deliver great value within underwriting.
Improving outcomes requires an approach that combines the best of underwriter judgment with machine intelligence.
See also: The Future of Underwriting
Specialized, AI-powered software can now do much of the heavy lifting for underwriters, while eliminating frustrating activities. Underwriters who experiment with, and embrace, new technologies are already setting themselves apart from their peers. They stand to improve their individual performance and also help to chart the future course of underwriting within their organizations.
For insurtechs to truly deliver on their collective promise, they need to empower those who are actually performing the work of insurance. Automation and machine learning need to be force multipliers for underwriting excellence – not poor substitutes for it. Getting this right will lead to a better experience for the insured and superior outcomes for the industry.
Long before the COVID-19 pandemic, insurers were investing in digital transformation, spurred by the rise of startups. Those investments took on new urgency as the pandemic forced businesses across industries to move to digital operations to stay afloat.
Over the long term, no technology will prove as vital to insurers’ agility and success as artificial intelligence, whose far-reaching impact will define the next wave of insurtech innovation.
Legacy players and nascent startups alike will leverage AI and machine learning to enhance customer service, speed claims processing and improve the accuracy of underwriting – enabling insurers to match customers to the right products, operate with greater efficiency and achieve better results.
Though insurance is often cast as slow to embrace technology and innovation, in a certain respect AI is very much within the industry’s wheelhouse. Since the first actuaries began their work in the 17th century, insurance has relied heavily on data – and as AI empowers insurers to do even more with vast swaths of data, the benefits will redound to providers and policyholders alike.
Bringing Customer Service to the Next Level
In today’s digital economy, personalization is all the rage. Customers crave tailored, relevant experiences, offers and promotions that reflect their unique backgrounds, needs and interests – and they increasingly expect businesses to deliver these experiences as a basic standard of service.
While personalization is often discussed in the context of sectors like e-commerce, the insurance industry is no exception to this trend. According to an Accenture survey, 80% of customers expect their insurance providers to customize offers, pricing and recommendations.
Of course, delivering bespoke experiences requires an abundance of customer data – and customers are more than willing to provide it in exchange for personalized service; 77% told Accenture that they’d share their data to receive lower premiums, quicker claims settlement or better coverage recommendations.
Because personalization can only deliver on its promise if it’s holistic and omnichannel, the most successful insurers will be those that don’t view personalized engagements as one-offs – a tailored email here, a promotion there – but that consistently provide personalization at every stage of the customer journey.
What will that look like in practice? AI chatbots will become a lot more “chat” and a lot less “bot,” not only providing 24/7 customer service but also using cutting-edge methods like natural language processing (NLP) to better understand what customers actually need and to conduct more natural, intuitive conversations. Underwriting will become much more precise as machines crunch massive sets of data – reams of usage and behavioral data generated by customers and their IoT devices, as well as relevant geographic, historic and other information – to create customized policies that reflect a policyholder’s true level of risk.
See also: Insurtechs’ Role in Transformation
From Cumbersome to Swift
Harnessing the power of AI, insurers can also streamline claims processing as part of a comprehensive digital strategy. Forward-thinking providers will increasingly integrate automated customer service apps into their offerings. These apps will handle most policyholder interactions through voice and text, directly following self-learning scripts that will be designed to interface with the claims, fraud, medical service and policy systems.
As a McKinsey analysis noted, with automated claims processing, the turnaround time for settlement and claims resolution will start to be measured in minutes rather than days or weeks. Meanwhile, human claims management associates will be free to shift their focus to more complicated claims, where their insights, experience and expertise are truly needed.
These transformative applications of AI will unlock revenue opportunities, improve risk management and help insurers deliver a new level of personalized customer service. But if AI will act as the great enabler, what will enable AI itself?
The answer lies in a robust digital core, which is vital to facilitating efficient business processes, maintaining resilience in an unpredictable world and supporting the rollout of new products and business offerings. Whether insurers manage to achieve that kind of digital agility will determine their ability to survive and thrive in a landscape that’s shifting faster than ever.
When Deb Smallwood and I wrote A Recipe for Commercial Lines Underwriting Transformation, we articulated the need to break free of the traditional paradigm of siloed and incremental evolution being viewed on a quarter-by-quarter and year-by-year basis. We challenged commercial insurers to leap forward with a big vision for the future and then reverse-engineer a holistic strategy to deliver the vision that leads with business, people and culture and is enabled by technology. This is the path to meaningful transformation that will ensure sustainable economic success AND create attractive environments that support good talent and generate further innovation. Our industry survey confirmed that significant change is on the horizon and that we’re not taking all the right steps today to prepare for, let alone capitalize on, that change. Meaningful differences emerged between the way small commercial units and medium-sized to large commercial units are positioned today, and what their paths forward should look like. Download the eBooks here for additional detail.
Perhaps not unexpectedly, given the prioritization and investment in personal lines and small commercial, we find that small commercial executives expect significant change to affect their organizations more quickly than do leaders in the medium-sized to large market space. Small commercial expects more dramatic change over five years, and our data shows that they are further along in envisioning and executing toward a future state, though there are still notable gaps to which attention must be paid.
Underwriting in the middle and large market spaces has historically been more complex and handled in a bespoke and high-touch way. It is here that we see the infinite layering of tactical tools as a stopgap, and prioritization for technology investments are behind their small-market counterparts. It makes sense that they see a 10-year runway for significant change borne out in the data. What gives pause for concern, however, is the lack of clarity on when and where to begin. We see this and other elements as potential roadblocks and warn that a good blueprint is necessary to manage through the construction. This space is ripe for development, and we are focusing on helping insurers create and activate those blueprints.
There are elements to be learned from the small-commercial journey. Data shows that they are leading with an outside-in, customer-centric view that drives meaningful and urgent change internally. While there are gaps to be attended, that action orientation with the end customer in mind is to be favored over the internal focus on improving speed, expense and risk-taking that is slowing change in the middle market and complex space.
A bright future is unfolding for commercial insurance underwriting, and the possibilities are both exciting and long overdue. Given the risks identified in our research and documented in these eBooks, it is critical to think big and enable real transformation – the market, your teams and leaders and your customers all need and expect it. It is a differentiated starting place between small commercial and the middle market, but, in both cases, we believe the best way to get there is to flip the lens and let the business and people lead the effort, updating processes, with all of it enabled by technology. Creating a culture of change readiness and innovation today pays dividends immediately and is the best way to accelerate this journey toward the future.
See also: The Future of Underwriting
In addition to the small commercial eBook and mid-to-large-market eBook, SMA and Boundless Consulting have written a research paper on this topic and designed a framework to guide organizations on this journey. Click on the links for more information.