Tag Archives: commercial lines

AI Investment in Commercial Lines

Artificial intelligence (AI) has been in almost every technology-based headline over the past 24 months. If an incumbent technology provider or a newly emerging insurtech organization wants to grab attention – well, just insert AI in the first few lines of the description. Better yet, insert AI in the product or organization name.

In fact, AI holds exceptional business promise, and there are numerous proven use cases. But AI is a complicated topic.

There are many sub-categories of AI, and one of the first steps in choosing the appropriate technology is to break down AI into consumable bites. SMA finds that there are six primary AI technologies in play within commercial lines organizations: machine learning (ML), computer vision, natural language processing (NLP), user interaction technology, voice technology and robotic process automation (RPA). The big question is – which AI technologies drive the most value for commercial lines?

Not surprisingly, there is a tug-of-war between AI for transformational purposes and AI for tactical purposes. According to commercial lines executives and managers, ML, RPA, computer vision and NLP (in that order) will transform commercial lines the most. Given the general need for transformation across the insurance industry, one could conclude that the previously stated order of technologies would be where the industry is heading in terms of investment. But that is not the case.

The actual investment order is new user interaction tech, machine learning, RPA and NLP, with the remaining technologies following. Does this mean commercial lines insurers have gotten it wrong? The answer to that question is “no,” with possible shadings of “could be.” Much of the framing for this answer lies in the product mix.

For the small business and workers’ comp segments, new user interaction technologies such as chatbots and text messaging have been invaluable in contact centers. This affects underwriting and claims by clearing tasks from work queues, thus freeing up technical expertise for more complex interactions. Billing benefits, as well. Collaboration platforms and real-time videos proved highly valuable during the pandemic’s height and continue to be highly worthwhile.

Machine learning has universal value across product lines. Whether it be ML to improve straight-through processing for less complex lines, such as small business and workers’ comp, or to provide decision support for complicated product lines, ML can contribute in all areas. The great thing about this is that investment in adopting ML skills pays off across the enterprise.

RPA is a technology that not only improves operational efficiency and expense management – important internal goals – but also enhances customer and distributor satisfaction through rapid request fulfillment. Policy service, underwriting and claims all gain value through RPA adoption. Because almost all commercial lines segments have repetitive processes, RPA skills are used universally.

See also: COVID-19 Sparks Revolution in Claims

The “could be” warning comes in terms of computer vision and NLP. Both technologies have significant transformational value in commercial lines, ranging from turning aerial images into information to digitizing paper-based information sources. Prioritizing these technologies sooner rather than later is critical across all product segments.

More than almost any other technology, AI technologies work best in combination — for example, NLP with RPA to increase process penetration. The industry is in its early days when it comes to AI usage, and skill sets are still advancing. The “getting it right” discussion is frequently dependent on product segments. But, over time, value will be universal regardless of product complexity, albeit for different reasons.

For additional information on all six AI technologies and survey results, see SMA’s new research report, AI in P&C Commercial Lines: Insurer Progress, Plans, and Predictions.

Commercial Lines: Kicking Into Gear?

“Transformation” is fast becoming the next overused word in insurance, right behind “digital” and “innovation.” But the fact that so many commercial lines insurers are talking about transformation indicates a reality – there is definitely fundamental change underway. It is true that the basics of the business remain the same, and many of the headline-grabbing initiatives are not yet driving big financial gains. But in those headlines and the behind-the-scenes strategies and pilots underway, there is a palpable sense of real transformation. And it is changing the industry for the better.

SMA’s recent research report, 2020 Strategic Initiatives: P&C Commercial Lines, provides more insight into this transformation. It addresses both what insurers are doing and why they are doing it. The why discusses the factors compelling insurers to embark on transformation, while the what covers insurer strategies and plans and their stage of development. Great progress is being made in the overall digital transformation as well as a dozen other initiatives ranging from improving customer engagement to building world-class data/analytics capabilities.

SMA’s observation from working on strategy with insurers is that there are actually two levels of transformation underway. We divide this bi-level transformation of commercial lines into approaches we call incremental and transformational.

Incremental transformation, Level One, is beyond business as usual. It is not just developing next year’s plans to improve the business on a continuing basis, with gradual, minor improvements to the metrics. It is more about harnessing innovation to generate ideas and approaches, take more risks, establish new roles such as customer experience or chief data officers and begin to change the culture. The objective is to accelerate the optimization of the business and achieve top-line and bottom-line results faster and at a higher level. However, at the incremental level, all activity is done in the context of the current business model and builds off of today’s growth and profitability.

See also: Commercial Lines Embracing Change  

At Level Two, the transformational level, revolutionary change takes place. The objective is nothing less than relevance and future survival. In this mode, insurers are looking at how to create value in new ecosystems, engage in new types of partnerships and achieve the next level of optimization. Considering new business models; rethinking the future roles of underwriters, adjusters and other industry professionals; and designing insurance products to address emerging risks are all part of this level of transformation. By definition, this more “earth-shaking” transformation is a greater challenge because it requires a broader understanding of the rapid changes taking place in the world at large and then translating them into likely scenarios for insurance. Bolder bets are required as part of the risk/reward equation.

What is clear is that many insurers that thought they were undergoing major transformation are now realizing that they are at Level One (incremental transformation). Leaders are trying to kick it into high gear as they launch initiatives to drive Level Two transformation. This is not to imply that the incremental transformation ends. On the contrary, it is still vitally important that insurers push forward with the incremental improvements to the business while working in parallel on more transformative activities. It is a difficult balancing act, but those that successfully move down these paths in parallel will be the winners in the next decade.

Commercial Lines Embracing Change

During the past decade, SMA has conducted a survey to learn how insurers are viewing emerging technology. This year’s technology survey reflects industry changes, because, in the grand scheme of things, some of the featured technologies are no longer emerging. And because the strategic value of the technologies to insurers is maturing, there is a shift in how the research looks at transformational technology.

At the end of the day, technology should be about transforming the business and driving better outcomes. The survey results reveal the degree to which strategies are being generated. Are there pilots in the works? What percentage of the activities are implementations? Where do commercial insurers believe impact is at a business-area level? And, probably everyone’s favorite, are insurers investing?

This year’s recently published survey showed some predictable results – AI is the insurance industry darling, and commercial lines is no exception. But there were also some surprises – IoT activity fell off from 2018. But why? The reasons highlighted in the report are important – it isn’t lack of value. SMA analysis and experience reveals that there are seven technologies that are supporting commercial lines transformational activity to one degree or another:

  1. AI/Machine Learning
  2. Robotic Process Automation (RPA)
  3. New User Interaction (UI)
  4. Internet of Things
  5. Virtual Payments
  6. Wearable Devices
  7. Blockchain

To be very clear, not every insurer and every product line places the same value on each of the transformational technologies. Commercial lines are complex, and insurers are adopting where business outcomes are improved and the technology is within the parameters of strategic plans. The trick for many commercial lines insurers will be to pay close attention to shifts in business outcomes and respond quickly. Unlike past technology cycles, competitive advantage tied to technology adoption is emerging quickly.

See also: Winning in Small Commercial Lines  

For the skeptics about commercial lines adopting transformative technology, I hope you are a bit more positive. For those curious, or even downright happy, I hope learning curves went up, and you are challenged to understand how the seven transformative technologies can drive better outcomes within your own company.

For more information, check out SMA’s research report, Transformational Technologies in P&C Commercial Lines: Insurer Progress, Plans, and Projections.

How to Use AI in Commercial Lines

Last time, we discussed some of the potential benefits of AI in commercial insurance. Now, let’s talk making the business case.

Many insurers are hesitant to invest in AI without proof that these theoretically smart systems will yield real-world returns. A mature AI vendor will have the foresight to develop a team within its organization that’s dedicated to value analytics. This team — made up of data scientists and actuarial experts — will use the company’s own AI solution to run a simulation that can quantify potential savings that the solution could provide.

This capability is crucial, as insurers don’t want to wait three or four years to realize a return. The value analytics team will take an insurer’s historical data and run the simulation. It might conclude that if the insurer had implemented this AI solution two years ago, it could have saved a certain amount — such as 5% to 10% — on claims costs. This percentage of savings might be based on a specific action, such as moving injured workers from low-ranked providers to high-ranked providers — or doing the same for attorneys. Or, the savings might encompass claims that could have avoided certain scenarios, such as surgery or litigation.

See also: 4 AI Payoffs in Commercial Insurance  

Once the AI solution is deployed against live data, the models continue to run every month (or quarter) based on a pre-defined set of performance metrics. Every month (or quarter), the calculations become more accurate, moving from a rough estimate to a tighter range and eventually to a precise calculation of savings achieved.

Traditional models were challenged by the fact that claims are long-term transactions that can take as much as 18 to 24 months to close, but AI — with its machine learning — is able to handle this complexity with a high degree of accuracy.

A Holistic Approach, Not a Silver Bullet

In folklore, it’s the silver bullet that kills the wolf. This bullet has come to signify a simple solution that magically resolves an insurmountable problem. However, an important part of making AI real is understanding that, while it is powerful, it’s no silver bullet.

At the end of the day, AI is most effective when it’s part of a holistic approach. All the pieces of the puzzle must be put in place. At a high level, these pieces include the AI technology itself, operational tweaks and metrics to gauge results. Impact follows when all these components work in harmony. When these conditions are there, we’ll begin to see the needle move on costs and outcomes. For example, insurers can use AI insights to create more efficient workflows; they can facilitate more effective hiring and training practices that enable human resources to apply their expertise at precisely the right moment in the claims process. It’s iterative, with machine learning driving change in a continuous cycle.

See also: New Era of Commercial Insurance 

Although immediate savings can be achieved, an enduring competitive advantage can only be realized when the application of AI is seen as a journey. It requires continuing effort and investment. Strategic players understand it can take a few years of making improvements to truly redefine their cost structure, customer experience and position in the market. The organizations that start early on the AI path with an iterative mindset will be well-equipped. We’re looking forward to an exciting decade ahead.

As first published in Digital Insurance.