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Data Prefill: Now You See It, Now You Don’t

At children’s birthday parties, a guest magician may utter the well-worn phrase, “now you see it, now you don’t” – and a bouquet of flowers disappears. That trick, a heartwarming memory for many, also relates to the vast quantity of questions on an application for commercial lines insurance.

It’s daunting for a business owner to come face to face with the numerous blanks on an insurance application. Much of the required information is not immediately at hand – or not understood at all. For distributors, the familiarity with the content is certainly there – at least for seasoned personnel. But the time it takes to fill empty boxes keeps them away from more useful interactions with customers. On the other side of the transaction, company underwriters need information to price the risk. For a very long time, the industry has been at a stalemate.

A conundrum? Not any longer.

See also: 3 Keys to Selecting the Right Platform  

Enter data prefill and new data sources. Data prefill certainly isn’t new – personal lines insurers have employed it for some time. But, the impetus to use the capabilities in commercial lines has not been present until now. Business owners require a simpler application process, and distributors need to be freed from clerical tasks. Undertaking a data prefill initiative may be a simple decision for some organizations – but for others it may be a challenge. In either instance, SMA has a five-step analysis process (Why, Who, How, Where and What) that can guide any organization looking at data prefill. It’s important to approach the initiative with a measured assessment to ensure a successful outcome, even if everyone is already on board with data prefill.

Given the press that organizations such as Cake Insure and Pie Insurance have received, it might be easy to assume that data prefill is all about small business and workers’ compensation. Clearly, there are significant opportunities in the small business arena to condense insurance applications down to three, four or five pieces of data. Evan Greenberg, CEO of Chubb, has declared that the current 30 questions in small business applications will be condensed to around seven within 18 months. However, it would be a mistake to assume that data prefill is just about one commercial lines segment.

In fact, insurers covering all but the most complex jumbo commercial lines have an amazing opportunity to use the same data integration techniques for data prefill to automatically integrate data into more complex lines of business – to improve data accuracy and thus drive profitability. Regardless of the line of business or size of the business insured, augmenting application data with new, emerging data can support underwriters in their decision making. And, perhaps, it can eliminate the need to obtain information from business owners and distributors and promote a much greater degree of accuracy. SMA’s recently released report, Transformation in Commercial Lines: The Five Steps for Data Prefill, provides a view of this.

See also: The Problems With Blockchain, Big Data 

This brings us back to “now you see it, now you don’t” and the disappearing questions on commercial lines applications. Having spent a long time as an underwriter, I recognize that it is unsettling to think about losing the data elements that one has relied on to make decisions. However, with data prefill, that data can be found and used in many ways: eliminating questions on applications for small businesses and prefilling internal systems for more accurate decisions on complex lines. No one will be deprived of data – the source will just be different – an insurance magician’s answer to several challenges!

Quest for the Holy Grail in Workers’ Comp

Quotes from only five data points, or even fewer? Name your number, and you can find an insurer looking to transform the sales experience to match. We have seen a great deal of this momentum in personal lines with increasing attention in small commercial lines. And the line of business delivering today is workers’ comp!

Insurers writing workers’ comp – including insurtech startups – are innovating in many areas, including quoting, servicing, claims and the overall customer experience. There is high potential for emerging technologies, including AI and wearable devices, to enable these advancements and tremendous benefits to be gained from external data sources as well as the untapped data already within an insurer’s systems. Together, these circumstances have created fertile ground for innovation.

Both established and greenfield insurers are taking advantage of the possibilities that advanced technologies bring to the workers’ comp sector. This year’s SMA Innovation in Action Awards gave us two excellent examples of how both types of companies are approaching these new opportunities – in the digital MGAs Cake Insure, which was incubated by Pinnacol Assurance, and Pie Insurance, a greenfield venture. They demonstrate two different approaches to the same goal: leveraging new technologies and external data to create a seamless digital experience for customers.

See also: 3-Step Approach to Big Data Analytics  

Pinnacol Assurance is a workers’ comp insurer that is more than 100 years old. They wanted to reinvent the purchasing experience for workers’ comp by emphasizing digital and leveraging new technologies such as AI to condense the entire process into five minutes or less. Cake Insure, a digital MGA, is the result.

Cake’s online platform gives consumers a responsive, mobile-friendly experience that requires only a few data points to generate a quote. An AI-driven policy classification engine uses natural language processing and machine learning to enable straight-through processing for more than 90% of new policies. This technology enables Cake customers to simply enter a description of their business in their own words to get a quote, with no industry jargon or class codes required. Certificates of insurance can be generated and shared immediately via the Cake client portal or email. Cake’s success demonstrates how an established insurance company can embrace greenfield thinking and reinvent the customer experience.

Greenfield insurers and MGAs are also pursuing the transformational possibilities of workers’ comp. Pie Insurance is a full-stack digital MGA for Sirius Group that set out to change the workers’ comp market for small businesses, an underserved and often overcharged business segment.

Pie uses predictive analytics and high-quality data sets in real time to give small business owners a seamless, mobile-friendly way to find the coverage they need at the right price. According to Pie’s proprietary data, 80% of small businesses overpay for workers’ comp, often by as much as 30%. The company provides consumers with a detailed breakdown of the coverage and pricing that is appropriate to their risk and offers an online quoting experience that is as easy as getting an online quote for personal lines insurance. The savvy use of third-party data combined with predictive analytics gives Pie the ability to quote a new workers’ comp policy in minutes.

See also: Predictive Analytics: Now You See It….  

These companies are simply two examples of how the workers’ comp market is transforming. Both established and greenfield insurers and MGAs are making headway in this area. We can expect further changes to come as insurers find even more ways to bring new technologies to bear on the customer experience. So, stay tuned.

For more information on the SMA Innovation in Action Awards program and this year’s winners, please click here.

Emerging Technology in Personal Lines

Personal lines insurers are investigating emerging technologies and developing strategies and plans related to individual new technologies. Technology is advancing so rapidly that it is even difficult to define what should be considered an emerging technology. For the past several years, SMA has been tracking 13 technologies that many consider to be emerging. These include technologies such as autonomous vehicles, AI, wearables and the Internet of Things. In our recent research, five of these technologies have emerged as “power players” for personal lines insurers, based on the level of insurer activity and the potential for transformation. The specific plans by insurers for these and other technologies are detailed in the SMA report, Emerging Tech in Personal Lines: Broad Implications, Significant Activity.

See also: 2018’s Top Projects in Personal Lines  

Some big themes for emerging tech in personal lines stand out:

  • Artificial Intelligence dominates. AI is often a misunderstood and misused term. However, when specific technologies that are part of the AI family are evaluated, much activity is underway – by insurers, insurtech startups and mature tech vendors. Chatbots, robotic process automation (RPA), machine learning, natural language processing (NLP) and others are the subjects of many strategies, pilots and implementations.
  • The Autonomous Vehicle frenzy is cooling.There is still an acute awareness of the potential of autonomous vehicles to dramatically alter the private passenger auto insurance market. But there is also the realization that, despite the hype, the transition is likely to be a long one, and the big implications for insurers are probably 10 or more years out.
  • The IoT is going mainstream. Discussions continue about the transformational potential of the IoT for all lines of business. But rather than just talking about the possibilities, there is now a great deal of partnering, piloting and live implementation underway. We are still in the early stages of incorporating the IoT into strategies and insurance products and services, but their use is becoming more widespread every day.
  • UI Options are dramatically expanding. The many new ways to interact with prospects, policyholders, agents, claimants and others should now be considered in omni-channel plans. Messaging platforms, voice, chatbots and more are becoming preferred ways to communicate for certain customer segments.

See also: Insurtech and Personal Lines  

Certainly, other trends and much emerging tech activity are happening outside these main themes. Wearables, new payment technologies, drones, blockchain and other technologies are being incorporated into strategies, pilots and investment plans. The next few years promise to be quite exciting as advancing technologies spark more innovation in the industry.

Emerging Tech in Commercial Lines

Historically, technology adoption within commercial lines organizations has been met with a wall of push-back, largely related to commercial lines being wrapped in a cloak of “art versus science” thinking. Because of risk and product complexity, commercial lines organizations believed that only highly trained and seasoned humans could be involved with processes and decisions.

Additionally, due to the predominance of large, enterprise-scale projects, characterized by protracted ROI exercises and IT resource allocation exercises, past technology choices generally brought out the “yeah buts.” (What are the “yeah buts”? This is the response to enterprise technology options, to which commercial lines product and underwriting heads promptly responded – “yeah, but that doesn’t work for us.”) In many cases, this was not an inappropriate response because of risk and product complexity. But, at long last, there is a change afoot, and it lies within emerging technologies.

SMA has been conducting research and surveys around emerging technology since 2010 to gain insight and understanding of insurance industry adoption and spending. In the past, results have predominantly trended across the P&C industry. However, the recent 2018 results reveal clear differences between commercial lines and personal lines organizations.  Even more exciting, commercial lines product segment and transactional differences are emerging. As the phrase goes: Vive la difference!

See also: Expanding Into Commercial Lines  

So, what does all this mean? SMA’s recent report, Emerging Tech in Commercial Lines: Ramping Up Adoption, covers eight emerging technologies that hold great promise for commercial lines organizations: artificial intelligence (AI), new user interaction technologies, the Internet of Things (IoT), drones, blockchain, autonomous vehicles, new payment technologies and wearables. How are commercial lines organizations viewing these technologies? Here are some examples that show emerging technologies are being viewed uniquely by varying commercial lines segments and processes:

  • AI – This technology garners the highest percentage of implementations of all the emerging technologies by almost twice the other categories, with 26% indicating so. Investment in AI exceeds the next closest emerging technology by more than 24 percentage points. The difference: It can drive straight-through processing for small business and simple specialty lines and support complex decisions for middle market, large national/global accounts and complex specialty lines. “Art versus science” well managed!
  • New User Interaction Technologies – This is another technology that is affecting small commercial lines as this product segment goes digital. But 67% of all responders see the value in customer experience, regardless of product segment, and 50% are focused on policy servicing.
  • Blockchain – While personal lines organizations are generally assessing the applicability of blockchain, commercial lines have found use cases and pilots. 42% of survey respondents believe that policy servicing and billing are the significant value areas. Global and complex lines of business are the first target areas.

See also: Top 5 Themes in Commercial Lines  

Other emerging technology examples and spending projections can be found in SMA’s commercial lines report. But the big takeaway for me is that, happily, the “yeah buts” are disappearing across commercial lines of business and products as executives search for and find emerging technologies that can improve business outcomes. Because of the way emerging technologies are being delivered by incumbent and insurtech providers, discreet value choices can be made without having to launch enterprise-level projects. Vive la difference!!!

And the Winner Is…Artificial Intelligence!

Artificial intelligence stands out as one of the hottest technologies in the insurance industry in 2018. We are seeing more insurers identifying use cases, partnering and investing in AI. 85% of insurers are investing time, money and effort into exploring the AI family of technologies. The focus is not so much on the technology itself as on the business challenges AI is addressing.

  • For companies looking to improve internal efficiency, AI can assist through machine learning.
  • For those working to create a dynamic and collaborative customer experience, AI can assist with natural language processing and chatbots.
  • For those seeking an edge in data and analytics, AI can help to gain insights from images with the help of machine learning.

Through our annual SMA Innovation in Action Awards program, we hear many success stories from insurers throughout the industry that are innovating for advantage. AI was a key technology among this year’s submissions. The near-ubiquity of AI was even more obvious among this year’s insurer and solution provider winners, many of whom are leveraging some type of AI to solve widely variant business problems. They have provided some excellent use cases of how insurers are applying AI and how it is helping them to succeed.

Two AI technologies, machine learning and natural language processing, fuel Hi Marley’s intelligent conversational platform, which West Bend Mutual Insurance piloted in claims with outstanding results. The Marley chatbot lets West Bend’s customers text back and forth to receive updates, ask and answer questions and submit photos. Its use of SMS messaging means that communication can be asynchronous and done on a customer’s own schedule, eliminating endless rounds of phone tag.

  • Natural language processing allows Marley to communicate with customers in plain English – both to understand their needs and to respond in a way that they will understand.
  • Machine learning enables Marley to continue to improve. The platform analyzes every conversation and uses it to shape how Marley responds to specific requests, refining its insurance-specific expertise for future interactions.

See also: Strategist’s Guide to Artificial Intelligence  

Natural language processing is also a critical tool for Cake Insure, a digital workers’ comp MGA with a focus on making the quoting experience easier for direct customers. One of the hurdles that would-be customers had to overcome in obtaining workers’ comp coverage was answering a multitude of questions regarding very specific information that a layperson is unlikely to know about or understand.

  • NAIC codes, for example, are required for every workers’ comp policy, but the average small business owner would be baffled if asked about them. Cake circumvents this by asking usera to type in descriptions of their companies in their own words. Natural language processing parses this plain-language description and searches for its approximate match in the NAIC data sets. This back-end process occurs without the user’s awareness and without exposing potentially confusing content.
  • As with Hi Marley’s chatbot functionality, natural language processing is paired with machine learning to improve its ability to respond to specific phrases and content.

Machine learning can also be deployed in conjunction with other AI technologies. Image analysis and computer vision are combined with machine learning in Cape Analytics’ solution, which can automatically identify properties seen in geospatial imagery and extract property attributes relevant to insurers. The result is a continually updated database of property attributes like roof condition and geometry, building footprint and nearby hazards.

  • Computer vision helps turn the unstructured data in photos and videos from drones, satellite and aerial imagery into structured data.
  • Machine learning allows the solution to train itself on how to do that more effectively, as well as higher-level analysis like developing a risk condition score for roofs.

We are only scratching the surface of how AI can be applied across the value chain. The incredible variety of AI’s potential applications in insurance is difficult to overstate. QBE knows that well: It won a company-wide SMA Innovation in Action Award for wide-ranging activities in emerging technologies and partnerships with insurtech startups, but AI in general, and machine learning specifically, are their top priorities. In addition to partnering with dozens of insurtechs, QBE has also pushed itself to deploy each insurtech’s technology somewhere within its business – meaning QBE has dozens of different creative AI applications in play at once. For example, in partnership with HyperScience, QBE is improving data capture from paper documents through machine learning and computer vision.

These winners’ stories demonstrate the myriad ways that insurers are applying AI to improve business operations. Notably, its deployment helps them to significantly improve the customer experience – or, in the case of data capture, the internal employee experience. The need for this kind of seamless customer experience in the digital world cannot be overemphasized. AI, which struck many as a science-fictional concept, has proven its real-world worth by enabling insurers to transform their customer journeys and experience.

With full-scale implementations popping up across the insurance industry, as well as the pilots and limited rollouts that we have seen in previous years, it is easy to lose sight of the fact that we are seeing only the very tip of the iceberg in terms of how AI can transform the business of insurance. Applications of more advanced and advancing AI technologies, as well as the combination of AI with emerging technologies such as drones, new user interaction technologies, autonomous vehicles and IoT, are unexplored territory that is bright with promise.

See also: 3 Steps to Demystify Artificial Intelligence  

This much is clear: AI will change the face of the insurance industry. In fact, it’s already happening.

For more information on the SMA Innovation in Action Awards program and this year’s winners, please click here.

To download a free copy of SMA’s white paper AI in P&C Insurance: Pragmatic Approaches for Today, Promise for Tomorrow, please click here.