Tag Archives: strategy meets action

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!

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.

3 Techs to Personalize Claims Processing

Claims is a people business – virtually every claims executive I have ever met believes this. If you have ever been in a vehicle accident, experienced damage to your home or business, or been injured in a work-related incident, one of the first things that comes to mind is: I need to talk to someone who can assure me that I have insurance coverage and that there will be resources, both financial and technical, to make me whole again. This reaction is a human one and is not likely to go away. Many claims organizations have tried to maintain staffing levels to ensure a human connection is available to all. However, this is expensive, and claims organizations are already experiencing a shortage of individuals to fill critical claims roles.

Claims executives are at a crossroads, and many questions arise. How do we maintain 1:1 people interactions and simultaneously manage skills gaps and expenses? Then there are digital expectations from all parties to the claim – insureds, claimants, distributors, service providers – how are those expectations met? Given all these weighty challenges, many claims decision-makers relate to the phrase: “There’s a light at the end of the tunnel, and it’s a train coming the other way.” But, for many claims organizations, the reality is that the digital train that is coming can provide answers to the people challenges they face.

See also: How Work Culture Affects Claims Process  

SMA’s recent research report, Claims Transformation: New Paths Forward for Reporting,  Verification and Communications, explores emerging technologies and trends in claims operations. Relative to the people business theme, there are several areas of innovation where concerns, expectations and answers merge.

  • Self-reporting via photo and video. Apps that facilitate the insured or claimant in providing visual representation of damage will speed the claim along versus waiting for an adjustor or inspector to do the same thing. Faster settlement clearly meets consumer expectations. Additionally, precious claims resources are preserved for more complex claims.
  • Self-reported photos and videos along with AI analysis. The resulting outcomes from AI analysis can facilitate the next-generation of straight through processing (STP), ultimately going well past the current glass and towing claims STP, as things such as machine learning evolve over time. Again, shorter time to settlement with little or no claims adjustor involvement – a win-win.
  • Telemedicine and digital health platforms blend consumer-accessed, personalized information with a collaborative environment for adjustors, service providers, medical professionals and other concerned parties. These technologies blend useful, self-service information with human access at the moment of need.

These are just a few examples of the technologies that claims organizations have at their disposal to transform processes and operations. The previously mentioned SMA research report covers many other areas.

Make no mistake, balancing when to insert adjustors into processes and when technology can facilitate desired outcomes is not easy to accomplish. One of the key success factors is to look at claims processes from the outside in. This is not intuitive for claims organizations that have spent entire careers managing the challenges and intricacies of the adjustment process with an internal lens to meet corporate compliance goals and tangential department needs within a regulatory framework that can be daunting.  However, looking at claims processes from the consumer perspective – outside in – can suggest ways of execution that fulfill the need for the customer to be compensated for their loss in the fastest way possible or to find the clearest path to wellness. Happily, these outcomes also preserve human claims resources for when an individual really needs it.

See also: The Best Workers’ Comp Claims Teams  

The technology vs. human paradigm will continue to change, probably forever. However, claims is one of the areas within insurance where expert adjustor skills can truly make a meaningful difference for individual outcomes. But the definitions will continue to change, and the challenge for claims executives will be to continually assess processes through a different lens. Optimistically, the light in the tunnel will be a source of inspiration.

What’s in a Name? Art of Insurtech Naming

What is it with insurtech brand names? Among the insurtechs that SMA is tracking (well over 1,000) are a wide range of names ranging from the clever to the practical to the bizarre. Having personal experience with naming, I can understand the challenges of finding something memorable, not already used, and lacking any negative connotations. There is always the option of functional naming; for example, Insuresoft clearly creates software solutions for the insurance industry.

When I was recently in a whimsical mood, I decided to do an exercise to categorize insurtech brand names by a number of topics or areas, including food, animals and human names. This is a sampling of what I found:

Food

One could make a whole meal out of insurtech names. The main course could be Oyster, focused on workers’ comp. Fruit sides might be Pear Insurance or Pineapple. There are plenty of drink options with H2O, Lemonade and Soda Insurance. And dessert – everyone’s favorite – is not lacking in options, with Cake or Pie, or maybe even Marshmallow.

See also: 3 Insurtech Firms Take a Star Turn  

Animals

Comic George Carlin used to wonder who took all the blue food. (Blueberries are not blue; they are purple!) But there are plenty of blue animals in insurtech, including Blue Owl, Blue Leopard and Blue Zebra. Then we have animals with descriptors like Bold Penguin, Pandadoc and PrecisionHawk. The insurtech menagerie also includes Hippo, Dolphin, Canary, Rhino and even a hybrid in CatDogFish. There is even a regular Zebra to go along with Blue Zebra.

Human Names

Why not anthropomorphize insurtechs? We do it with everything else. There is Bob – and if he gets lost there is FindBob. Abe, Albert, Frankie, Gabi and many others are named after people. Then there is Hi Marley, which does a nice job of creating something unique that also relates to the company’s solution – leveraging texting and messaging platforms to communicate with policyholders and claimants.

There is no question that many of these names are becoming known in the insurance industry, but there are pros and cons for using these types of names. One caution for those selecting names – think about search engine optimization (SEO) and how individuals will discover your site. With enough money, brand visibility can be built for any name. But in many cases funding is limited in the beginning stages, and the focus is more on building the solution and getting successful partnerships and projects underway. I have personally had great difficulty finding any information on some of these insurtechs – even just navigating to their websites – due to names that are so common that SEO is difficult.

See also: Insurtech’s Act 2: About to Start  

Another piece of advice (although I don’t claim to be a branding expert): Two-word names (separate or conjoined) offer more options for uniqueness than one-word names – Cake Insure, Young Alfred and TechCanary would be examples. Of course, brands are built, and companies succeed, based on the strength or their offerings, their innovation, their customer relationships/experience and many other factors. But I, for one, am glad that insurtechs are choosing names that are fun and interesting. So, what’s in a name? I guess it’s what you make of it.