Tag Archives: cognitive computing

Realistic Expectations for Insurance in 2020

Visualize a meter that ranges from No Change (1) to Total Transformation (10). I expect the actual changes to the 2020 Insurance Industry meter to register somewhere between 1 and 2.

Thinking about insurance industry trends for the next year was always a fun exercise whether I was at the META Group, Financial Insights (IDC) or Ovum (now Informa Tech, I believe). Each trend captured the opinions from our team of technology-focused insurance industry analysts concerning what we thought would occur over three to five-plus years for each specific issue. Once the trends were finalized by the team, our trend report drove a significant part of our research agenda for the following year.

Instead of trends, I decided to publish my realistic expectations for the 2020 insurance industry:

  1. The League Tables (ranking of insurance carriers) for each major insurance line of business will look the same at the end of 2020 as the tables look at the end of 2019.
  2. There will continue not to be any (statistical or otherwise meaningful) correlation between investment levels in startup insurance firms and any measurable impacts on incumbent insurance firms specifically or the insurance industry generally. (Hype does not equal reality regardless of how much PR digital ink is spewed by the startups!)
  3. Insurance firms will continue in their grand tradition of exhibiting “magic bullet” syndrome: believing that the latest technology or technology application can resolve their major business objectives and can be implemented by using minimal company resources.
  4. Insurance firms, particularly in the U.S. and Europe, will continue to struggle to rationalize the large multiplicity of each of their core administration systems (i.e. policy administration, billing, claims management systems).
  5. Independent agencies (and broker firms) will continue to sub-optimize their operations by not acting in the reality that they are joined at the hip with each of the carriers they conduct business with.
  6. Although insurance firms will continue to recognize the absolute criticality of data, the firms’ various data elements will collectively behave more like useless sludge than a clean and useful resource.
  7. The lack of clean, standardized data will continue to hinder (stop?) insurers from successfully deploying customer-facing (and other market-facing, including producer-channel-supporting) initiatives.
  8. Most insurers will continue to give lip service to providing world-class customer service.
  9. The number of independent insurance agencies and insurance broker firms will continue to decrease as M&A continues in the producer channel, but the number of agents/brokers will remain stable.
  10. 5G, immersion technologies (AR and VR) and enterprise streaming will join the never-ending parade of technologies/technology applications in 2020, already chockablock with other “supposed insurance firm immediately must haves” that include leveraging social media, offering increased functionality on mobile devices, virtual agents/chatbots, interactive video for client onboarding and customer service, IoT, big data, cognitive computing, deep learning and machine learning – all of which technology firms will use as door openers as they reach out to insurance CIOs and CTOs.
  11. Cyber risks will continue to cascade through any device connected to the Web used, owned, leased or otherwise in the possession of society (families, individuals, businesses, federal/state/local governments and the military) adding more pressure on insurers to decide whether or how to profitably offer protection or services.
  12. I’ll continue to hope, in vain, that increasingly more insurance firms will realize the importance of using geospatial solutions as critical components of decision-making, whether the geospatial data comes from terrestrial or Earth Observation sources.

See also: Are You Ready to Fail in 2020?  

3 Big Challenges on the Way to Nirvana

We hear almost daily how insurtech is disrupting the once-staid insurance industry. The main ingredients are big data, artificial intelligence, social media, chatbots, the Internet of Things and wearables. The industry is responding to changing markets, technology, legislation and new insurance regulation.

I believe insurtech is more collaborative than disruptive. There are many ways insurance technology can streamline and improve current processes with digital transformation. Cognitive computing, a technology that is designed to mimic human intelligence, will have an immense impact. The 2016 IBM Institute for Business Value survey revealed that 90% of outperforming insurers say they believe cognitive technologies will have a big effect on their revenue models.

The ability of cognitive technologies, including artificial intelligence, to handle structured and unstructured data in meaningful ways will create entirely new business processes and operations. Already, chatbots like Alegeus’s “Emma,” a virtual assistant that can answer questions about FSAs, HSAs and HRAs, and USAA’s “Nina” are at work helping policyholders. These technologies aim to promote not hamper progress, but strategies for assimilating these new “employees” into operations will be essential to their success.
Managing the flood of data is another major challenge. Using all sorts of data in new, creative ways underlies insurtech. Big data is enormous and growing in bulk every day. Wearables, for instance, are providing health insurers with valuable data. Insurers will need to adopt best practices to use data for quoting individual and group policies, setting premiums, reducing fraud and targeting key markets.

See also: Has a New Insurtech Theme Emerged?  

Innovative ways to use data are already transforming the way carriers are doing business. One example is how blocks of group insurance business are rated. Normally, census data for each employee group must be imported by the insurer to rate and quote, but that’s changing. Now, groups of clients can be blocked together based on shared business factors and then rated and quoted by the experience of the group for more accurate and flexible rating.

Cognitive computing can also make big data manageable. Ensuring IT goals link back to business strategy will help keep projects focused. But simply getting started is probably the most important thing.

With cognitive computing, systems require time to build their capacity to handle scenarios and situations. In essence, systems will have to evolve through learning to a level of intelligence that will support more complex business functions.

Establishing effective data exchange standards also remains a big challenge. Data exchange standards should encompass data aggregation, format and translation and frequency of delivery.
Without standards, chaos can develop, and costs can ratchet up. Although there has been traction in the property and casualty industry with ACORD standards, data-exchange standards for group insurance have not become universal.

See also: Insurtech’s Approach to the Gig Economy  

The future is bright for insurers that place value on innovating with digital technologies and define best practices around their use. It’s no longer a matter of when insurance carriers will begin to use cognitive computing, big data and data standards, but how.

Cognitive Computing: Taming Big Data

In the complex, diverse insurance industry, it can be hard to reconcile theory and practice. Adapting to new processes, systems, and strategies is always challenging. However, with the arrival of new opportunities, cultural transformation will go more smoothly.

Insurance companies that are considering how to plug into the insurtech landscape should understand the various models within the innovation ecosystem. Carriers have to weigh their options carefully before choosing between incubators and accelerators, or venture capital and partnerships, when creating their best internal and external teams.

The key elements disrupting the insurance industry include the Internet of Things (IoT), wearables, big data, artificial intelligence and on-demand insurance. Although well-established business models, processes and organizations are being forced to adapt, insurtech can be more collaborative than disruptive.

It is no secret that the insurance industry is responding to changing market dynamics such as new regulations, legislation and technology. With digital transformation, there are numerous ways technology can improve and streamline current insurance processes.

See also: Rise of the Machines in Insurance  

Cognitive Computing

Cognitive computing, a subset of AI, mimics human intelligence. It can be deployed to radically streamline industry processes. According to the 2016 IBM Institute for Business Value survey, 90% of insurance executives believe that cognitive technologies will have an impact on their revenue models.

The ability of cognitive technologies to handle both structured and unstructured data in new ways will foster advanced models of business operations and processes.

Insurance carriers can use this technology for improved customer self-service, call-center assistance, underwriting, claims management and regulatory compliance.

Big Data

Unstructured data is rapidly growing every day. For instance, wearables can provide insurance companies with massive amounts of data that can yield insights about their markets. Social media also produces a flood of data.

To harvest this data intelligently, insurers need to adopt the right analytical solutions to analyze, clean and verify data to customize their offerings according to their clients’ individual needs. Predictive analytics evaluates the trends found in big data to determine risk, set premiums, quote individual and group insurance policies and target key markets more accurately.

Linking the Two

Insurance organizations may have more data than they realize or know what to do with. Existing data is coming in from different core systems, and new data is being captured with IoT devices like wearables and sensors. Cognitive computing is the link to organizing and optimizing this data for use.

See also: Strategies to Master Massively Big Data  

Whether it is used to predict risk and determine premiums, flag fraudulent claims or identify what products a customer is likely to buy, cognitive computing is the way to ensure these goals are achieved. Sorting these trends among reams of data makes them more manageable and ensures that a business’s IT objectives link back to business strategies.

Over the years, systems will evolve through learning processes to a level of intelligence that can adequately support more complex business functions. Schedule a meeting with your executive team to examine risks, opportunities and insurtech synergies that can take your organization beyond the competition.

Possibilities for AI in P&C Insurance

Artificial intelligence (AI) is a term for a very broad array of technologies that mimic human cognition and activities; They can also discover patterns and relationships that go beyond anything humans are capable of. Depending on your view, AI will either be a great boon to human society and business or an existential threat to humanity. Or you may believe that the whole area is hyped and won’t have these dramatic implications. Whatever you believe, it is important to understand how AI applies to the property/casualty industry and where the greatest potential lies for harnessing the technology.

See also: Strategist’s Guide to Artificial Intelligence  

A new research brief by SMA, based on a survey of insurance executives, provides some insights into these areas. AI in P&C Insurance: Potential and Progress covers personal and commercial lines, revealing significant differences between the sectors. AI has potential in P&C to address many business issues across the enterprise for every sector of P&C. Today it appears in use cases here and there. Over time, AI will contribute to solutions everywhere in P&C.

Insurers are experimenting with and implementing AI technologies such as robotic process automation (RPA), chatbots, data and text mining and machine learning. Underwriting rules engines and solutions for claims fraud are being enhanced with newer AI capabilities. Underwriting and claims are two areas that have been using earlier forms of AI (case-based reasoning, rules engines) for some time. These areas still offer great promise for using AI in the future, but now AI is being applied to customer-facing areas as well as other operational areas (e.g., marketing, distribution, policy servicing). For example, insurers are now using AI technologies to improve the customer experience – in fact, personal lines insurers see that as the area to reap the most value from AI overall. Commercial lines insurers tend to expect more value from a better understanding of risk and more efficient operations.

It is important for insurers to actively investigate AI technologies and how they might apply to strategic or operational business needs. What makes AI so important and applicable to many insurance use cases is the range of technologies that are part of the AI family. Depending on how you group and count them, there are at least a dozen different AI technologies. In addition to those already mentioned, there is image recognition and visioning systems, natural language processing (NLP), cognitive computing, artificial neural networks and others.

See also: Seriously? Artificial Intelligence?  

Over time, various AI technologies will become embedded in many different solutions and be used across the enterprise. Now is the time to explore, experiment and look for alignment to business strategy where advantage can be gained.

Go Digital… but Don’t Change Who You Are

My business school professors managed to hammer a single idea into my head about corporate strategy, and that is that there are only two ways to build a sustainable competitive advantage. You can be better, or you can be cheaper. That’s it. A company can approach these strategies from many different directions, but, at the core, these are the options. To create a long-term advantage over the competition, a company has to build a coherent strategy and create an organizational structure dedicated to that strategy. A company that plans to beat the competition with technology must invest in R&D, and a company pursuing a low-price strategy shouldn’t spend millions on lobby artwork. Existing companies are not blank slates.

This is especially true in the insurance industry, which largely consists of established companies with established ways of doing business. Those established methods are sometimes focused on price, sometimes on product, but all have a coherent strategy and organization. Startup culture looks at insurance and sees lumbering dinosaurs. In some cases, this view may be accurate, but it’s important to remember that dinosaurs ruled the earth for 180 million years because they were very good at being dinosaurs. Insurers today are very good at being the kind of insurers they are.

See also: Insurers Must Adapt to Digital Demands  

For these reasons, I believe that some insurers have been looking at digital disruption in the wrong way. In some areas, digital has the potential to transform the insurance market, but, in much of the market, digital is more of an environmental transformation rather than a world-shattering meteor.

This question about the ultimate impact of the digital and technology revolution on the insurance market is the single most important one facing insurers today. Each insurer must look at his or her market, products and organization and decide if digital is a meteor or a slow warming. If this change is a meteor, it may be time to look at acquisition strategies. If this change is environmental, then the considerations are different. No digital strategy is going to fundamentally change an insurer’s nature. Most insurers need to use technology and digital strategies to reinforce their current strengths, not attempt to be something that they are not. An insurer’s already-determined strategy and focus should set the stage for who they are digitally, not the other way around. Using this approach, let’s consider some traditional insurer structures and strategies, and ways that digital can fit into what these companies are already doing.

Focus on Price

The first and most obvious insurance strategy is a focus on price. A low-price strategy is common in personal lines, because most automobile and homeowner’s insurance does not differ widely between companies. Innovation in personal lines tends to be more focused on creative distribution and service delivery, rather than on innovation in the insurance product itself. There is potential for disruption on the product side, most notably in the areas of autonomous cars, telematics and “pay as you go” products. However, a company that is focused on price rather than product innovation has some interesting digital strategies to pursue. Automation and efficiency are traditional rewards of technology investments, and in this situation each insurer must decide which technologies have the highest potential return. Blockchain is a common topic of conversation, but realistically how useful is an unbreakable public ledger of transactions to a company that sells automobile policies? Cognitive computing, on the other hand, could fundamentally transform the cost structure of such a company by automating the routine administrative tasks that occupy so much of insurers’ cost structures. What does an insurance company that fully embraced cognitive computing look like? No one really knows, but my best guess is that it would not much resemble the companies of today.

Focus on Customer Experience

The second common insurance strategy in personal lines is a focus on customer experience. The idea behind this strategy is that if products do not differ between competitors, then service can be a key differentiator. This customer-focused strategy is not a new idea in insurance, but traditional distribution channels create major challenges. Direct writers sell over the web or through the phone, both of which are traditionally low-touch, low-experience channels. The major alternative distribution channel is through independent agents. In this second channel, insurers have outsourced much of the customer experience to these agencies, over whom the companies have limited control. In either case, if an insurer is focused on improving customer experience, then that insurer must have a strategy that both maximizes customer touchpoints and ensures that each of those touchpoints is positive. Technology has a major role to play in this strategy.

For agency writers, building a new distribution channel is not feasible, and the digital strategy has two parts. One, enable agents with technology to provide customers the digital experiences those customers want. Two, build direct contact with those customers through mobile and web. For direct writers, technology provides the only contact channel, so these companies must focus on improving what they are already doing. In either case, technology investments in customer communications are critical, because most insurance customers do not have routine contact with their insurer. Insurers must maximize the value of these outbound communications, because these communications may be the only available touchpoints.

See also: Insurers Must Finalize Digital Strategies  

These two approaches are far from the only viable ones available to insurers. Insurers focused on product or underwriting excellence will take advantage of the revolution in data analytics to create new kinds of insurance products and price those products more precisely. Insurers focused on distribution innovation will use digital technologies to deliver their insurance through new channels to new customers in new markets.

Not Whether, but Where

In all cases, insurers that are not facing complete market disruption should adapt their current structures to this new environment, rather than attempting to become something that they are not. To build an effective digital strategy, all insurers must evaluate their market, their organization and their goals to decide where to invest in digital, and how best to profit from those investments.