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Strategies to Master Massively Big Data

Telemetry, IoT, wearables, AI, chatbots and drones are tools that help group insurers better engage with customers and improve business processes. There is one thing that all of these technologies have in common: data.

Personal data to be precise.

Exactly how insurers will mine, manage and utilize the massive amounts of data now available from various internal and external sources may mean the difference between data mastery and data mystery for many carriers. In this blog, I’ll outline a few things carriers can start to think about as they incorporate big data into their corporate strategies.

See also: 10 Trends on Big Data, Advanced Analytics  

Start Out Simple and Stay Focused

Data science is composed of several disciplines and skill sets. AJ Goldstein does an excellent job of deconstructing this complex craft into what he calls, “The Data Science Process,” consisting of six parts:

  1. Frame the problem
  2. Collect raw data
  3. Process the data
  4. Explore the data
  5. Perform in-depth analysis
  6. Communicate the results

Goldstein says that, although data science is a large, complex paradigm, only about 20% of the skills needed will contribute to 80% of the outcomes. So focusing on that core 20% necessary to achieve the results you’re looking for will help simplify the process and keep IT departments focused on the goals you originally set out to achieve with the data.

Applications for big data in insurance currently center on providing solutions to tasks like premium setting, fraud reduction and target marketing. How this looks will differ across projects, but regardless of the application, data experts will collect data from various sources, analyze it and use it to draw conclusions about how the company can improve the bottom line and provide value to customers.

They don’t call it big data for nothing! The amount is gigantic. New variables and trends that arise can easily lead you astray from the original question you set out to answer.

Stay on track and focus on what you set out to determine. You can always circle around to address new insights later.

Mitigating Risks

Consumers know that sharing data comes with risks. Even the most hardened networks can be vulnerable to cyber-attacks and data breaches, leaving consumers understandably wary of how and with whom they share their personal information. Carriers that take the proper cybersecurity measures will be better prepared to ward off or respond to breaches. Obtaining accreditations such as ISO 27001 may help identify any gaps before hackers do.

Privacy is another important factor when obtaining and storing customer data. Consumers want to know what their data is being used for and be assured that it will not be used for anything else. If carriers can guarantee this, studies show that customers are willing to provide personal data in exchange for lower fees and improved services.

See also: Next Step: Merging Big Data and AI  

When the proper measures to manage big data are in place, an opportunity to form digital trust with customers is possible. If this is established, the possibilities are endless for the kind of engagement and relationships that can be developed and sustained. With information everywhere, people still value relationships they can trust. That’s never going to change.

Insurers have gone from seeing the value in data, to being able to analyze it, to capitalizing on automation that is now having an immediate impact on operations. The ability to automate business front-ends and back offices has in many cases catapulted insurers into the digital age, and most are landing on their feet.

This is due in no small part to strong leadership from CIOs, a shared understanding of what customers now expect and a mandate to provide it. Insurers that master big data will likely leap to the front of the pack. Those that see it as a mystery may quickly find themselves out of the race.

5 Challenges When Innovating With AI

Artificial intelligence is booming in insurance. In a recent report, Celent identified AI use cases around the globe and across the insurance value chain.

Uses include customer engagement (USAA’s Nina); product optimization (Celina Insurance Group, Protektr); marketing and sales (Usecover, Insurify, Optimal Global Health, Ping An); underwriting (ZestFinance, SynerScope, Intellect SEEC, Swiss Re); claims (Tractable, Ant Financial, Gaffey Healthcare); fraud detection (Ant Financial, USAA); risk management (Achemea); and business operations (Ping An Direct, Union Life).

Insurers are wise to innovate with AI technologies. Early adopters will face challenges but will also have the potential to reap greater rewards by improving efficiency and customer engagement.

Here are five challenges for carriers to consider when innovating with AI:

1. What technology to use when. When embarking on a digital transformation, there may be a number of solutions available for a given problem, one of which could be AI. But while AI may resolve an issue, it is important to examine all the potential solutions and decide which one is the best fit. Perhaps robotic process automation (RPA), application programming interface (API) or another automated solution is best suited. Can an existing technology be leveraged?

Deciding what solution to apply when requires you to look at the whole organization and all the issues upfront. This allows CIOs and CEOs to examine each problem, decide on the right technology solution and make sure it complements the overall strategy and budget.

See also: Strategist’s Guide to Artificial Intelligence  

2. Big data + AI = big strategy. A second challenge surrounds the management of big data obtained from customers, core systems, brokers/agents and insurance exchanges. Add to that the varied types of data that AI is managing, analyzing, communicating and learning from and things get a little more complicated. Here’s a list of the different data types AI may be working with:

  • Structured, semi-structured and unstructured data
  • Text
  • Voice
  • Video
  • Images
  • Sensors (IoT)
  • Augmented/virtual reality

Data is also classified as real-time, historical or third-party — yet another dimension to consider. Make sure your strategy takes the necessary data variables into account: where data will come from, where it will flow to and how it will be handled at various points in the customer journey.

3. Managing customers across swim lanes. This leads us to challenge No. 3: the ability of AI to engage with customer data at key touchpoints during the customer lifecycle. For example, if Lucy has group benefits as well as voluntary products, car and house insurance, how will her data be managed and optimized across swim lanes?

What will be the touch points for AI? When will other insurtech solutions be present? When is human intervention required? And how will this data be used to inform future risk decisions?

4. Harnessing AI’s multidisciplinary capabilities. AI encompasses machine learning, deep learning, natural-language processing, robotics and cognitive computing, to name a few. You can read my blog post here to learn more. Deciding what technical abilities will be required to solve your problem could present challenges as the lines between disciplines blur.

Additionally, the next wave of AI could come from entirely different industries, such as aerospace, environmental science or health — but  it will still have applications for insurance. The best way to overcome this is to examine your AI needs across solutions and select vendors with the right capabilities to execute them.

See also: The Insurer of the Future – Part 3  

5. Communicating past tech speak. As AI becomes mainstream, the challenge of helping non-technical business professionals understand these complex applications is real. AI systems can require a level of technical expertise beyond the everyday scope of business.

True digital transformation, regardless of technical complexity, affects everyone in the organization. Ensuring the vision is shared will matter as day to-day operations, tasks and activities change. Find someone who can break down the benefits of these new solutions into bite-sized pieces that everyone understands to ensure buy-in and ultimate success.

The question of whether AI will indeed disrupt the industry or simply enable its full digitization is still not known. It will not be the solution to every problem. However, if implemented strategically, it may hold the capacity to create an entirely new way of insuring — and delighting — customers in a rapidly changing landscape.

Robots and AI—It’s Just the Beginning

You’ve probably had regular help from a virtual assistant by phone or online, assisting you with basic tasks such as directing your call or giving you your bank balance. Helpful, right? The companies that employ the virtual assistants think so, too, and are applying these AI/robotic processes to more and more of their everyday business operations.

Often called out for being slow to change, the insurance industry is beginning to catch up quickly. It’s making sweeping changes across organizations and core systems because of the disruptive emergence of insurtech. Carriers like Celina and USAA are using AI in their daily operations and reaping the benefits.

As a result, insurers are now either delivering — or are in the process of delivering — a great digital experience to consumers. Once complete, this transformation will entail an entirely new way of doing business and servicing customers.

See also: Strategist’s Guide to Artificial Intelligence

There are four main technologies to keep in mind:

Robots

Robotics is the branch of technology that deals with the design, construction, operation and application of robots, virtual or physical. They are autonomous or semi-autonomous machines or systems that can act independently.

Artificial Intelligence

AI is the theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making and translation. AI is software that learns and improves. Some robots can use AI to improve their capability by learning, but that is optional.

Cognitive Computing

Cognitive computing technologies are a subset of AI. Cognitive computing “refers to computing that is focused on reasoning and understanding at a higher level, often in a manner that is analogous to human cognition,” writes Lynne Parker, director of the division of information and intelligent systems for the National Science Foundation, in Computerworld. “This is a subset of AI that deals with cognitive behaviors we associate with ‘thinking’ as opposed to perception and motor control.”

Robotic Process Automation

Insurtech consultant Celent defines robotic process automation (RPA) as a set of technologies that can automate processes that currently require human involvement. Robots replicate human behavior to conduct the tasks as a human would; robots also optimize the tasks. RPA can yield benefits when applied to the right roles. It does well supporting repetitive tasks in various environments where there is little change, often back-office support roles and tasks.

Accenture found that cost savings after deploying RPA can reach as high as 80% and time saved on tasks as high as 90%. Automating repetitive processes means tasks are completed quickly with fewer errors, opening up new opportunities for employees to focus on more customer-centric tasks.

But RPA is not the answer to everything. It does not think, reason or predict. It completes simple, repetitive tasks quickly, but it does not learn or self-improve. Developing an enterprise-wide strategy to determine where RPA provides the most value and to anticipate the organizational change that may result is the prudent approach.

The Future Is Here

IBM’s Watson and Amazon’s Alexa are early examples. Insurers already have joined the revolution. Celina Insurance Group uses an analytics-based agency prospecting tool to appoint agents in high-potential underserved areas. USAA’s “Nina” is an AI virtual assistant that chats with customers on the USAA website. It’s designed to respond to 120 questions, from reporting stolen payment cards to changing a PIN.

See also: The Big Lesson From Amazon-Whole Foods  

There will inevitably be lessons to learn from successes and failures of this first wave of robotics and AI. However, early adopters of these technologies also risk success. Investing in innovation is what will allow insurers to stay ahead of disruption and, in some cases, create it.

As robots evolve, their capabilities and applications will no doubt be vast. Just as we could not have predicted how the internet — and now the Internet of Things — would evolve, robotics and artificial intelligence will likely follow the same course.

How to Respond to Industry Disruption

Automating risk management, rating, quoting and renewals, integrating massive disparate legacy systems and redefining age-old business models – essentially all at once – is no small task. But it offers progressive insurers great opportunities to vault past the competition

It seems as if almost overnight emerging insurance technologies have flooded the market under the rubric of insurtech. Of course, this isn’t quite how it happened. This shift in insurance, evolving over decades, has seen a rush largely due to the emergence of agile disruptors recognizing the need for digitization and automation in a market previously slow to change.

The innovations have been fast and furious, but according to a recent Celent report, Life Insurance CIO: Pressures and Priorities 2017, insurance IT departments are still relatively slow to make innovation a top priority. Only 14% of carriers pursuing innovation say it will have a significant impact on IT spending. Some 71% report a moderate impact, and 14% say none at all.

Nevertheless, as disruptive forces increase, traditional insurers will have to respond.

See also: Preparing for Future Disruption…

Take peer-to-peer insurance. This new model first appeared in 2010 when a German company, Friendsurance, decided to offer products that promote transparency. Its pricing reflects the number of claims recently submitted.

Consider Lemonade—the insurance outfit, not the drink. It offers personal insurance to New Yorkers, boasting, “Maya, our charming artificial intelligence bot will craft the perfect insurance for you. It couldn’t be easier, or faster.” There’s even a charitable angle: “We take a flat fee, pay claims super-fast and give back what’s left to causes you care about.”

New approaches such as Friendsurance and Lemonade are creating customer-centric models that could garner attention from consumers and may have the potential to change insurance dramatically.

Driverless cars, enabled by Internet of Things technology such as sensors, will affect the way cars are insured. Google and Uber are already investing in fleets of self-driving vehicles, but, with few on the road as of yet, the extent to which safety has improved hasn’t been determined.

But it is clear is that claims previously resulting from human error would likely no longer apply. The car manufacturer, not the driver, would be liable. If this happens, drivers can expect lower insurance premiums but may see higher prices or built-in fees for autonomous cars to reflect the transfer of risk from the driver to the manufacturer.

Digital business tools such as electronic signatures are already having a big impact. The technology allows for the creation and transfer of secure signatures over networks via computers, tablets and smartphones. It can support completing an application or policy in one transaction.

E-signatures improve workflow for the broker as well as the customer’s experience. Now brokers and customers can finalize transactions from anywhere at their convenience and eliminate the manual tasks of printing, scanning, faxing and emailing documents. Electronic signatures also help reduce risk by providing audit trails and ensuring all documents that necessitate a signature are in order. Benefits include lower costs, fewer errors and more streamlined processes. Regulations in some states limit the use of e-signatures, however.

See also: Which to Choose: Innovation, Disruption?  

These innovations are creating entirely new ways for insurance providers to reach and retain customers, and it’s only just beginning. Today, continuous innovation is just as important for insurers as the traditional disciplines of underwriting, financial management, marketing and customer service.

How to Support the Agent of the Future

New-business sales and servicing has received increased attention from insurance carriers in recent years, and with good reason. Insurers that provide tools and resources that make it easier for agents and brokers to quote and retain clients have a better chance of return business. A key way to accomplish this is through agent/broker portals and exchange sites.

Typically web-based, these portals support the sales and service function of a carrier and aim to improve efficiency in business processing through functionality that authorizes an agent to easily quote new business as well as service in-force business.

With a new wave of millennials entering the workforce, and an entire generation of baby-boomer knowledge holders preparing to leave, distribution management is poised for redefinition along with the rest of the industry. The digitization of core systems is largely underway and is now reaching out toward distribution channels, offering insurance companies a chance to help define what E&Y refers to as the “agent of the future.”

See also: How Insurtechs Will Affect Agents in 2017

The extent to which these agents and brokers will be successful will depend on the ability of both agent/brokers and insurers to adapt and collaborate. Distribution channels need to be willing to adopt new practices, tools, and processes to adjust to changing regulation and customer-centricity. Insurers that inquire into the needs of agents and brokers, and implement portal solutions that address them, can improve business processes and possibly establish a competitive edge.

Craig Weber, CEO with Celent, an independent technology research firm, agrees: “Insurance carriers are starting to more aggressively seek out solutions to help them improve operational efficiencies and deliver better service to customers. In terms of distribution, independent agents have made it abundantly clear that underwriting speed and process support often drive their decisions to place business with one carrier versus another.”

Digital distribution models offer a new array of opportunity for usage, gathering and transfer of data. When insurers provide agents with access to data in the form of quotes, illustrations and marketing material, turn-around times can be significantly enhanced. Simultaneously, data gathered by agents during the sales process (CRM) can populate new business, policy and administration systems, reducing the need to re-key information. Valuable analytics on channel activity and performance can further inform insurers by highlighting top producers and indicate where more support might be needed in the Agent/Broker Portal or exchange site.

IT departments have historically had to develop these portals themselves, but insurtech vendors are responding to the increasing demand. Here is a list some of the standard agent portal features and functionality to watch for in your solution.

Because core insurance technology platforms are as varied as insurance companies themselves, portal and exchange site requirements and solutions are bound to reflect this complexity. Nevertheless, it is in the carrier’s best interest to make the agent/broker experience as easy, even enjoyable, as possible by including the features and functionality that producers, and insurers, need.

See also: Find Your Voice as an Insurance Agent

Insurance companies, as well as offering agent/broker portal functionality, are often tying their own sales and underwriting system into both portals and exchange sites. Exchange sites are numerous and are usually insurance-product-specific (P&C, individual health and life, or employee benefits and ancillary benefits). The more an insurance company can streamline with straight-through processing across various digital media the better and more cost-effective the solution.

FutureTech and Business Transformation

Additional and emerging technologies such as AI, robotics, sensors and predictive data and adoption of digital self-service portals will all play a role in defining the “agent of the future” and the systems that support them. The digitization of distribution is one of many aspects that insurers must consider as business systems transform. If undertaken strategically, with insight from stakeholders, digitization could yield a substantial return for insurers, agents and the customers they serve.