Tag Archives: Watson

Existential Threat to Agents

It was 1975. While completing an application for malpractice insurance, a dentist told me his address was 12345 Main St. I commented on how simple it was. He shot back, “So simple even insurance agents can understand it.”

In 1994, while speaking about managed care to a conference for librarians, I mentioned the rising cost of healthcare. There were about 250 in attendance. The audience was engaged. Suddenly, someone in the back of the room screamed, “Read the Golden Stethoscope and see what those bastards are doing to us!” I was shocked by this apparent “nut” in the crowd. Looking around, I realized the majority of attendees were nodding in agreement with the “nut.”

A few months later, working as the executive director of the Louisiana Managed Healthcare Association, I was at my office. Don, one of my board members, called to say I needed to come to his office right away because two federal agents wanted to talk to us.

I did what any of you would have done. I threw up in my garbage can, then went to Don’s office. We met with these two agents for about four hours. They were investigating physicians in two parishes who were allegedly colluding with a hospital to drive patients to their institutions. What they were doing was illegal.

Later that week, I spoke to the medical society in one of these parishes. One hundred doctors were in attendance. The doctors had just concluded a meeting that celebrated their leadership in funding a physician-owned HMO. This was a priority because no one was going to tell them what they could or couldn’t do in the practice of medicine.

See also: How to Earn Consumers’ Trust  

Once introduced as the executive director of the Louisiana Managed Healthcare Association, I began my presentation on Managed Care 101. Ninety-eight of the doctors were polite hosts and a respectful audience. The two other doctors operated in full attack mode.

Toward the end of the program, one screamed at me from the back of the room, “I don’t think insurance companies and HMOs should make money in healthcare.” I explained that many people felt doctors were making plenty of money in healthcare and that premiums were too high.

I will never forget one doctor’s response. He said, “We’re just getting by.”

Ninety-eight of his colleagues bowed their heads in embarrassment. Later, I was told he was grossing $2 million a year. (I wanted to yell, “The Feds are going to get you,” but I didn’t.)

A November 2012 Gallup survey ranked 23 professions based on the public’s perception of their ethics. Agents rank seventh FROM THE BOTTOM – between legislators and attorneys.

Not everyone loves us as much as we love ourselves. The dentist, the librarians, the physicians and the participants in the ethics survey all have their opinions. I’m assuming most see themselves in a positive light but are often suspect of others. This brings me to the point of the story.

On TV in 1954, Robert Young played Jim Anderson, an insurance agent, in Father Knows Best. Those were simpler times, and insurance was not the expense that it is today. We now see ourselves as the Main Street agent (adviser), a trusted choice, “like a good neighbor” and other “feel good” personifications.

But more and more consumers I talk with are “mad as hell and won’t take it any more” with the cost of insurance. Premium costs, rate increases, larger deductibles and co-pays are breaking our clients. The worst is yet to come. When the National Flood Insurance Program must finally demand actuarially sound rates, and the adverse selection of the ACA finally takes its toll, voters will rebel, and government will gladly welcome the chance to further expand its failed involvement in our industry.

See also: Why More Don’t Go Direct-to-Consumer  

We can explain all we want. Consumers don’t care. All they want is relief. In my opinion, if we don’t aggressively work to solve the cost problems because we believe nothing can be done, we will lose our industry and agency system as we know it.

Peter Drucker stated this clearly in 1993, when he said, “Customers do not see it as their job to ensure manufacturers a profit.”

Peter Drucker was a very wise man. Video stores, book stores, travel agents, solo practitioner doctors, full service gas stations, etc. were dumb, fat and happy, and now most are gone. The consumers no longer saw their value.

How might consumers spell relief? A – M – A – Z – O – N, or W – A – T – S – O – N or A – I or some other innovation that we can’t even imagine.

America’s agents need to wake up before it’s too late!

Chatbots and the Future of Interaction

When it comes to the list of disruptive technologies, are we giving chatbots enough credit?

Chatbots are only beginning to show their potential, garnering initial headlines primarily due to Lemonade and its chatbot called Maya. That is interesting, considering that chatbots and AI will likely have a greater overall impact than many of the up-and-coming technologies we have grown to accept, such as autonomous vehicles. How is it possible that chatbots are silently sitting on the sidelines?

It’s simple. They aren’t sitting silently. Chatbot development and use is in full swing. The headlines are picking up. Research organizations are putting forward more predictions about chatbots than ever. Chatbots are easier to implement than many technologies and, operationally, they will provide real value. Text-based or voice-carried artificial intelligence and service-focused functions can readily swap with current human-based adviser/service functions. As complex as they are on the back end, chatbots don’t require major hardware investment, such as sensors, and they don’t require an inordinate amount of coding. So, for all of their disruptive potential to the way we do business, they may be far less disruptive to operations and IT, though operations and IT (and customers) stand to benefit from chatbots.

See also: Chatbots and Agents: The Dynamic Duo  

In an era where impatience is growing and speed is rewarded, chatbots can dramatically improve service levels and meet or exceed expectations. They can also make the economics work for providing service and executing transactions for the growing ranks of high-volume, on-demand, low-premium risk products coming to the market. They are the future of nearly all personal business transactions. For insurers, chatbots can be their own distinct channel as well as augmenting existing channels, supporting a multi-channel world.

Chatbots are growing in use and importance

In Majesco’s Future Trends 2017 Report, we discussed the impact and potential of chatbot growth. Chatbots aren’t growing merely because they have service potential — they are growing because automated non-human service is gaining acceptance among the Gen X, Millennial (Gen Y) and Gen Z cohorts.

Chatbots’ appeal and growth will likely make them one of the technologies to break out of age-based stereotypes. WeChat, China’s most popular chat app, is a great example. With nearly 1 billion users (889 million people), its impact is felt across generations and is even spurring older generations to adopt mobile technology. WeChat is popular — its users interact for an average of 90 minutes per day. Because it uses voice commands, it is also learning from conversations, illustrating the potential of chatbots to gain something from each interaction.

Business Insider said that 80% of businesses will be using chatbots by 2020, with 42% believing that chatbots will improve the customer experience. In addition, 29% of customer service positions in the U.S. could be automated with chatbots or other technology.

Chatbots offer immense potential for customers to interact with an insurer, through direct interactions within messaging or other social media apps.

Other technologies and their impact on chatbots

The “automated home” race between Amazon’s Alexa, Google’s Home, Apple’s HomePod/Siri and many other technology providers will enhance chatbot adoption and use. The more people become comfortable with interactions that are non-human, the easier it will be for people to feel comfortable in a chatbot purchase and service environment. Insurance is already adopting chatbot use and ramping up chatbot availability.

In the past year, for example, insurtech saw a rapid rise in the use of chatbots within startups ranging from Elafris, which enables customers to download auto ID cards and pay bills, to Denim, which markets to consumers and links them with insurers or agents for renter or homeowners insurance.

Robo-advisers represent a chatbot with real AI integration and rules management that can go beyond outside customer service and well into day-to-day executive assistance.

In July 2015, Zurich shared how it was using robo-advisers in two ways: First to accelerate and improve policy processing and issuance that improved quality and accuracy for international casualty programs. Second, Zurich used them in the U.K. to conduct routine diary reviews for open claims that traditionally required attention by human operators.

In the quest for improved customer service, quality, accuracy, speed and efficiencies, robots and robotics have significant opportunity for insurers. From automating processes to interacting with customers, the potential seems limitless, as well as creating a starting point for cognitive applications.

A natural link: AI and Chatbots

Cognitive systems help visualize, use and operationalize structured and unstructured data, pose hypotheses based on data patterns and probability and understand, reason, learn and interact with humans naturally. As a result, the systems help organizations create knowledge from data to expand nearly everyone’s expertise, providing continuous learning and adapting to the environment to out-think the competition and the market.

AI and cognitive computing technologies like IBM’s Watson have been touted as the link between data and human-like analysis. Because insurance requires so much human interaction and analysis regarding everything from underwriting through claims, cognitive computing may be insurance’s next solution to better analyze and price risks using new data sources, while adding an engaging and personalized advisory interface to their services.

A savvy insurance technologist can easily begin to draw the lines between that kind of intelligence management and its potential when linked to chatbot advisory and directive services. Just as many of today’s advisors and agents have experience in underwriting, tomorrow’s chatbot may carry with it the ability to market, gather data, quote, underwrite, issue policies and settle claims without human intervention. Putting one face on an insurance company probably couldn’t get more complete than that.

See also: Hate Buying? Chatbots Can Help  

For now, we can see the seeds of this complete chatbot value chain in its beginnings. At the recent SVIA InsurTech Bootcamp in August that we were involved in, we saw and discussed the array of opportunities to leverage chatbots, AI and cognitive … highlighting the opportunities unfolding.

In June of this year, PolicyPal, a Singaporean startup, announced the launch of its AI-enabled mobile app, which includes a chatbot supported by IBM Watson Conversation technology. The app not only helps prospects through the insurance selection process, it explains complex insurance concepts to consumers to enhance their overall insurance knowledge. The AI, having educated itself, is in effect giving back through chatbot interactions. That is the future of insurance interaction, a market where both parties have something to learn and gain from the insurance relationship.

When Gartner asserts that, “Chatbots will power 85% of all customer service interactions by the year 2020,” that may be enough to drive some business leaders to look into all that chatbots have to offer.

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.

Much Higher Bar for Customer Service

“It’s all about the customer.” How often have we heard that statement?  More times than we can count, Yet it is more relevant than ever as we exit the “pre-digital” age and enter an environment where survival will be measured by rapid adaptability (see our recent blog post An Ocean Apart: Pre-Digital and Post-Digital Insurance Models).

In our prior posts, we focused on two areas of the insurance value chain that likely are not top of mind when thinking about digital transformation — billing and claims.  In this post, we’ll cover policy and customer serving, which is certainly a higher-profile area for digital enhancement. Policy and customer servicing should be near the top of insurers’ “to do” lists when it comes to embracing the digital shift and transforming into a digitally optimized, customer-focused enterprise.

While many insurers express the desire to become more digitally enabled, most are struggling to catch up, let alone position themselves as leaders. Technology is evolving, and customer demands are growing faster than most companies can deal with. Add to this the challenge that insurers are often saddled with legacy systems, siloed data and product- (not customer-) focused processes that make anticipating and adapting to these changes all the more difficult.

A McKinsey survey from earlier this year reported that most insurers in the U.S. and Europe focus their digital attention on sales and marketing, in particular on the earliest stages of the lifecycle — research and quoting. While these two areas are important, the survey noted that insurers were lagging in their ability to service customers digitally after they were on-boarded.

See also: Key to Digitizing Customer Experience  

Improving Customer Service Is a Great Way to Differentiate

Majesco’s primary research studies on consumers and small-medium businesses showed that, compared with other industries, insurers are pretty bad at service. Life insurers are ninth out of 10 in terms of “ease” of servicing (of the industries shown in comparison, only streaming TV/video/music gets poorer marks for service), while P&C insurers are in fifth place (behind online banks, local retailers, national retailers and online retailers). All small-medium businesses (SMBs) ranked life insurers and employee benefits providers no higher than eighth out of 10 different industries they use as suppliers. P&C insurers also ranked low (fourth out of 10) among the smallest SMBs (those with fewer than 10 employees), but fare much better among larger companies, rising as high as third and second.

Furthermore, our research noted that poor marks have a demonstrable effect on success. If a respondent reported that any one of the aspects surveyed (research, purchase, service) was “not easy” then their Net Promoter Score dropped significantly. And NPS is recognized as a key predictor of a company’s growth and profitability.

According to Celent research, even agents, who are understandably worried about digitally enabled self-service reducing their importance in the sales process, recognize the need for digitization of insurance service processes. The research notes that agents are asking insurers to invest in technology enhancements to, among other things, improve online policy changes.

But It Isn’t Easy (of Course)

At first glance, policy and customer service appears to be an important and straightforward – if not particularly sexy – way to apply digital capabilities to improve outcomes. But looks can be deceiving.

Some of the basic tenets of good service – a 360-degree view of the customer, for example – can be difficult and expensive to implement. Regulatory barriers may prevent streamlining how policy changes are implemented online, varying significantly from state to state and country to country. Legacy policy management systems may not be able to connect to digital front ends in a direct way.

But all of these challenges provide an opportunity to focus on a customer journey-map-based approach to digital transformation! By starting with a vision for digitally enabled customer service (what you want the service experience to be, what business goals you are trying achieve, what key performance indicators you will measure for success) and then creating customer personas and journey maps, you will be able to create a transformation road map. That road map will include people, process and technology changes that you will make over time to reach that vision, allowing for incremental change (instead of taking a riskier, big-bang approach to changes).

Don’t Ignore the Shiny Objects

Just because we recommend an incremental approach doesn’t mean it can’t be fun! There is a lot of cool and interesting insurtech investment in this area, which can (and often should) be leveraged to roll out needed functionality without having to build it yourself.

For example, having e-signature (and as per this blog post on digital billing) and multiple e-payment capabilities can make a policy change paperless and seamless for the customer, something that has been shown to improve service “ease of use” scores. Chat capabilities (human or chatbot) to walk customers through basic to tricky processes is a boon to customer service, with leaders like Lemonade and Geico leveraging them at almost every step of the customer lifecycle. Co-browsing options can be used to help customers navigate particularly tricky process steps. Customer analytics can be used to identify customers at risk of leaving, help them manage their risks and even identify cross- and up-sell opportunities.

Even artificial intelligence (AI) shows promise in customer service, and far beyond just chatbots. IBM’s Watson is assisting customer service efforts in dozens of industries, and all indications are that it will be especially useful in insurance, where matching customers to products and services can help generate revenue and improve customer satisfaction. An excellent non-insurance example is the work Watson is doing with H&R Block. Watson is used to feed appropriate question prompts to tax professionals during client consultations. Bill Cobb, H&R Block president and CEO, said, “Watson is learning more and more as it does more tax returns.” According to a recent IBM blog, “Watson has learned 600 million data points relevant to the industry as well as the U.S. tax code.”

Imagine Watson in insurance, rolled out to give agents prompts based on both individual knowledge and “learned” experience. Watson will help insurers translate regulatory requirements and improve relationship management. Cognitive customer service will give real depth to the possibilities. The Future Today Institute has stated in its 2017 Tech Trends Report that artificial intelligence will soon be integrated into nearly every facet of work life. In a detailed look at industries covered in the report, AI is the #1 trend in every industry.

But Keep an Eye Out for Pitfalls

One potential pitfall is to think this service mentality applies to just personal lines, which, as I’ve highlighted in my other blog posts, is far from the truth. Commercial carriers have a lot to gain from digitally enabled servicing, particularly in the SMB market, where margins can be thin on a per-policy basis. Commercial carriers may be very amenable to service outreach that includes risk-mitigation advice as well.

See also: ‘It’s the Customer Experience, Stupid’  

Insurtech is not just for personal lines, either: A recent SMA study highlighted more than 400 insurtechs targeting the commercial space, and the carriers themselves are interested in leveraging them for, among other things, customer servicing.

Other pitfalls include trying to do too much at once or taking a scattershot approach to service improvements. These dangers reinforce the critical importance of leveraging customer journey mapping to create a disciplined approach to capability deployment.

How to Start

As we have consistently advocated, start with a vision of what you want to achieve. Check this against other investment priorities and pain points for your customers and other stakeholders (for example, if the biggest area of complaint is with the claims process, you may want to consider starting there). Create personas and journey maps to guide your decision-making.

The Great AI Race in Insurance Innovation

The rise of artificial intelligence is the great story of our time. Leaving the laboratory after decades in the making, artificial intelligence, or AI, is infusing itself into many aspects our daily lives – from homes and phones to cars and offices. Machines are now able to perform tasks that previously required human intelligence across various industries. Insurance, once perceived as highly resistant to change, has now accelerated the race for innovation.

Placing AI at the forefront of the innovation agenda, insurers have been separating the hype from reality to reinvent business models. Insurance has accepted the fact that AI isn`t coming — it’s here. Companies are racing to apply artificial intelligence to find a 10X improvement.

The following case studies provide a first-hand look at how today’s pioneering insurers are advancing strategic growth and transformation with artificial intelligence:

AI in Consumer Engagement

Insurers are constantly seeking opportunities to enhance the trust and relationship with customers, as the industry has always suffered from a lack of frequent and direct engagement. Today, AI is increasing being applied to collect large volumes of real-time data at very high velocity, recognize patterns of customer behavior and engage in deeper interactions for a more personalized and engaging overall experience with customers.

As AI is vying to become an indispensable part of customers’ everyday life, intelligent personal virtual assistants like Amazon’s Alexa, Microsofts’s Cortana, Google’s Now, Facebook’s M and Apple’s Siri are evolving to learn customers’ preferences and behavioral patterns and then making recommendations and potentially acting on behalf of the customer. Using just voice services, customers are now able to interact with insurers through a more intuitive channel, from asking everyday insurance questions to getting an insurance quote, or simply navigating the insurance process.

See also: Insights on Insurance and AI  

AI bots’ are becoming the new user experience (UX). Chatbot technologies are engaging customers on websites, mobile apps and messaging services such as WhatsApp, Facebook Messenger and SMS using natural language. The advancements in conversational AI agents, including their ability to adapt to speech patterns, vocabulary and personal preferences, have driven insurers to take things to the next level with full conversational interactions powered by AI bots throughout the customer journey. From a customer perspective, it`s truly a game-changing experience as we could now simply ask a question through speech or text and have insurers resolve problems or attend to an inquiry, at any point in time from any digital interfaces (including websites and mobiles apps) instead of navigating our way around complicated websites or time-consuming contact centers. Some insurers have successfully launched Alexa-integration, allowing customers to quickly access important information such as policy premium status, as well as make payments and recommend additional coverage based on lifestyle changes.

Although these advancements won`t be able to replace an agent in the short term, AI agents are learning at unprecedented speed, and this is just scratching the surface of what’s coming. A recent Gartner study predicts that, by 2020, the customer will manage 85% of its relationship with an organization without human interaction. While we know analyst projections may at times be over-optimistic, the reality is that AI likely will be the basis for competing on customer experience from here onward. There’s no turning back.

AI in Automated Advisory

Some insurers will leapfrog the innovation race with automated insurance advisory. With robo-advisers, insurers can now offer real advice without the need for any human intermediaries, anytime and anywhere.

The complexity of insurance often frustrates customers and leads to mistrust. It is also hard to decouple decisions from emotional and social reasons or agent bias.

Robo-advisers can build a consolidated financial portfolio, often aggregating data from various insurers and financial providers including life and health coverage, annuity accounts, savings, brokerages, etc. Robo-advisers then combine behavioral and external data to simulate future risk preferences, running future scenarios to infer cradle-to-grave financial plans and investment management advice.

AI in Underwriting and Claims Management

Increased automation in claims management and underwriting holds the promise of delivering a more customer-centric experience.

Today, AI-based agents are building predictive models for processing and settlement of claims expenses and high-value losses with far lower costs and heighten levels of efficiency. Tasks that took typically months are now accurately achieved in a matter of minutes, allowing insurers to focus on value-added activities. In early 2017, tongues started wagging when Lemonade used AI to settle a claim in three seconds and Fukoku Life of Japan displaced 34 employees with IBM’s Watson Explorer AI, for a 30% productivity increase.

See also: Seriously? Artificial Intelligence?  

Software developed using machine learning gathers all the details that underwriters need, while also identifying hidden risks.

Insurers are racing to routinize more work with artificial intelligence automation in core insurance business process areas such as fraud detection, policy services and contract administration, claims administration and risk compliance. We foresee increased application of artificial intelligence in any task that’s high-volume and highly repetitive and demands low human judgment, reaping sizable costs savings.

AI in Pricing Risk

Traditionally, insurers use generalized linear models (GLM), with predefined variables such as age, sex, location and occupation class, then fitted with additional factors/variables for predictions.

Today, modern machine learning techniques have increased speed, sophistication and accuracy, accelerating the adopting of usage-based and behavior-based pricing. Motor, alone, has seen a constant stream of telematics data ingested into machine learning models; driving patterns are not only used for accurate pricing of risk but also to prevent accidents by alerting drivers with behavior tips and with information about traffic and road conditions.

Health insurers are capitalizing on wearable technologies such as Fit Bits and Jawbone to drive individuals toward better health. By linking incentives to customers with healthy lifestyle characteristics such as regular exercise, walking, running, cycling, swimming and a healthy body mass index (BMI), insurers are lowering risk — and premiums.

With shorter modeling response time, increased actuarial simulation and the capability to learn, machine-based pricing is marching toward becoming an industry standard much quicker than we anticipated.

The Future

The work in artificial intelligence is just beginning. Insurers are aggressively exploring opportunities.

See also: Convergence: Insurance in 2017  

Winners will be determined by the velocity and scale of their use of AI and by the ability to go beyond pure business results. After all, the fundamental promise of an insurer is to help customers live their lives with peace of mind — healthier and safer.