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Digital Insurance, Anyone?

The digital banking conversation is alive and kicking within the FinTech world, focused on discussing the merits, definitions and initiatives around what it means for a bank to become digital across its entire technology and business stacks. I have yet to find the same level of discourse and vibrancy within the insurance world.

Spurred by Yan Ranchere’s latest blog post, I am adding my own thoughts to the insurance narrative or, dare I coin it, the “digital insurance” narrative.

First, let’s frame the discussion by attempting to define the evolution of the insurance model from old to current and future or digital:

Old Insurance Model:  This model is mostly paper-based with an application collected from the customer by the agent and sent to the carrier. The agent quote is not binding and may indeed change once the carrier has reviewed the application. I would qualify this model as carrier-centric. The carrier does all the heavy lifting with data verification and underwriting, with little stimuli from external data feeds in real time; the agent merely serves as a conduit.  As result, underwriting and closing a policy may take several days or even several weeks.

Claims management and customer service are cumbersome. Arguably, this delivers poor service in today’s age of instantaneous expectations. Not only can the old model be considered carrier-centric, I would also venture it is product-centric (in the same way that the old banking model is product-centric). The implications from a technology point of view are the same as in the banking world: a thin front end, shaky middleware and a back end that is silo-driven and that makes it difficult to optimize underwriting or claims.

Current Insurance Model:  The current model optimized the old model and made the transition from carrier-centric to agent-centric, which means that things are less paper-based and more electronic and that there is more process pushed onto the agent to be closer to the customer. In this model, the agent is empowered to issue policies under certain limits and risk frameworks—the carrier is not the gating factor and central node anymore.

Instead of batch-processing policies at the carrier level, the system has moved to exception processing at the carrier level (when concerned with nonstandard data and policies), thereby leveraging the agent. The result is faster quotes and policies signed more quickly, with the time going from days and weeks to hours or just a day. Customer service will go the same route. Claims management will still remain the central concern of the carrier, though.

Digital Insurance Model:  This is the way of the future. It is neither carrier- nor agent-centric, and it certainly is not product-centric any more. This model is truly customer- and data-centric—very similar to what we witness in digital banking. The carrier reaches out to the customer in an omni-channel way. Third-party data sources are readily available, and the technology to process and digest the data is extremely effective and delivers fast and furiously. Machine learning allows for near-instantaneous underwriting at a carrier or agent level, any time, anywhere. The customer can now get a policy in minutes.

Processes after policy-signing follow a similar transformative route. The technology implications are material: new core systems of record, less silo effect, more integration, massive investments in data warehouses and in products and services that act as layers of connection between data repository centers, core systems, claims management platforms, underwriting platforms and omni-channel platforms.

Picture the carrier effectively plugged in to the external world via data sources, plugged in to the customer in myriad ways that were not possible in the past and plugged in to third-party providers, all of this in real (or near-real) time. That means no more of the old linear prosecution of the main insurance processes: customer acquisition, underwriting, claims management. Furthermore, with a fast-changing world and more complex customer needs, delivering a product is not the winning formula any more. Understanding the customer via data in a contextual manner is.

To be fair, insurance carriers have nearly completed massive upgrades to their database architecture and can claim the latest in data warehouse technology. Some carriers have gone the path of renovating their channels and going all-out digital. Others are refining the ways they engage new customers. Most are thinking of going mobile. Still, much remains to be done. These are exciting times.

Boiling down what a digital insurance model means, we can easily see the similarities with digital banking; digital insurance must be transparent, fast, ubiquitous and data-focused, and there must be an understanding that the customer is key and is not a product.

Once you digest this new model, it is easier to sift through the key trends that are reshaping and will reshape the industry. I am listing a few that we followed at R66.  By no means is this an exhaustive list, nor is it ordered by priority, impact or size of opportunity:

1) Distribution channel disruption: There are three sub trends here—a) the consolidation of brokers and agents, b) channels going all-out-digital and disrupting the brick and mortar and c) carriers continuing to go direct and competing with brokers.

2) Insuring the sharing/renting economy: Think about Uber, Airbnb and the many other start-ups that are building the sharing economy. All of them need to or already are creating different types of coverage through their ecosystems. Carriers that focus on the specific risks, navigate the use cases, gather the right data and are forward-thinking will win big. James River is an insurance carrier that comes to mind in this space.

3) Connected data analysis: I do not use the term “big data” any more. Real-time connected data analysis is the right focus. Think of the integration of a series of hardware devices, or think of n+1 data sources. These are powerful, mind-blowing and will affect the trifecta of insurance profits: underwriting, claims management and customer acquisition.

4) Technology stack upgrades:  This means middleware to complement data warehouse investments, new systems of record, software platforms for underwriting (or claims management) and API galore. It’s the same story with banking; there is just a different insurance flavor.

5) Technology externalities: GPS, telematics, AI, machine learning, drones, IoT, wearables, smart sensors, visualization and next-generation risk analysis tools—you name it, these will help insurance companies get better at what they do, if they adopt and understand.

6) Mobile delivery:  How could I not list mobile delivery? Whether it is to improve customer acquisition; policies or claims management; or customer service, we are going mobile, baby.

7) A la carte coverage: Younger generations are approaching ownership in different ways. As a result, a one-size-fits-all insurance policy will not work any more. We are already witnessing a la carte insurance based on car usage, homes or commercial real estate connected via sensors or IoT.

8) Speciality insurance products:  We live in a digital world, baby, which means cyber security, fraud and identity theft.

It should be noted that the above describes changes in the P&C industry and that the terms “carriers” and “reinsurers” can be used interchangeably. Furthermore, I have not focused on health insurance—I know next to nothing in that field.

Any insurance expert is welcome to reach out and educate me. Anyone as clueless as I am is welcome to add their thoughts, too!

This article first appeared on Pascal Bouvier’s blog, here.

Easy Predictions on Future of Work

The trouble with our times is that the future is not what it used to be.”
– Ambrose Paul Valery – 1937

The Exaggerated Research Institute conducted a study to identify key trends that will be affecting the workforce in coming years. The research was based on interviews with leading psychics, astrologists, clairvoyants, precognitors, telepathics and other reliable sources.


Future Workforce Demographics

  • The Rise of the Contingent Workforce. The future workforce will be largely composed of contingent workers, including temps, contractors, leased employees and consultants. Most of them will be kept cryogenically frozen in storage and thawed when needed.

There will be two primary categories of contingent workers:

  • Generalists will increasingly know less and less about more and more, until they know practically nothing about almost everything.
  • Specialists will know more and more about less and less until they know practically everything about nothing.
  • Workforce Diversity. By the year 2050, four generational cohorts of employees will be working together -Millennials, Centennials, Antennials and Perennials. Designing workplaces to meet all of their diverse needs will be a major challenge. For example:
    • The ideal Millennial workplace: Ping-pong tables, meditation booths, squash courts, refrigerators, nursing rooms, food courts with healthy food options.
    • The ideal perennial workplace: Mah jong tables, medication booths, shuffleboard courts, defibrillators, napping rooms, cafeterias with early bird specials.

The Future of Management Practices

  • Workforce Reduction. Companies will continue to release employees whose skills are considered unnecessary, only to end up contracting with them as consultants at greater expense. This practice will be known as dumb-sizing.
  • Workforce Terminology. The term human capital, an endearing euphemism for “people,” will evolve to primate widget.

Workforce Technology of the Future

  • The Rise of Intelligent Machines. Increasingly, automatons such as droids, robots or drones will do nearly all work currently done by human beings. Human beings will handle some work tasks that automatons consider too boring or dangerous. This shift will be fraught with controversy.
    • Humans will argue that automatons are heartless and soulless, and therefore inferior.
    • Automatons will point out that they don’t require compensation or benefits, breaks, food, vacation time, sick days or positive feedback, and that they work faster and less expensively without complaining or making mistakes. And with the right algorithms, they can fake empathy.
  • Manufacturing Technology. 3-D printers will eventually produce nearly everything, from engines to food to human body parts. Older employees will be able to print younger versions of themselves and have their brains transplanted to their reprinted bodies. Health insurance will not cover these procedures.
  • Industrial Technology. Advances in automation and software will revolutionize every industry. For instance:
    • Trucking companies will switch to driverless trucks. Truckers will be allowed to ride along, having complete control of the horn.
    • Most packages will be delivered via drones. Human employees will be used to crush and mutilate packages before shipping.
  • Communications Technology. Email will be replaced with Tmail, a system by which messages are sent telepathically into employees’ minds via tiny implanted devices. To reduce confusion with employees’ own thoughts, T-messages will be preceded by a voice announcing, “I’ve got mail!”
  • Office Technology. The typical office of the future will have only one machine, which will be a combination PC-speakerphone/vacuum cleaner/printer/scanner/fax/floor polisher/power stapler/beverage dispenser. This machine will frequently jam and run out of magenta ink. No one will know how to fix it or whom to call.
  • The Virtual Office. Many offices and factories will be completely virtual. Virtual employees will sit at virtual workstations, work in virtual teams, report to virtual managers and get virtually nothing done. Virtual managers above a certain pay grade will have virtual windows.
  • Computing Technology. The cloud will soon reach its storage capacity. From that point on, employees will store their data somewhere over the rainbow. Video goggles will replace desktop and laptop computer screens. Healthcare costs will escalate as goggled employees obliviously walk into traffic, fall down stairs and crash into furniture.
  • Commuting Technology. Inspired by George Jetson, many employees will commute to their workplaces in flying cars that transform into briefcases. GM’s flying cars will be recalled after several transform prematurely during flight.
  • The Paperless Office. By the mid 2040s, companies will realize that they have stocked millions of file cabinets containing unidentifiable documents and obsolete office supplies. To comply with auditing and risk management policies, all file cabinets will be permanently warehoused.

The Future of Learning and Development

  • Preparation for the Working World. Trivial elementary school courses such as social studies, history, art and literature will be replaced with practical content on designing e-commerce apps, managing technology start-ups, seeking venture capital and launching successful IPOs.
  • Virtual Reality Training. All employee training will be delivered via fully integrated virtual-reality helmets that will simulate the real work environment. For example, in a realistic job preview, trainees’ virtual avatars will lose all of their self-esteem by being ignored, criticized, overlooked, disregarded, misunderstood, unappreciated, excluded, undercompensated and unrecognized.

The Future of Performance Management

  • Performance Reviews. Because of its inherent inaccuracies and biases, the dreaded annual performance review process will fall by the wayside. Instead, 360-degree feedback processes will be expanded to include feedback from employees’ relatives. Subsequently, employees will petition for the return of annual performance reviews.

The Future of Rewards

  • Most future companies will pay their employees with Bit-coin, a virtual currency. Most employees will find Bit-coins virtually impossible to understand, cash or spend, even though they will be accepted at virtually all new-age coffee shops. As a result, workers will collaborate to create a bartering economy in which, for example, groceries are traded for sheep.
  • The gap between top executive pay and average employee pay will continue to escalate from the current “You can’t be serious” to “You’re f****** kidding me.”
  • In a cost-saving measure, most companies will eliminate nearly all existing employee benefits. From that point on, benefits will refer to carpeting, windows, air conditioning and chairs.

The Future of Innovation

  • The Quality Movement will devolve into a mediocrity movement when it is discovered that mediocrity can be delivered consistently at lower expense. Companies that previously had mottos like “Quality is Job 1” will switch to slogans like “Feh, that’ll do.”
  • Change Management. Companies will stop the expense associated with continual change and institute change-avoidance initiatives. Employees will receive incentives for not trying anything new or different.

The Future of Employee Engagement

  • Employee engagement surveys, which will automatically import each worker’s employee ID, race, gender, age, level, job code, manager name, work location and tenure, will remain “anonymous.”
  • Employee engagement survey reporting will become continually faster. This will make it possible for managers to ignore employee feedback more frequently, and in real time.
  • Through Six Sigma improvement efforts, many companies will successfully reduce the time it takes for post-survey action plans to be ignored, forgotten and abandoned.

The Future Work Environment

  • Flexible Work Arrangements. The work from home (WFH) movement will evolve into a work from bed (WFB) movement, as WFH employees continue to try to further reduce their commuting time. Sleepworking will be a constant challenge for management, as will safety procedures for certain jobs, such as those that involve welding.
  • Workplace Design. To optimize workspace and reduce cost, most work cubicles will be double-deckered and sized based on each worker’s height and girth. Floors will be covered with torn newspaper and partitions replaced with chicken wire. Each cubicle will include a water tube and, in larger cubicles, a running wheel.


By the year 2050, the vision of the people-less office will become a reality, as automatons make all human employees redundant. Most former workers and their families will move to Western states, where they will live in log cabins, tents, abandoned vehicles, trailers and caves. They will live off the electrical grid, subsist on fishing and farming and have perfect work/life balance. They will practice the art of storytelling, spend endless time with their families and discover true happiness.

AI’s Huge Potential for Underwriting

For decades, the insurance industry has led the world in predictive analysis and risk assessment. And today, with the treasure trove of big data available from historical processes, IoT and social media, insurance companies have the opportunity to take this discipline to a whole new level of accuracy, consistency and customer experience.

The actuarial models that were once driven solely by large databases can now be fueled with tremendous quantities of unstructured data from social media, online research and news, weather and traffic reports, real-time securities feeds and other valuable information sources as well as by “tribal knowledge” such as internal reports, policies and regulations, presentations, emails, memos and evaluations. In fact, it is estimated that 90% of global data has been created in the past two years, and 80% of that data is unstructured.

A large portion of this data now comes from the Internet of Things — computers, smart phones and wearables, GPS-enabled devices, transportation telematics, sensors, energy controls and medical devices. Even with the advancement of big data analytics, the integration of all this structured and unstructured data would appear to be a monumental achievement with traditional database management tools. Even if we could somehow blend this data, would we then need thousands of canned reports, or a highly trained data analytics expert in every operating department to make use of it? The answer to this dilemma may be as close as our smartphones.

Apps that Unleash the Power

As consumers, we are no stranger to the union of the structured and unstructured datasets. A commuter, for example, used to rely on Google Maps to get from his office to his home. But with the advent of apps like Waze, not only can he get directions and arrival times based on mileage and speed data, but can also combine this intelligence with feeds from social media and crowd-sourced opinions on traffic. Significant advances in the power of in-memory processing, machine learning, artificial intelligence and natural language processing have the potential to blend millions of data points from operational systems, tribal knowledge and the Internet of Things — using apps no more complicated than Google Maps.

Using apps that harness the power of artificial intelligence and machine learning can provide far superior predictive analysis simply by typing in a question, such as: What are the chances of a terrorist act in Omaha during the month of December? Where is the most likely place a power blackout will occur in August? How many passenger train accidents will occur in the Northeast corridor over the next six months? What will be the effect on my fixed income portfolio if the Federal Reserve raises short term interest rates by .25 percentage point?

Using a gamified interface, these apps can use game theory such as Monte Carlo simulations simply by moving and overlaying graphical objects on your computer screen or tablet. As an example, you could calculate the likely dollar damages to policyholders caused by an impending hurricane simply by moving symbols for wind, rain and time duration over a map image. Here are some typical applications for AI app technology in insurance:

Catastrophe Risk and Damage Analysis

Incorporate historical weather patterns, news, research reports and social media into calculations of risk from potential catastrophes to price coverage or determine prudent levels of reinsurance.

Targeted Risk Analysis (Single view of customers)

With the wealth of individual information available on people and organizations, it is now possible to apply AI and machine learning principles to provide risk profiles targeted down to an individual. For example, a Facebook profile of a mountain climbing enthusiast would indicate a propensity for risk taking that might warrant a different profile than a golfer. Machine learning agents can now parse through LinkedIn profiles, Facebook posts, tweets and blogs to provide the underwriter with a targeted set of metrics to accurately assess the risk index of an individual.


Each individual assessor has his own predilection to assessing risks. By some estimates, insurance companies could lose hundreds of millions of dollars either through inaccurate risk profiling or through lost customers because of overpricing. AI apps provide the mechanics to capture “tribal knowledge,” thereby providing a uniform assessment metric across the entire underwriting process.

Claims Processing

By unifying unstructured data across historical claims, it is possible to establish ground rules (or quantitative metrics) across fuzzy baselines that were previously not possible. Claims notes from customer service representatives that would previously fall through the cracks are now caught, processed and flagged for better claims expediting and improved customer satisfaction. By incorporating personnel records when a major casualty event occurs, such as a severe storm or flood, you can now dispatch the most experienced claims personnel to areas with the highest-value property.

Fraud Control

Integrate social media into the claims review process. For example, it would be very suspect if someone who just put in a workers’ compensation claim for a severe back injury was bragging about his performance at his weekend rugby match on Facebook.

A Powerful Value Proposition

The value proposition of artificial intelligence apps for better insurance industry underwriting and risk management is too big to ignore. Apps have been transformational in the way we intelligently manage our lives, and App Orchid predicts they will be just as transformational in the way insurance companies manage their operations.

3 Game Changers — and How to Survive

The follow-the-leader principle works on a trail that has proven to be relatively safe from perils and predators. However, when new frontiers are breached, a new kind of leadership is required for survival.

Insurers have generally been able to just follow the leader for ages, but now a new frontier has been breached. The insurance industry is vulnerable to three game changers that consumers are eager to embrace.

Drawing on remarks I made recently at a keynote for the National Association of Mutual Insurance Companies Annual Conference, here are the game changers:

The first big disrupter is data collection. Insurance is built on the principle of using accurate data and statistics to build underwriting financial models that serve to predict behavior and events from an actuarial or probability standpoint. London’s Edward Lloyd figured this out when he opened his coffee shop in 1688, and people started selling insurance to merchants and ship owners. His motto was fidentia, Latin for confidence. We now refer to “confidence factors” when estimating future losses.

Insurers have been notorious for using forms to collect data. But, today, a person is subjected to more new information in one day than a person in the Middle Ages saw in his entire life. If modern competitors to the insurance industry can obtain more accurate data in a faster and more in-depth manner, they may beat insurers at their own game.

With cloud computing and its infinite data storage/retrieval capability, trillions of bits of information relating to insureds are available. Data sources track things like profile patterns, such as personal Internet searches or satellite surveillance data. Relevant data can be mined and analyzed to build a risk model for every insurable consumer or business peril from property and vehicle insurance to earthquake and weather insurance.

The five biggest data collectors on the planet are Google, Apple, Facebook, Yahoo and Amazon. These high-tech companies have the ability, financial resources and potential desire to foray into the insurance industry. Keep in mind that in 2014 the world’s top 10 insurers received $1.2 trillion in revenue, yet surveys have shown that people around the world have grown to use and trust the products and services provided by the five biggest data collectors.

Accessibility and familiarity are allowing profitable new brands to replace old brands. Consumers also prefer and use third-party validation and independent comparisons found on websites.

What does this spell for the insurance industry? Sadly, consumers have grown more uncomfortable with reliance on and interaction with agent relationships. John Maynard Keynes once said: “The difficulty lies not so much in developing new ideas, as in escaping from old ones.”

The second emerging threat to insurance is botsourcing — the replacement of human jobs by robotics. The robots haven’t just hatched in agriculture or auto assembly plants — they’re expanding in a variety of skills, moving up the corporate ladder, showing awesome productivity and retention rates and increasingly shoving aside their human counterparts.

Google won a patent recently to start building worker robots with personalities. Move over, Siri.

Author and entrepreneur Martin Ford, in his book Rise of the Robots, argues that artificial intelligence (AI) and robotics will soon overhaul our economy. Increasingly, machines will be able to take care of themselves, and fewer jobs will be necessary.

Reassessment of the way we employ our workforce is essential to cope with this new industrial revolution. The lucrative insurance realm of personal and product liability insurance lines and workers’ comp is being tempered as human risk factors — especially in high-risk areas — give way to robotics. The saying goes: “Management is doing things right, but leadership is doing the right things.”

How will the insurance industry react to the accelerating technology of bot-sourcing?

The third emerging threat to the insurance industry that has received enormous attention this past year autonomous vehicles. More than a half-dozen carmakers, as well as Google and Uber, predict that self-driving vehicles will be commonplace on our roads between 2017 and 2020. Tesla Motors CEO and general future-tech proponent Elon Musk has predicted that human drivers could someday be outlawed. Humans cannot outperform an autonomous vehicle, which can assess and react to more than 7,000 driving threats per second. There are no incidents of driver impairment, reckless driving, DUIs, road rage, driver texting, speeding or inattention.

With a plethora of electronic distractions, increased safety can only be achieved when human drivers are removed from the equation. Automakers have employed an incremental approach to safety in their current models. These new technologies are clever and helpful but do not remove the risks. There’s a phenomenon called the Peltzman Effect, based on research from an economist at the University of Chicago who studied auto accidents. He found that, when you introduce more safety features like seatbelts into cars, the number of fatalities and injuries doesn’t drop. The reason is that people compensate for it. When you have a safety net in place, people will naturally take more risks. Today, 35,000 vehicle occupants die in the U.S. because of auto accidents. Autonomous vehicles are expected to cut auto-related deaths and injuries by 80% or more.

One of the biggest revenue sources to insurers is vehicle insurance. As autonomous vehicles take over our roads and highways, you need to address all the numerous unanswered questions relating to the risk playing field. Who will own the vehicles? How can you assess the potential liability of software failure or cyberattacks? Will insurers still have a role? Where will legal liabilities fall? Who will lead the call to sort these issues out?

Clearly, the lucrative auto insurance market will change drastically. Insurance and reinsurance company leadership will be an essential ingredient to address this disruptive technology.

As I told the conference: Count on Insurance Thought Leadership to play a significant role in addressing these and other disruptive technologies facing the insurance industry. A Chinese proverb says: “Not the cry, but the flight of a wild duck, leads the flock to fly and follow.”

Seriously? Artificial Intelligence?

I don’t know about you, but when I think of artificial intelligence, I think Steven Spielberg and Arnold. That was until I saw a solution offered by Conversica, a Salesforce partner.

AI is here, it’s happening now and it’s a lot more pervasive than you think. The rise of “robo advisers” in financial services, Ikea’s “Anna” customer service rep and Alaska Airline’s “Jenn” all point to the growing adoption of technology that personalizes customer experiences….at scale.

One of the 5 D’s of Disruption in insurance is “Dialogue.” And AI is driving it.

Today, in insurance, AI is used to create natural dialogue with customers, nurture those leads, prioritize them for agents and follow through as needed. Conversica, for example, gets smarter as it interacts more with customers. And, yes, it has passed the Turing test.

It is particularly well-suited for B2C because the volume of interactions with prospects can be overwhelming for insurance agents. As insurers embrace omni-channel, new prospects can be created from any source, whether it be a contact center, social media or a face-to-face meeting. Not only is lead volume increasing, but it takes as many as six before an agent can get a prospect on the phone. This becomes a time and energy suck for agents; he is unable to follow through on every lead, and the quality of interactions goes down.

So how are insurers and agents responding? In this webinar, Eric (Conversica) and Alex (Spring Venture Group) explain to me how AI is used to nurture and convert leads.

My takeaway: AI is not just a science project. It works. It’ll become more invisible to consumers. And it creates real value to both customers and employees.

As Marc Benioff, CEO of Salesforce, said recently in Fortune magazine, “We’re in an AI spring. I think for every company, the revolution in data science will fundamentally change how we run our business because we’re going to have computers aiding us in how we’re interacting with our customers.”