As if the insurance industry was not complex enough, let’s add in a dose of AI, a pinch of ML, a dash of IoT and a garnish of Blockchain. This spread is a lot to bite off, let alone digest, but not impossible when the catalyst for their existence is broken down. Each one of these cryptic buzzwords simply solves for a human expectation, or soon-to-be need.
Chances are, you have heard of these terms being tossed around—as they are quickly becoming hot commodities across most industries. But, what is AI? And what is ML? And what is IoT? In short, they are innovative ways companies are beginning to collect, organize and implement data (recorded information) to drive a desired result. See, this isn’t so bad, right?
Artificial Intelligence (AI) is, as it is used in the insurance space, far from synonymous with Spielberg’s computerized beings. The interpretations of AI and its functions are extremely broad and hard to define as they are constantly changing. Essentially AI refers to the programming of computers to behave in a certain way under a set circumstance or an endless set of circumstances. It is a logical argument, really: if a then b, or if a & b then c, etc. It’s a large chess game in which the room for human error is eliminated.
Born out of AI, Machine Learning (ML) and predictive analytics are, in a way, subsets of AI, while they are also technologies that help to support it. ML and predictive analytics take the algorithms from the various logically programmed codes and then, through time and series of events, begin to “behave”, predict and automate according to patterns and irregularities.
To tie it all together, quite literally, the Internet of Things (IoT) is also a spawn of AI. IoT is, basically, the communication of people, things and computers that does not need the consciousness of a human to make that communication happen. IoT can be explained through the lack-there-of scenario below:
Imagine that you have left for work and while pulling into the office realized that you left the stove on. You call your neighbor and beg for their help, they stroll over to your house (20 minutes later), dig under your porch for the coffee can that houses the key to your front door. They unlock the door and walk in while fighting back the cats, they turn the stove off, exit, lock the door, re-plant the coffee can with the key and return home, cursing you all the way.
With IoT, everything is connected and communicating all the time and you would not even have to know how your stove was turned off because this would have been the scenario:
You head to work and forget that your stove was ever on. Luckily, your thermostat senses heat coming from your kitchen that has been hot for too long and it knows that no one is left in the house because the door was locked from the outside. Sensing danger, your IoT system sends a message to the stove and turns it off, averting the crisis altogether without you having to blink an eye- (oT).
Now, amplify this scenario by the millions of possibilities to control virtually anything if it is hooked up to a centralized…dare I say, nervous system. This is how IoT operates within large organizations to eliminate the wasted time and energy associated with human error while also enhancing efficiency and predictive outcomes.
Don’t Fear the Buzz!
Unfortunately, these buzzwords have developed a reputation of being extremely complex and foreign when, conversely, they were invented to eliminate the experience of those very descriptors. These technologies are designed to increase efficiency and precision, eliminate possible difficulties of organizing massive amounts of recorded information and can be applied to most anything that collects data.
Various tools, software and apps are being integrated into the internal/external processes of the insurance industry utilizing the great technological skill of these data-driven buzzwords. Perks of these integrations include real-time segmentation/personalization, generation of automation, and the streamlining of relationships between applications, devices, automated equipment, components, sensors, mobile devices, appliances and, perhaps, limitless other integration possibilities.
What Does This Mean for You?
From an insurance marketing perspective, the incorporation of these technologies is bringing about dramatic disruption. Higher levels of decision making and strategy to drive acquisition and awareness, to improve the customer/agent experience by leaps and bounds, and to boost ROI in nearly every department is being made possible by these technologies. (Not to mention their ability to not only increase ROI, but to tighten up the precision of the numbers surrounding ROI- music to any C-suite’s ears).
One of the voluntary benefits/supplementary insurance leaders in marketing, Aflac’s Catherine Blades, explains how important data is in measuring decisions. “My boss and I get so frustrated with reports that show ‘Oh, this popped up,’ but the data feels so random. You need unicorns who can take that data, translate it, make it relevant and turn it into actionable insights that you can measure against business objectives. I want to show my CEO how we’ve moved the needle.” (Cision n.d.)
These unicorns that Blades is referring to may not necessarily be human anomalies, but are starting to materialize in the form of AI and ML. These buzzwords are just doing jobs we do, but with much more precision and efficiency. AI and ML are just tools, not the hands that hold them.
The Gold Mine of Data
Despite the fear of the unknown, there is a kind of frenzy to implement these technologies that eerily resembles the same call to The Gold Rush of the mid-1800s. Every business is after a piece of the action, and some without fully knowing what it is, exactly, they are after, how to find it, and then how to mine it in an effective way to drive results. So, what is going on with this whole data collection thing and business?
Up until the Apple/Amazon/Google/Facebook phenomena of producing personalization through data, the collection of it was a more formal affair. Now, the interconnectedness of AI, ML, IoT and data analytics allows for consumer data to be shared behind the scenes, giving consumers the personalized experience that they have come to value and expect without ever having to think about how companies are providing it.
Collecting and utilizing data has become a passive transaction rather than the formulary mode of the past. Its passivity can be attributed to consumers’ trust in the data system and the companies collecting the data. Since most consumers are willing to give up their personal information in exchange for a convenient, personalized experience, consumer trust is almost a given. Because of this virtually seamless exchange and transaction between consumer and business, mass integration, the amount of data being collected and the ways in which it is collected is growing exponentially (not to mention the possibilities in which to use this data).
According to the new AXA Foresight trendbook, “IDC forecasts that by 2025 the global datasphere will have grown to 163 zettabytes…” That’s ONE TRILLION gigabytes! Which is “… ten times the amount of data generated in 2016. The volume and multiplicity of this data will open up a new world of business opportunities and unique user experiences.” (AXA 2018)
The continued multiplicity and worth of data is congruently intensifying the shade of data analysis from a dull organizational task to an empowered, multi-positional asset of marketing decision making and strategy development. Data is being used to drive business and to restructure business models everywhere. A data analyst is no longer an isolated job title, but rather, most current marketing and business development roles have incorporated it into their normal job responsibilities to drive conversions and track everything possible with the help of these innovative technologies.
Give Me the Cold, Hard Data
Ok, great. Now we know how important data is. But, how is it actually being used? In a recent Business Insurance article, Ralph Blust, president of Insureon Solutions, explains how data is being used in the B2B arena of the insurance industry using digital platforms. He also touches on the hot topic surrounding the fear that computers will take over the need for a human agent/broker. He describes how these buzzword technologies are not going to “take over” people’s jobs, but will, in fact, enhance these jobs and bring humanization back into the job.
“Digital platforms will not disintermediate insurance agents and brokers. In fact, it will have the opposite effect. Technology eliminates many of the administrative tasks that often fill up brokers’ days, allowing them to focus their efforts on risk identification and mitigation, consulting their insureds and helping them better manage the financial exposures their clients face.” (htt)
Explained in the same article, Erica Davis, SVP at JLT Re Inc. focuses on the data collection capabilities of the platforms being created in the insurance industry. “[They] are a gateway for the carriers to learn more about segments—what products are most helpful, what sort of claims exist [in each] segment—[these] are all helpful to drive growth and establish access to new markets.”
“Those that can harvest data and use technology to access data in an intelligent manner can build the best product for the future,” Brian McDermott, CIO, Victor. (htt)
The possibilities with utilizing data in the B2C insurance market is being tested in every which way. The insurance industry is notorious for lacking in great customer-service, but with the help and use of data, personalization and segmentation it is driving incredible customer experiences that no one could have imagined in these lines of business. Insurance? Experiences? Refreshing? They are now, thanks to data.
The Next Frontier of Insurance Marketing
Revolutionary data-driven insurance marketing initiatives that are in the works are projected to shake every insurance legacy architecture organization that we have come to expect. This is an amazing time to be in the insurance marketing business thanks to data and the systems being integrated to support it. One of the next big integration leaps in insurance marketing will be to implement the infamous, and a bit mysterious, Blockchain.
Our next post, Insurance Marketing, Measurements and Blockchain: A Love Triangle, will concentrate on how these technologies are being used in the insurance marketing industry, with a specific emphasis on Blockchain’s predicted disruption to both B2B and B2C marketing.
AXA Foresight, The AXA trendbook, November 2018