Tag Archives: Tony Canas

We Need to Talk About Our Call Centers

I started my career in insurance at the same place where most of our millennials are starting theirs, in the call center. In my case, it was a Farm Bureau claims call center in the beautiful suburban campus in West Des Moines, Iowa. I didn’t know it at the time, but I got really lucky. That call center was very well run by enlightened leaders who realized they were training the future leaders of the company.

As early as the interview, managers told me that this call center was different. They understood that most of the new talent coming into the company would start in this department, and they had been instructed to engage and train those young professionals, so they would grow into productive employees not only during but after their time in the call center.

They said they wanted me to spend two to three years in the call center, while learning as much as possible about the company and the insurance industry in general. After that, I’d be expected to start applying for positions beyond the phones. The department also required each individual to obtain the Associate in General Insurance (AINS) and the Associate in Claims (AIC) within the first two years. Failure to comply with the educational requirement could lead to termination.

The way the call center functioned on a day-by-day basis was also quite engaging. Reps were trained well and supported in their efforts to grow their career (even when it meant time away from the phones for a class). The call center answered all first notice of loss calls for both personal and commercial lines claims, so it was not overly specialized; there was lots of variety on the day-to-day work. You’d get to keep the simple claims and work them to completion, acting as real claims adjusters. This resulted in great customer service, as roughly 40% of all calls would be answered by the person ultimately handling the claim. The approach also resulted in lots of employee growth.

Even the way that managers measured performance was not bad at all for a call center. While they did measure the amount of time you spent on “After Call Work” and “Unavailable,” it wasn’t the main thing they cared about. To the best of my knowledge, they didn’t measure the dreaded “Time on Call” that most call centers use as their main measure of productivity. The main thing that counted in this particular call center was the number of new claims you took and the percentage of those that you kept.

At the end of every week, management would send out a list of the top 10 reps who answered the most calls and kept the highest of those calls. I was almost always in the top two for both categories, and enjoyed the friendly competition. Because the list only included the top 10, not the bottom ones, people weren’t offended by it; it was a very positive thing. Management also included in the weekly newsletter a congratulatory mention of everyone who had passed an insurance designation test.

While at times the call center could get hectic, the overall environment was very supportive of employee growth, and nobody seemed to hate the job. Eight years later, most of the people I worked with in that call center are still in insurance, and none of them are still call center workers. Many stayed in claims. Many are still in the same company. That’s a successful insurance call center in our book! It was such a great place that I was sad to leave when I got an offer for a better claims position at Nationwide, which ended my call center days.

Sadly, I would find out as I met many other young insurance professionals that great insurance call centers that focus on developing their people are rare. Most are simply awful places to work, and, while nobody seems to be keeping statistics publicly, we have found 20 horror stories for every positive one.

There are many conferences about insurance, and none seem to be talking about our call centers. The CPCU Society Annual Meeting and Leadership Summit has not had a single session about call centers in at least the six years I have been involved. It’s almost as if those call centers didn’t exist! Or, more likely, the leadership just doesn’t view them as really being insurance.

It’s like the call centers are the black sheep of the insurance family that nobody wants to talk about!

A huge portion of young insurance professionals in the 2010s started their insurance careers in a call center type environment. Most of them already had college degrees (and the associated student loans). Like previous generations, they fell into insurance by accident, but, unlike previous generations, they won’t stay out of loyalty or out of having found great careers. If we do our job right and engage them in the industry, they’ll grow. If we don’t, they’ll leave the industry, and we’ll continue having a huge talent gap.

We’re not saying that we should close all the call centers and go back to doing business exclusively in the old-fashioned way. We understand that our expense ratio will not allow us to do that in the age of price transparency and incredible competition for every insurance customer. What we are saying is that we need to realize that, in many cases, the call center is our only touch-point with the customer, and we should be making them love their time with us. Maybe even more importantly, the call centers are our new entry level point for new talent, and given the talent crisis, our bad reputation with younger generations, and the high expense of replacing any employee, we need that talent to grow with us.

See also: How to Reinvent Call Centers  

Based on the horror stories we’ve collected from conversations with fellow young insurance pros who survived some time in the call center and lived to tell the tale, here’s what many (but  not all) of the insurance call centers are like to work in:

You have to be logged in to the phones every minute you are in the office and are not allowed to even be in the office outside of your work hours. There are rows after rows of grey cubicles, packed with unhappy 25-year-olds with their college degrees hanging precariously from the cubicle wall and the headset making a semi-permanent mark in their ear.

Engagement is so low that it could better be measured in level of desperation. Turnover is high, with the great majority leaving not only the company but the industry and swearing they’ll never work in insurance again. The reps who haven’t quite given up on the industry yet are applying desperately to any open entry-level position that’s not a call center. It doesn’t matter if it’s claims, underwriting, processing or subrogation. Anything will do just to get off the phones! There’s so many applying for the same jobs with essentially the same resume, college degree and one to two years of insurance call center experience, that’s it’s very hard to differentiate among them, so hiring managers mostly just reject them without an interview. Some have been told directly that “we don’t hire from the call center.”

They are measured on 50-plus different characteristics, so many that it’s impossible to actually focus on improving. Who can control that many different minor factors during each phone call? The most important measures tend to be Time-on-Call and Availability. The first one measures the length of the average call, with the goal of keeping it as low as possible, and the second one measures the percentage of the time they’re available to take calls. In some extreme cases, even mandatory team meetings count against you the same as time spent in the restroom counts against you.

Performance evaluations are focused 100% on metrics and very little on your own growth or what you need to do to get out of the call center. Most of the supervisors are former call center reps themselves who only know the call center life. They often don’t know anything else about the company or the industry and can’t serve as good mentors even if they wanted to.

Professional development is encouraged by the company, but development time allowed by the department is very limited or completely non-existent, leaving it to  the employee to do all growth activities outside work hours. A case could be made that a motivated employee can grow by investing his own free time into activities like insurance designations, Toastmasters and networking, but most have no previous insurance experience and no advice on what they should be spending their time doing to grow with the company. The only thing they know is that they don’t want to be on the phones, and they don’t want to become call center supervisors either.

We have even heard stories of call center employees being denied support in getting their basic insurance designations because they’re not required for the call center job the employees are doing. Some are denied even the ability to participate in activities such as Toastmasters or a young professional group because those meetings are in the office, and Human Resources doesn’t want employees to be in the office outside of work hours.

There are better ways to run a call center. Not only should others learn from the example of the Farm Bureau Financial Service center where I worked, but there’s even more that we can learn from the best-run call centers outside the industry.

Look at Zappos, which was founded on the crazy idea of selling shoes online. Think about that one: Shoes are the kind of thing that absolutely has to be tried in person, and, when you go shoe shopping, chances are you try multiple shoes before you find a pair that fits just right. Zappos succeeded selling shoes online by doing two things differently: The company will ship you as many shoes as you want, and then you can try them and keep the ones you want, returning the rest. Zappos will cover the shipping both ways.

The second thing Zappos does is provide amazing customer service. To provide that service, Zappos runs large call centers staffed by very happy employees. How does it keep call center employees happy? By doing things diametrically differently from most other call centers (including insurance call centers).

The hiring process consists of several interviews, mostly looking for personality fit. The HR rep conducting the first interview tries to simply figure out if this is a person he would want to work next to for 40 hours a week. Skills are much less important — skills can be taught. During the hiring process, Zappos makes it very clear that the great majority of positions are at the call center, and, if you take the job, you’ll be answering the phones for a long time.

Every new employee, regardless of position, must go through the call center training. You can be hired for a vice president role and on day one you get to go to your new office to set your stuff down, and then you come back down to train for the call center with everybody else. After finishing training, everyone gets to work the call center for a couple of weeks before going on to the job they were hired for. This guarantees that all the leadership knows what the call center is like. Currently, in insurance, there are very few, if any, senior executives who came from the call center, partially because those call centers didn’t exist or were much smaller when those executives were starting their careers.

After their first couple of weeks on the phone full time, all new Zappos employees get called into a huddle room with their manager. The conversation includes giving the employee real feedback about her performance in the call center. Then the manager reminds the employee that most jobs at Zappos are at the call center level and that it’s hard to move to a different area. Finally, the manager says something like “Charlie, I’ve got  a check in your name for $2,000. I want to pay you to quit. If you don’t love the job, take the money, and we can part ways, no hard feelings.” Zappos does such a good job in hiring, orientation and training that only 2% of people take the offer.

The way Zappos measures performance is very different from others, too. It doesn’t measure Time-on-Call at all. All Zappos cares about is making the customer happy. That may mean ordering a pizza for a customer who is traveling and doesn’t know where to get a pizza or chatting for seven hours with a customer about which shoes to buy for her prom.

Zappos understands that happy employees lead to happy customers, and that, in a world where your only interaction with the customer is when she visits your website or calls your call center, a call is a huge opportunity to connect with the customer. Zappos understands that a call center is NOT a cost center; it’s a key touch-point with our customer. What could be more important than that?

The insurance industry has a lot to learn from Zappos. As millennials become a bigger and bigger part of our customer base, and they are not fans of visiting an agent’s office, the call center becomes our touch-point with the 95% of our customers who didn’t have a claim in any given year. Also, if the majority of your new employees are starting at the call center level, it’s our only chance to get them to fall in love with the industry and to convince them to make a career here.

See also: Insurers’ Call Centers: a Cyber Weakness?  

For more about the Zappos way, I highly recommend the book Delivering Happiness by Tony Hsieh, the CEO of Zappos. This amazing book will give you a great intro to how Zappos runs its business, especially its call centers. The company also provides guided tours of its offices in Las Vegas. The company provides training and consulting for other companies through its consulting arm Zappos Insights. You can learn more here.

We are strong believers that the first large carrier to figure out how to turn its call centers into talent mines will have a major competitive advantage in the talent wars. Combine that with student loan aid and maybe with opportunities to take sabbaticals every few years, and you’ll create an unmatched employee experience that millennials will not want to leave.

This article originally published at InsNerds.com.

Let’s Sponsor a Free Online RMI Course

The average age of an insurance professional in the U.S. is around 60 years old. Estimates place the giant wave of retirements coming our way at around 50% by 2020. The U.S. Department of Labor estimates that between retirements and growth we’ll need to hire 400,000 people in the next decade. That’s a lot of people!

Risk Management and Insurance (RMI) programs at colleges and universities have become more popular over the last few years, but they still only exist at fewer than 100 out of the 3,000-plus institutions in the U.S. RMI programs produce amazing graduates, but they only feed 15% of our hiring needs each year! So 85% of our new hires come without any sort of insurance background or education. Each company has to take the full expense of training these new insurance pros, and retention is lower because those people haven’t committed to a career in insurance; they might still be testing the waters.

See also: A New Paradigm for Risk Management?  

At the same time, college has gotten more expensive, and total student loan debt stands at around $1.3 trillion! That debt is very scary to potential college students, and many are choosing to forego going to college to avoid going into debt. This is bad for their future employment, but it’s also a waste for us; we could use their talents if we just played our cards right.

This is where today’s crazy idea comes in. We should come together as an industry and ally ourselves with an online education provider such as Coursera. Coursera offers massive open online courses (MOOCs) from world class universities in video format, with intra-video quizzing, group projects, automated grading of multiple choice tests and student peer grading of papers. You can take almost any Coursera class for free, or you can pay a small fee to get a certificate proving you passed the class. Coursera even has cool technology to verify you’re doing your classwork yourself instead of paying someone else to take tests for you.

Currently, there is not a single insurance and risk management class on Coursera. The only classes that come up in a search have to do with health insurance exchanges or with product and portfolio financial risks.

See also: The Sad State of Continuing Education  

We should come together as an industry and sponsor a free (or almost free) risk management and insurance program on Coursera, available to ANY student who is interested. We would work with the school to make sure the curriculum teaches them the things employers in the industry need them to know, and we could even split it into an “associate” type program meant to train customer service rpepresentatives (CSRs) for agencies and a more in-depth “bachelor” type program meant to train future underwriters, agents and claims and other industry professionals.

This could be a cost-effective way to make big strides toward solving our talent crisis, and it would help us improve our image overall. Who’s in?

This article originally appeared on InsNerds.com.

The Story Behind the Lemonade Hype

I am a sucker for new stuff. I bet many of you are, as well. If news of the iPhone 7’s release date caused you to immediately organize your camping gear for a week-long sidewalk holiday at your local Apple store, then you know what I am talking about. Beyond our excitement for the next iPhone or Tesla, apparently we also get all giddy for new insurance, as well.

Recently, an insurer named Lemonade has popped up on the scene and has caused quite a ripple. Here are some recent news headlines:

Wow! Give that publicist a raise. That is some quality publicity.

But it was when I saw this headline, “The Sheer Genius of Lemonade – A Whole New Paradigm for Personal Lines Insurance,” on InsNerds that I knew I had to speak out. Next thing I know, my good friend Tony Canas at InsNerds convinced me to write this response.

To start, this article is NOT a criticism of Lemonade or what it is trying to bring to the consumer. Insurance is in desperate need of heart and soul. No, what this article will do is splash some cold water on the hype inferno that appears to have taken over the sane minds of our industry. Allow me to go point-by-point with my issues:

Is Lemonade really peer-to-peer insurance?

Whether it is called peer-to-peer — or fashionably referred to as P2P — Lemonade ain’t it. Lemonade is a standard insurance company. You pay premiums, and the company pays claims from the general pool of funds. There are no peer groups insuring one another. There is no distribution model of peer invitations or referrals. The only “peer” element of the business model is that you will, as a customer, be grouped with others like you for the sole purpose of dispersing any underwriting profits to a charity of the group’s choosing. Now, there is a reason for this, but, seriously, was anything I just described even remotely connotative of peer-to-peer? Want to know what peer-to-peer looks like, see Friendsurance or Guevara.

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Is Lemonade really insurtech?

Sure, Lemonade is an online-only firm. And, yes, you can buy its insurance products through an app on your phone, where a bot named Maya will help you with your coverage selections, but Lemonade is still just an insurance company with a fancy website. I can buy insurance from other insurance companies where I can choose from dealing with a website, walking into an agent’s office or calling an agent over the phone. Lemonade has eliminated two options and given me a sole option that is little different from what I could have had before. And before you start screaming, “But I don’t want to call anyone or drive to any office,” just keep in mind that having options makes the experience better. Insurance is complicated enough that, occasionally, I would like to call someone or walk into an office and scream my head off. I deserve that option!

See also: Could an Incumbent Act Like Lemonade?  

What about the bot and the machine language? Isn’t that technology? It is technology in the sense that there are computer scientists engineering a robot to replace a human. But if the experience is crummier than just dealing with a human, it is a wasted effort.

In an attempt to play fair, I will reverse my position on this one — if it can be shown that the robot can handle the firestorm that comes when the company is hit with its first major natural catastrophe.

But isn’t it awesome that Lemonade’s underwriting profits go to charity?

One of the big marketing ideas coming from Lemonade is the unique feature of aligning the interests of policyholders and the insurer by taking excess profits and donating them to charity in the name of the peer group. Fraud is a big deal in insurance, and most insurers have systems in place to detect and counteract fraud. The charity angle from Lemonade is an attempt to prevent fraud from happening by linking the monetary loss because of fraud not to the big-bad insurer but to a softer, more sympathetic victim. Fundamentally, if you are a Lemonade policyholder and your claim is fraudulent is any way, you are depriving some charity of much-needed funds.

It is an interesting concept, but I don’t believe it will have much of a financial punch. The first drawback is that property insurance — being exposed to natural catastrophes (CAT) — is subjected to infrequent but occasionally massive losses. What appear to be underwriting profits in the quiet years between CATs are really opportunities to strengthen your balance sheet for the inevitable hit. As Lemonade expands to other states, its inability to build surplus because of the charity and the corporate status (see below), will really hamper the company’s business model. Lemonade is now, and will fully be, reliant on reinsurance to back its entire program. That by itself is not terrible, but, with full reliance on reinsurers, the excessive profits that the company thinks it will avail itself of, in reality, just go to the reinsurer. Think about this: If the reinsurer is taking all the risk, why would Berkshire Hathaway or Lloyds of London (two of the reinsuring entities for Lemonade) not want to profit from the transaction? These excess underwriting profits will simply transfer from insurer to reinsurer. My prediction is that the charitable donations will, in most years, be nonexistent or minuscule in comparison with premiums paid.

My second issue with the charity angle is that I don’t think it will bring the alignment of interest that Lemonade expects. One reason is that, if I am correct about the excess profits not materializing, then just the intermittent scheduling of charitable givings makes the whole exercise uninteresting to the insured, in my opinion. If Lemonade can’t provide a significant charitable donation in most years, the alignment will lose its appeal simply because the policyholders won’t be able to hang their hats on it. Perhaps worse, the charity angle may lose effectiveness because Lemonade is also marketing that it pays claims “super fast.”  Super fast claims handling (which, on Lemonade’s website, the company touts as a check in minutes), invites fraud. I think there is a major conflict of the business model. If your marketing message is that you can get a claims check in a few minutes without having an adjuster or claims rep work the claim, then your message is music to those upon whom the charitable message will have no impact. An an insurance buyer and seller, I know that out of super low prices, super fast claims handling and excess profits to charities, I can only choose one of those angles. More than one seems difficult. Getting all three strikes me as impossible.

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A broker by any other name…

Lemonade is a broker by another name. Another of Lemonade’s selling points is that insurers have a conflict of interest because they make money by denying claims. Lemonade purports to have absolved itself of this conflict by not actively acting like an insurer. Here’s how:

Lemonade is actually two companies. It is a risk-bearing insurance company AND a brokerage firm. When you buy a policy from Lemonade, the 20% fee goes immediately to the brokerage firm. The remaining 80% stays with the insurer. The paper on which the insurer is based is a B-corporation, which essentially makes it a non-profit. So it is the brokerage part of the business that is the money maker. That is the entity that secured all that seed-funding. Sequoia Capital knows a thing or two about making sound investments. It doesn’t do non-profits. And once the fee from the premiums the policyholder pays gets swept into the Lemonade’s brokerage company, it will not be used to pay claims, at all… ever. It is income, free of insurance risk. If the insuring entity ever goes insolvent, all the fees will be protected.

There is nothing wrong with this. The model has already been used successfully by other insurers. But, by acting as a broker, Lemonade has shifted its risk from the risk of loss or damage of the client toward that of a trusted adviser that only has one product to sell and gets a 20% commission for selling that one product. What if its product is NOT the best choice for the client? Will Maya the bot steer the buyer elsewhere like a traditional agent would? No. How forcefully will Maya point out all the flaws and gaps of Lemonade’s ISO style homeowners policy? Will Maya give direction to the insured about the flood or earthquake policy the client really should have but can’t buy through Lemonade? Somehow, I can’t match the hype and excitement of seeing a broker selling an average product, even if it’s sold via a robot.

See also: Why I’m Betting on Lemonade  

Lastly, I want to challenge the major premise of Lemonade — that insurers make money by denying claims. As a professional in the business for 20 years, I find that this is the one selling point that Lemonade and its marketing keeps touting that upsets me the most. It upsets me because it isn’t true. In fact, I have seen the opposite. I have seen emails or communications from senior executives to staff adjusters onsite during a natural disaster that flat out instructed adjusters to move quickly, be fair and, if there is any doubt about the damage, settle IN FAVOR of the policyholder. I am not naive enough to believe insurers never play fast or loose with their claims handling, but, by and large, insurers pay their claims. In the property area in which Lemonade competes, those policies it sells are legal contracts. Many a court battle has been fought to word the contract so that claims can be settled quickly and fairly. Lemonade is implying that it will be different; it is almost implying that it won’t deny claims. Are there really claims that insurers have denied (and acknowledged via the court system) that Lemonade would not have denied? I seriously doubt it.

Look, I like new things. You like new things. Lemonade is the new thing on the 300-year-old block. But the shiny new aspects that Lemonade is bringing to the table don’t appear to be worthy of the hype, in my opinion. I give them an “A” for effort in maximizing the hype to drive attention and sales. But insurance is all about the long game. The real key performance indicators (KPIs) are retention, combined ratios and customer satisfaction. Those will take years to sort out. Is Lemonade truly in it for the customer; does it really want to revolutionize the business model; or is the exit strategy already in place?

The world is watching. I hope it succeeds.

Why Exactly Does Big Data Matter?

Unless you’ve been living under a rock for the last few years you’ve heard a LOT about big data. But if you’re like most insurance professionals, you didn’t go to school for computer science, and even though it sounds very cool you really haven’t gotten your head around a simple question:


What the heck is big data? And how will it affect insurance?

For the last several years, the world has been creating more data than it ever had in the past. Some call it the digital exhaust: Everything we do leaves a digital trail, and with a smartphone in every pocket, a laptop in every backpack and near-universal access to giant clusters of computers in the cloud, the sheer amount of data we are able to collect on everyone and everything has grown exponentially. Data grew to such large quantities that it no longer fit in the memories computers use for processing it, so whole new tools had to be designed to handle it. We started creating and saving so much data that there was a qualitative change, and all of a sudden we became able to extract new insights and create new value due to the large scale of the amount of data that we can access. Things are now possible that simply could not have been done at a smaller scale.

One of the key changes that happened is that we started recording everything in a digital rather than analog way (computers instead of paper). As recently as the year 2000, only a quarter of all of the world’s information was digital. By 2007, more than 93% of the world’s information is now in digital format and can be much more easily read and analyzed by computerized tools! By 2013, more than 98% was digital.


Why Is Big Data a Big Deal for Insurance?

At its very core, insurance has always been an information business. We don’t make widgets. We help people and businesses manage their risks and help pay for the losses when they happen, and all of this is based on information, not on arranging physical atoms in any way. It’s literally a pure information business.

See also: What Comes After Big Data?  

For centuries, when faced with very large numbers of data points, society has depended on using samples. This applies even more to the insurance industry. Think back to CPCU 500; our ENTIRE business is based on the law of large numbers and on making statistically valid predictions about risk. (If you haven’t done your CPCU, stop reading this article right here and go get started on it! Here’s why, here’s how.) Sampling, and the law of large numbers, was necessary because we lived in a world of limited information, an analog world where most things didn’t get recorded in an easy-to-analyze way. We are now in a different world, in the digital era, and now, thanks to big data, we are approaching a world in which we won’t need to use samples anymore; we’ll have ALL the data. This will have huge implications for our industry.


Historically, we had to work with samples because it was very difficult or impossible to collect all of the data, and because we didn’t have tools that could work with gigantic sets of data. Having ALL the data related to something, instead of a sample of it, allows us to see much more detail. For example: In the old analog world, our actuaries figured out that 16- to 19-year-old drivers were more likely to have an auto accident, and this became a key part of how we price auto insurance. In the new digital world of big data, we might be able to analyze every second a young person has ever driven and make a personalized price for his very own level of risk! That rate will be much more accurate because it is based not on some of the general data (the accidents had by insured 16- to 19-year-olds) but rather by ALL the specific data (every second of driving this person has ever done).

By its very definition, actuarial science, which our entire business is built on, is “the discipline that applies mathematics and statistical methods to assess risk,” and one of the aims of statistics is to “confirm the richest findings using the smallest amount of data.” In other words, our entire business is built on making predictions using limited data. In a world of unlimited data, we will have to quickly become world class at analyzing and reacting to ALL the data, or we might be beat at our own game by those who do.

The Why Doesn’t Matter, Only the What

In the old world of small data, society spent a lot of resources trying to figure out the why behind things. Scientific and statistical studies started with a hypothesis, a prediction of how things worked, and then tested the available sample of data to see if that hypothesis was correct. If it wasn’t, then the hypothesis was modified and tried again. Most data was collected for a specific purpose, and it was very difficult to use it for other purposes without collecting a new sample. Today, with so much data around and more to come, hypotheses are no longer crucial. All that is needed is analysis for correlations.

Before big data, because of the more limited amount of computer power we had, most analysis was for linear relationships (this causes that); with the new tools of big data analysis and the faster computers available today, we can find more complicated non-linear relationships (a, b, c, d, e, f, g independently predict x a little bit but together they predict x very accurately).


It doesn’t matter that your system doesn’t know all the variables that go into a problem, only that it can predict the result. For example, Google has used big data to predict flu outbreaks faster than the Centers for Disease Control and Prevention (CDC) by letting the computer figure out which searches correlate with flu outbreaks. It doesn’t matter whether those people know that what they’re searching about is the flu, just that they’re searching on it and that when those hundreds of identified search terms happen in one area there’s a very good chance that area is experiencing a flu outbreak. In the new world of big data, the why something happens doesn’t matter, it only matters that we are now able to find the hidden patterns and find it or predict it. Society will need to shed some of its obsession for causality in exchange for simple correlations.

One example of how an insurance company is trying to use big data to improve its underwriting is Aviva, which studied the idea of using credit report and marketing data to underwrite some life insurance applicants instead of the traditional blood and urine lab analysis. The idea is to identify applicants with higher risk of lifestyle diseases like high blood pressure, diabetes and even depression. The method uses lifestyle data that includes hundreds of variables such as hobbies, the websites people visit and the amount of television they watch, as well as estimates of their income. The traditional lab tests cost $125 per person while this new approach can be as cheap as $5.  This is an example of a correlational relationship being valuable and more efficient than relying on a causal relationship for prediction of an outcome.

The More Data We Have, the Less Exact It Needs to Be

In the old world of small data, statisticians and data analysts were trained to clean out outliers and try to get data that was as clean as possible. With big data, we are looking at vastly more data, which means that we can get away with less precision. It’s a tradeoff; with less error from sampling, we can accept more measurement error. The old tools (spreadsheets, relational databases, SQL, business intelligence tools, etc) were created to work on exact data; the new tools are designed to work with large quantities of imperfect data. The need for perfect data was a side effect of the limited tools we used to manage small data.

See also: Eating the Big Data Elephant  

Here’s a great example of why we can now get away with less exact data: Suppose we need to measure the temperature in a vineyard. If we only have one temperature sensor for the whole plot of land, we must make sure it’s accurate and working at all times: no messiness allowed. In contrast, if we have sensors for every one of hundreds of vines, we can use cheaper, less sophisticated sensors (as long as they don’t introduce a systematic bias). Any particular reading may be incorrect, but the aggregate of many readings will provide a more comprehensive picture.

Data Is No Longer Stale After Its Original Use

One of the very limiting features of the old world of data is that once a dataset was built for a particular use, it was very difficult to use it for another, so you have to know what you’re looking for before collecting the data.  Because you were collecting a sample of data and inputting it into a very structured format for future analysis, getting the right pieces of information was of paramount importance.

In the new world of big data, all data becomes a new raw material to create value in new and creative ways, most of which were impossible in the old world. Because we are collecting data on everything, and our tools are more sophisticated in ability to arrange and rearrange that data, we are more able to use the information in a variety of ways.

Think about it; that telematics device on your car collects a TON of data. Think about the data your smartphone collects about your habits each day. Every time you search on Google, it’s recording not only what you search for but even the exact amount your mouse spent at different parts of the screen. Soon, we’ll even be able to track your eyes through the webcam when you visit our website. There’s just a TON of data out there that we’ll now be able to analyze and learn about our customers.

Being Free of Sampling Will Allow Us to Know More

Sampling quickly stops being useful when you want to drill deeper, to take a close look at some intriguing subcategory of the data. One of the key benefits of being able to collect ALL of the data about something is that we can dig further into the data and ask it fresh questions that we hadn’t even thought of when we started collecting the data. In the old paradigm of sampling, one would collect only what was directly asked for. If you noticed a pattern in that sample but needed something to explain or verify the pattern that you had not thought to ask for ahead of time, you would need to re-sample and get additional data to confirm what you found.

Data No Longer Needs to Be Structured

Traditionally, the way data was stored in spreadsheets and databases was structured, meaning that each field could fit a very specific type of data; a phone number field, for example, could only hold a 10-digit number. The problem is that only around 5% of all digital data in the world is structured in a form that neatly fits into a spreadsheet or database. That means we had no easy way to analyze the other 95%! Pretty much all data had to be cleaned up before analysis, which made everything smaller and more expensive.

In the new world of big data, new tools such as Hadoop are able to analyze unstructured data in all shapes and sizes, 100% of data instead of just 5%. The tools can even analyze things like books, journals, metadata (data about data), audio, video and much more. Imagine being able to include every second of conversation digitally recorded from your call centers along with all your other data and analyze it all to find trends! This is one of the most powerful features of big data, and it is already being used in many call centers.


Messier Data Will Help Us Insure Messier Things

Big data’s ability to help us analyze messy data could help us insure harder-to-insure things. For example, ZestFinance, a company founded by a former chief information officer at Google, built technology that helps lenders underwrite small, short-term loans to people who have bad credit scores. Turns out traditional credit scoring is based on a few factors, while ZestFinance uses a huge amount of variables using big data, and it produces solid results; in 2012, the company’s loan default rate was a third lower than the industry’s.

Big data might allow us to better underwrite risks for which we don’t have very good data, such as people who can’t get a driver’s license or commercial risks that currently can only be insured in the surplus lines market. Imagine all of the services, microinsurance and other innovations we’ll be able to develop.

From Indemnification to Risk Prevention

One of the techniques used with big data is predictive analytics, and pretty much every carrier is experimenting with it.

The technique is being used to prevent big mechanical or structural failures: placing sensors on machinery, motors or infrastructure like bridges makes it possible to monitor the data patterns they give off, such as heat, vibration, stress and sound, and to detect changes that may indicate problems ahead.

The underlying concept is that when things break down, they generally don’t do so all at once, but gradually over time. If we have sensor data and correlational analysis, we can probably figure out that something is about to break before it actually does. This can allow us to prevent claims from ever happening, thus moving from insurance as a loss-paying service to being a risk-prevention partner.

See also: Forget Big Data — Focus on Small Data  

Acknowledgement: Much of this article comes from Big Data: A Revolution That Will Transform How We Live, Work, and Think. Yes, you should read it! Yes, we get a small commission if you buy it using that link, and it helps us run and improve InsNerds.

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This article originally published on InsNerds.com.

Lemonade: A Whole New Paradigm

We’ll admit it; we were caught asleep at the wheel on this one. We had heard of Lemonade a few months ago and how it successfully raised $13 million in investor funding, but given that there are 500-plus other insurtech startups out there, we didn’t pay that close attention. Then on Sept. 21, it opened for business. Both Carly and Tony were in Hawaii for the CPCU Society Annual Meeting and entirely too busy drinking Mai Tais, err, I mean, working the event to even notice that Lemonade went live. We’re back in the lower 48 now, back at our day jobs and, after almost a month working on catching up, it just recently hit us that Lemonade is a BIG deal. A REALLY BIG DEAL.

A lot of digital ink has already been spilled at ITL with at least three great articles about Lemonade, but we still needed to give our own point of view. As Insurance Nerds, we are completely geeked out, and, as millennials, we can’t help but want to move our own insurance to Lemonade and are actively wondering when the company will expand to Pennsylvania and Georgia, where we live.

Lemonade is not just another insurtech startup. It is an actual, mobile-first, legacy-system-free, licensed carrier offering P2P (peer-to-peer) insurance to delighted customers in the state of New York through a seemingly magical iPhone and Android app. To start understanding what this is all about, you must watch the three short videos in this article:

That first video looks like a VERY snazzy proof of concept, and it almost makes you wonder if this thing will ever go live or if it will simply be vaporware. But it’s already live! Maya, the young lady who asks you in plain English a few simple questions to “get you some great insurance” is not a call center rep in NYC, Des Moines or even in Delhi; she’s an artificial intelligence chat bot. This technology is so new that it was unknown before 2016 and is only starting to be experimented with in the high-tech industry, and it’s live on Lemonade, helping people buy homeowner’s and renter’s insurance.

Notice how, as the user fills in his address, the system automatically pulls potential matching addresses, and once it has a full match it automatically displays a map to confirm. Then it asks whether you have roommates, a fire alarm or a burglar alarm, if you answer yes to any of those, the system knows what else it needs to ask.

See also: Lemonade: Insurance Is Changed Forever  

It immediately pulls data from databases, analyzes all the underwriting characteristics it needs and offers an incredibly cheap policy. Oh, and if you already have a policy, Lemonade will even cancel it for you and get you a refund! Coverages are shown in a simple, graphical illustration, and just tapping on a darkened icon adds that coverage to your quote immediately. Enter your credit card info, and done. The whole video takes about 40 seconds to get to a bound policy. In real life, it probably takes about 90 seconds. You even get to sign your contract right on your touchscreen. It’s downright magical.

The ease of use and freedom from legacy systems by themselves are probably enough to get 70% of millennials (and many Xers and Boomers) to leave their existing insurers and go with Lemonade instead! As Michael Tempany explains, no existing insurer can produce an app like this because of our legacy systems, workforce and processes. It’s simply not possible. He even argues that “the only solution for traditional insurers wanting to compete with Lemonade is to start from scratch. In short, they need to create a company or subsidiary unencumbered by legacy systems, workforce constraints and intermediaries.”

But that’s just the beginning. Rick Huckstep of the Digital Insurer is absolutely right that “This is what insurance is meant to be: mutuality in the pooling of shared risk.” He argues that “the industry has lost its way with the evolution of mass scale personal lines in the 20th century. The profit motive has gotten in the way of trust; the insured and the insurer are both chasing the same dollars. And now, their interests are no longer mutual but are misaligned. The insured wants a helping hand and to be ‘made whole.’ The insurer wants to satisfy its duty to shareholders.” This is true even with mutual companies with no shareholders; the existing model of every other insurance carrier puts the customer’s interests against the carriers interests at least to some extent. While Lemonade is a full-on risk-bearing carrier, it has eliminated the existing dilemma of every other carrier: Lemonade takes a 20% cut of the premium as a fee, and that’s it. If you have a loss, you get paid for it (immediately and without questions), and, if you don’t have losses, and your policy produces a profit, it gets donated to the charity of your choice.

The claims process is also amazing. You open the app, tell it you had a claim, answer a couple of questions, sign on the screen, record a quick video explaining what happened and get paid, on the spot, immediately.

Oh, and by the way, Lemonade is A-rated and reinsured by Lloyds of London.

The second video explains the science that makes it all work and has a great line: “Insurance that is a social good, not a necessary evil.” This tag line is going to be killer awesome. Also, very interesting that Lemonade explicitly explains what Geico’s “15 minutes can save you 15% or more” line has always meant: There are no brokers or agents involved.

Nobody explains Lemonade better than Dan Ariely, behavioral economics expert, Duke professor and Lemonade’s chief behavioral officer. “In the very structure of the old insurance industry, every dollar your insurer pays you is a dollar less for their profits. So when something bad happens to you, their interests are directly conflicted with yours. You’re fighting over the same coin. Basically if you tried to create a system to bring out the worst in people, you would end up with one that looks a lot like the current insurance industry.”

See also: It’s Time for Some Lemonade  

And a fantastic commercial making it all crystal clear to the customer:

Make no mistake, Lemonade will expand beyond New York, and we’d expect it to be in all 50 states within the next five to seven years at the very latest, and it will expand beyond renters and homeowners.

A lot of questions remain open: Will Lemonade have decent underwriting results? Will the underwriting results even matter given the fee-based structure? Will the company be able to come up with an equally genius model for auto insurance? How about commercial insurance?

A couple of things are absolutely certain: Millennials have no issue leaving legacy insurance companies and will be thrilled to try this out; and our industry has changed forever. Lemonade is what we will get compared with from now on. How will your company compete?

Want to support InsNerds?

InsNerds is free, it’s a labor of love and it takes a lot of time. We have a ton of fun doing it, and we would really appreciate your support in keeping it running. If you’ve been helped by one of our articles, if we’ve helped you grow in your career, if you agree that our content is improving the insurance industry and that we are unique in what we do, please consider donating. We’ll use your donation to deliver even more career- and industry-changing content, and to spread the word about that content far and wide in the Insurance Industry.