Tag Archives: behavioral economics

A Behavioral Science Scandal

A much-cited claim about how behavioral science can guide insurance has been exposed as fraudulent. The claim was made most prominently by Dan Ariely, a best-selling author and pioneer in the field of behavioral economics, who was Lemonade’s chief behavioral officer from 2015 through 2020. But the claim turns out to be based on fabricated data.

The claim was based on a study that Ariely and four co-authors published in 2012 in the Proceedings of the National Academy of Sciences. Ariely then cited the study at length in his 2013 book, The Honest Truth About Dishonesty, continuing his string of best-sellers that began with Predictably Irrational in 2008.

The study reported that people would be more honest if you asked them to promise to be truthful before providing information rather than having them provide the information and then certify that what they reported was accurate. In other words, you disrupt the usual process, in which people supply information and then just have to rationalize a bit of cheating afterward.

The study said it drew on nearly 13,500 customers of an auto insurer, half of whom signed a claim of truthfulness at the top of an application and half of whom signed at the bottom. The study reported that those who signed at the bottom said they drove about 10% fewer miles than those who signed at the top — and, of course, paid lower premiums as a result.

The conclusion was so appealing that the paper was cited more than 400 times in academic publications. Many organizations, including the IRS, began having at least some people attest to their honesty at the start of the process. I certainly fell for the idea. I couldn’t even tell you how many times I’ve cited the study.

More importantly, from the standpoint of insurance, Lemonade incorporated behavioral economics ideas into its initial business model that at least rhymed with the study’s conclusion, even if they didn’t specifically build on it. Lemonade took a set share of premium, to demonstrate to customers that it had no incentive to deny claims. Lemonade also said it would donate to specified causes if claims were below a set level — encouraging clients to minimize claims.

Other insurers surely built on the study, especially given Lemonade’s success (even though its use of behavioral economics seems to have mattered far less than its sleek customer experience and slick marketing).

The plot began to unravel as others tried and failed to duplicate the study’s results. Eventually, the authors published two retractions in 2020, in the Proceedings of the National Academy of Sciences and in Scientific American.

As part of the retractions, the authors published the original data — which is how it became apparent that the study was based on more than an honest mistake; the data had been manufactured.

Sleuths at Data Colada spotted what, in retrospect, were obvious problems. The data didn’t follow a Bell curve, as you’d expect. There weren’t some people who drove a little, some who drove a lot and a whole bunch who fell in the middle. Every division based on mileage had almost exactly the same number of people in it, from low mileage through high mileage, and not a single person out of nearly 13,500 drove more than 50,000 miles in a year. In addition, the mileage that people supposedly reported was accurate down to the mile, even though actual people would round off the numbers. The precision was a clear indication that a random number generator was being used.

There was more, too. In any case, when confronted with the Data Colada analysis, all the authors quickly agreed that the data had to have been faked.

At the moment, the focus seems to be on figuring out who to blame for the fraud. I confess to some personal confusion. I spent time with Ariely at a small, three-day conference where we both spoke in 2008 and found him to be extremely smart and thoroughly engaging, so I’d like to think that he wasn’t involved. (He has vigorously denied faking any data.) But he has said he was the only one of the five authors who dealt directly with the insurer that provided the data, and it’s not at all clear to me what the insurer would gain by faking the results. (While the company wasn’t initially named, it’s since been identified as The Hartford.) I’m also confused because he cited the study to me, personally, at that gathering in 2008 but didn’t publish the results for four years. Why wait so long with such an interesting result? (He’s on the record as having cited the study in a talk at Google in 2008, so he wasn’t just talking to me, either.)

But I’m more concerned with the broader point, which I think is this:

Behavioral economics is still a powerful tool for insurers despite this embarrassing fraud. We may like to think of customers as completely rational, but they aren’t, and we need to understand them as they are, not as we’d like them to be. That doesn’t mean accepting broad pronouncements about behavior, even from charismatic experts like Ariely. Understanding behavior means engaging with our own customers deeply, testing how they react to various actions on our part and then tailoring our interactions with them, foibles and all, to maximize benefits both for them and for us.

I realize that this is two weeks in a row where I’ve take a contrary view about technologies and techniques that are huge benefits to the insurance industry — last week’s was When AI Doesn’t Work. I’m sure these two Six Things commentaries aren’t the start of a trend. But I don’t believe that trees grow to the sky, so I don’t see the point in pretending they might. When there’s a problem, I’ll always try to point it out.

Cheers,

Paul

COVID-19 Risk and Buyers’ Psychology

Despite all the attention devoted to the continuing devastation from COVID-19, compliance with mitigation measures is not turning out to be universal. Even public officials have been bending the rules. Indeed, a recent study from the U.K.-based behavioral science consultancy Dectech found that nearly a third of those surveyed had spent time with someone outside of their household despite restrictions on such socializing.

Similarly, many families are underinsured, suggesting that perhaps they do not see the value of such financial protection, or do not understand their risk in not having it.

Is the problem that people just don’t understand the risks of this pandemic, or is the issue with risk in general?

A handful of studies published since the summer have examined the psychology of how the public perceives the pandemic’s risks. What can these results tell us about the public’s perception of COVID-19 risk, and how can this information help insurers understand consumer mindsets and needs?

Understanding the threat of COVID-19

When people understand that a reasonable threat exists they will generally be more likely to take actions to avoid it. This was shown to be the case during 2014’s avian flu epidemic, and COVID-19 research has consistently been telling a similar story — the larger the threat people feel, the more likely they are to take protective measures such as washing hands, wearing masks, social distancing and even panic shopping.

But the bigger challenge may well be the public’s sense of the threat in the first place. In one U.S. study, half of the respondents substantially underestimated their risk of dying if infected. Perhaps more worryingly, older respondents and individuals with underlying health conditions also underestimated the virus’s potential threat despite understanding that they were at higher risk than the population average.

See also: How to Leverage Behavioral Science

A well-established finding from behavioral economics is that humans are often poor at understanding their own risk objectively. For example, a majority of people implausibly believe they are better than average drivers, and many also believe their chances of avoiding cancer are better than other people’s, despite no objective basis for the belief. This comparative optimism — the belief that negative events are more likely to happen to others — might also explain how people are perceiving the risk of COVID-19. A study early in the current pandemic on perceived risk and self-reported personal behavior conducted by researchers at the California Institute of Technology found that participants perceived a high level of risk to the general population but tended to rate themselves as being at lower risk than the average person. This perception was not influenced by whether the respondents were actually at lower risk than average.

This finding, replicated by a group of researchers from the U.K., U.S., Europe and Australia using the U.K. data, also suggests that, despite the inescapable factual information available about COVID-19, people still believe “it won’t happen to me.”

Perhaps most interesting is the finding that factors beyond objective facts influence COVID-19 risk perception. According to a study from the University of Cambridge of almost 7,000 individuals in 10 different countries, although participants had relatively high threat perception, men, who are statistically far more likely to die from COVID-19, were less likely to report feeling threatened by the pandemic than women. The researchers also found that risk perception can be amplified by how a person’s friends and family are perceiving the risk and by their having existing prosocial values (values that promote behavior benefiting society as a whole). The Cambridge study also showed that the most powerful predictor of COVID-19 risk perception was direct personal experience with the disease.

Clearly, despite all the objective information we have at our disposal, visceral experiences — i.e., concrete evidence obtained and interpreted through our own senses, emotions and social interactions — and existing attitudes are powerful drivers of people’s reactions to external threats.

Is risk knowledge or a feeling?

These studies paint a picture of reactions to the COVID-19 pandemic that are consistent with psychologists’ view of risk perception: Perceiving a threat may push people to take action, but perceiving a threat accurately is not guaranteed. While perception of COVID-19 risk is relatively high on the scales used in the studies, it is still underestimated and subject to biases such as over-optimism and social influence, and context such as pre-existing worldview, direct personal experience and gender identity.

Risk, to humans, is subjective — fundamentally about what one is feeling. Fear, disgust and the prospect of guilt and regret turn people away from danger, and, when not sure how to respond, humans look to other people’s behavior and their own expectations for answers. This is how people experience the world first-hand, and this experience, rather than objective facts, frequently dominates judgments and decisions.

To understand the physical effects of COVID-19, seeing someone in a hospital bed who is either intubated or on mechanical ventilation is likely to have a far more powerful visceral effect on a person than case numbers. People can empathize with the horror of the situation and grasp the risk in a way that knowledge of the numbers just cannot achieve.

Perhaps this was the idea behind one U.K. city’s campaign to promote compliance with COVID-19 restrictions. Its shocking slogan, “Don’t Kill Grandma,” sought to elicit an emotional response to promote a personal understanding of COVID-19’s risks rather than presenting statistics and then expecting a highly rational and analytical response.

Communicating to inspire protective action

Should communicators use shock tactics such as fear appeals to help people gain an appropriate understanding of risk? One of the most widely discussed uses of fear appeals, i.e., tactics designed to elicit emotional discomfort and motivate particular responses, are the campaigns to push smoking cessation. Cigarette packets in the U.S. are required to display warning messages, and in the U.K. must have both warning language and harrowing images of the physical effects of smoking, in the hopes that user exposure to these horrifying images may promote behavior change.

Fear appeals can be effective, but there are serious caveats. Overly shocking communications can make people disengage and ignore or react defensively to the intended message altogether. Finding the right balance of engaging emotions while sustaining people’s attention is vital for risk communicators. In particular, being able to show that a risk is personally relevant and that one’s own actions can minimize the danger of a particular risk are key elements of making fear appeal messages work.

Insurance marketers face a similar challenge in persuading consumers to protect their assets and finances. It can be off-putting to communicate risk by scaring potential customers. Also, the industry is dominated by a highly objective and numbers-based understanding of risk, but, as the COVID-19 research shows, people do not usually think of risk statistically.

See also: COVID and Power of Personal Connections

Insurers can learn from the COVID-19 research that, while it is difficult for people to appreciate intangible risks, communicating risk in terms of lived experiences, whether their own or that of others, might be a powerful tactic. From this perspective, it is unsurprising that insurance sales increase in response to emotively striking but objectively unimportant events, such as widely reported floods leading to increased insurance demand in unaffected areas, and the death of Kobe Bryant generating a spike in life insurance sales. For insurers, this might mean finding ways to approach customers at moments when risk events are salient and emotionally resonant — when such events and people’s interactions with the information are spurring thinking about caring for their families, health and homes. These could be important opportunities for demonstrating the value of insurance products.

COVID-19 communications and insurance marketing share a conundrum. Objective risk for humans is often intangible. Insurers seek to understand and communicate health and financial risk objectively, but also need to acknowledge that customers might not receive that objective message. Exposing the risk by creating or exploring feelings that resonate with lived experience, identity and expectations are going to count for far more than just bare facts.

7 Biases Customers Have About Risks

Although risk is at the center of insurance, there is a question that is not asked enough: How do we measure risks?

When you ask an actuary to measure the likelihood of occurrence for a specific risk in a year, (s)he uses models based on various data sets. However, none of us use actuarial models in our daily life to measure risk (including actuaries). We simply tap our memories about that risk. If memories are vivid, we think that risk is higher.

Using memories does not sound like the best way to measure a risk, so why are we so simple and superficial in our daily lives?

Contrary to popular belief, our brains often mislead us, and the problems also affect hard missions like measuring the probability of an event occurrence. Here are seven cognitive bias and shortcuts that lead us to make wrong decisions about risks.

1. Availability Heuristic

The stronger our memories, the stronger our emotions. While measuring the probability of a risk, we check our memories based on:

  • Recent events
  • Frequent events
  • Tragic events
  • Unexpected events

Negative events are easier to remember. It is quite possible that we exaggerate risks in such cases. For this reason, car insurance, which has high loss frequency, is one of the biggest lines.

2. Myopia

No matter how healthy our eyes are, our brains have trouble seeing the distant future. Because our most basic instant is survival, we focus too much on today and do not pay attention to risks in the future.

Even if we do not save enough today for retirement, we do not think that we will face income problems. This explains why people tend to buy mobile phones instead of life insurance.

3. Amnesia

Even as we exaggerate recent events, we forget them quickly. Insurance penetration increases rapidly after a natural disaster but declines to the previous level in few years.

After Hurricane Katrina, the number of flood insurance policies in the U.S. grew by 14%, which is three to four times the growth rates observed in previous years. Policy numbers dropped to pre-Katrina levels in just three years.

4. Overconfidence

Another bias is the tendency to exaggerate our talent and performance. Self-confidence is usually a good thing, but having too much of it can cause us to underestimate the risks. 

Among car drivers in the U.S., 90% said they were better than average.

5. Illusion of Control

Thinking we have full control in our lives can make us insensitive to risks. There are people who afraid to travel by plane on one side, and people who drive motorcycles on the other…. Sometimes one person can belong to both groups.

Being injured or dying while riding a motorcycle is much more likely than an airplane crash, but we might take that risk because we have the illusion of control.

See also: COVID-19: Actuaries Now All Wrong  

6. Optimism

Being optimistic about the future is one of the most beneficial features of humankind. Based on optimism, we make long-term investments, have children and go to work every day. But when it comes to risk management, being optimistic can be misleading.

People are more balanced when considering good things and bad things in their past. But while thinking about the future we generally give weight to good things. This optimism might prevent us from seeing possible risks.

7. Black Swans

All swans were thought to be white until the Australian continent was discovered. Black swans appeared on the continent, and this term is used as a metaphor for hard-to-predict, tragic and rare events: 9/11 attacks, the 2008 economic crisis and now COVID-19.

Black swans are ignored until they happen. After thatm the effects are highly exaggerated. Finally, at some point, they are ignored again. That means today’s black swan COVID-19 is a great opportunity for the insurance industry, at least for the next 10 years, just as the terror insurance market was in the U.S. after the 9/11 attacks.

Behavioral Insurance

To provide an insurance service based on consumers’ needs, we should stop for a bit and try to understand deeply how they measure risks. As the gap increases between insurers’ and consumers’ considerations about risks, it becomes much more difficult to meet their expectations.

Behavioral economic theories can help insurers in many areas, from product development to pricing, from marketing to claim managements. It is time to meet with the “behavioral insurance” approach beyond the traditional insurance practice based on statistics and calculations.

Why Buying Insurance Is Like Dieting

Have you heard of the marshmallow test? A marshmallow is placed in front of a kindergarten child, and an offer is made; you can eat this marshmallow right now, or, if can wait for 15 minutes, you will get a second one. This experiment, which sounds quite simple, provides invaluable insights about the self-control dynamics of humans.

The experiment was conducted first in 1960, and the results have been evaluated over the years. It was found that kids who were able to hold off a long time without eating a marshmallow were more likely to have higher SAT scores. Similarly, in their adulthood, these people had a better body mass index, more self-confidence and less tendency to be addicted.

Studies also show that delaying gratification gets harder under stress and keeps getting harder, the longer you delay. If you realize that you forgot your entrance card after driving in terrible traffic in the morning, you will be defenseless against dessert at lunch.

Buying insurance is an act of delaying gratification, like retirement saving, dieting or avoiding sugar. It takes real self-control to spend your money on a product that you don’t enjoy when it is not mandatory. Delaying today’s pleasure for a possible future benefit, buying car insurance instead of a new phone….

So, if buying insurance is an act of delaying gratification, how can you help your customers on this issue?

See also: Is Buying Insurance Like Ordering Food?  

Develop Desired Products

Perhaps be a supporter on good days rather than just compensate for the bad days? Why don’t life insurance companies try to make their customers’ life happier? At least they could send them a cake on customers’ birthdays.

Enriching an insurance product with benefits that can be used immediately can also help customers to delay gratification. Offering free car washing service once a month to your car insurance customers will definitely make them more satisfied with their purchase.

Ease Purchasing

Did you know that we suffer physical pain when making any payment? Neurofinance studies show that spending money activates the areas of the brain associated with physical pain and feelings of disgust. And the activation is much more when payment is in full view. Ask your customers to pay in cash, if you want to make your customer suffer. PayPal, mobile wallets and contactless payment are much kinder solutions.

Know Your Best Customer

The best insurance customers are those people who make regular savings, eat healthily and do volunteer jobs for the community. Why? Because those people have enough self-control to delay daily pleasures. As they are aware of their responsibilities, they will be more likely to purchase insurance. They will also do their best to avoid risks. Identify this customer segment and flag them as the best customers.

Appreciate the Will

Being appreciated strengthens our will, motivating us to be more responsible. Insurance companies should appreciate their customers both emotionally and financially.

The health insurance company that appreciates customers with emails for being careful about pursuing a healthy life would increase customer satisfaction. The insurance company that gives small gifts to customers who have not any claim for years would likewise be rewarded with customer loyalty.

Knock on the Door at the Right Time

High stress leads people to instant gratification. Long-term plans are usually made in quiet moments. If you are not able to check the pulse of your customers by using a wearable device data for now, don’t worry. Just call your customer in the morning instead of evening after a busy work day. Speech emotion recognition systems are also powerful tool that should be used in call centers.

See also: The Behavioral Science on Buying Insurance  

Automate Decisions

Delaying gratification is a real struggle when you do it the first time. We struggle mentally, but it becomes easier the next time, and finally it turns into a kind of habit. Our brain automates the action, so we don’t have to spend our self-control power.

It is difficult to get consumers to adopt the insurance purchasing habit, so there is bloody competition for the customers who already have this habit. Customer acquisition is silver, but retention is golden.

Insurers rely on insurtechs for the technological transformation of the industry. But first the industry needs a customer-oriented transformation. This may be possible by understanding the emotional and behavioral tendencies of consumers.

Thanks to Walter Mischel, who inspired this article with research for more than 50 years on delay of gratification and self-control.

The Behavioral Science on Buying Insurance

Why do people buy insurance, when they could spend their money on dozens of other excellent products and services? A classical answer would be, “to be safe against risks.” Then, why do some people spend thousands of dollars on insurance products while others don’t spend a penny? Doesn’t everyone want to be safe against risks?

To find real answers, it is necessary to take a closer look at the motivations of people.

Deciding whether to purchase insurance is not easy. Consumers usually don’t get any financial benefit in return for the premium they pay. However, in addition to financial benefits, insurance products offer moral benefits such as peace of mind and a feeling of safety. So the benefit of insurance from the customer’s view can be formulated as (risk expectation x coverage) + (moral benefit).

Thus, the motivation of customers to buy insurance depends on two main indicators: risk expectation and risk sensitivity. Risk expectation determines the expected financial value of insurance. Risk sensitivity shows the concerns of customers, so it directly affects moral benefit.

Who Wants Pizza?

Being cautious is the main instinct behind insurance purchases. Of two consumers who face the same risks, the more cautious one is more likely to buy insurance. Exercising regularly to be safe against chronic illness resembles buying home insurance to be safe against fire, theft and earthquake. Preferring fast food instead of healthy food is like buying a great TV instead of auto insurance. Purchasing an insurance product is like dieting; costs arise immediately, but benefits are achieved later.

See also: Behavioral Economics Show Details Matter  

Generally, competition among insurance companies is thought to depend on prices, brand awareness and customer service. In fact, competition is much broader. Purchasing decisions cross product categories; people buy home insurance or… shoes.

Insurance companies should develop strategies to convince more people to buy insurance, not those shoes.

Fans of Insurance

The key point is: People make risk assessments based on their personal experiences, not actuarial tables. Therefore, insurance companies need to focus on the feelings and emotions of consumers and not just working on statistics.

People exaggerate the likelihood of risk occurrence under certain circumstances, which increases their sensitivity of risk. People will be more likely to buy insurance even if all other factors are the same.

Some opportunities:

  • High Loss Frequency: Consumer tend to demand insurance where loss frequency is high even if severity is not so great. A house fire is a disaster, but a car accident is more likely. This explains why automobile insurance is one of the biggest lines.
  • Customers With Claim: Risk sensitivity increases cumulatively. If you faced a negative situation recently, you look at the world more pessimistically. It would be a good strategy to offer home insurance to customers who made auto insurance claims the previous month.
  • Highlighted Risks: If a risk is highlighted in public, people exaggerate the possibility even if risk occurrence is not high. Theft news broadcast on TV for a week would increase people’s tendency to buy home insurance policy for a time.
  • After Tragic Events: Right after tragic events like earthquake, flood and terror attacks, people think they will happen again soon. It makes no sense to buy insurance after an earthquake because, statistically, a new earthquake is not to be expected soon, but sales rise.
  • Uncertainty and Fear: Important experiences like having a baby or suffering a heart attack make an impact on people’s view of life. There will be a significant increase in risk sensitivity. Therefore, it would be a good strategy to offer life insurance bundled with family health insurance to a customer who had a baby recently.

Homework for Insurers

On the behavioral approach side, there are some basic steps to follow to grow the whole insurance market;

  • Being Micro: Insurance products are not only complex but also are too focused on macro risks. In fact, the daily risks of our lives are more micro and ordinary. Why are major risks like fire or flood pointed out in home insurance products rather than damage to electronic devices or accidental risks?
  • Being Visible: Insurance companies have a natural advantage because they pay thousand of claims every single day to people and touch their lives. Creating positive stories from negative events can bring life to insurance products.
  • Being Informative: Insurers should undertake the mission of “warning against risks,” in addition to providing financial coverage. The insurance company that interacts with customers regularly and improves their risk awareness would build brand trust.
  • Being Protective: Getting share from competitors is becoming tougher everyday. Insurance companies are not only competing with new-generation insurtechs but also with technology, entertainment and consumer goods companies. The most rational and cost-effective strategy could be retaining the existing customer portfolio.

See also: Machine Learning – Art or Science?  

New-generation economic theories based on behavioral science provide important insights about customers’ decision mechanisms. Many organizations, from e-commerce companies to government institutions, are profiting from the insights. For insurance companies, a good place to state would be understanding that customers are not robots who just want the most coverage at the cheapest price.

Thanks to Daniel Kahneman and Richard Thaler for inspiring this article with their behavioral economic theories.