Tag Archives: Daniel Kahneman

Our Big Problem With ‘Noise’

A new book co-written by behavioral economist extraordinaire Daniel Kahneman points out a major problem that numerous industries, including insurance, only sort of know they have and is surely worse than they recognize. He calls the problem “noise.”

He says insurers are very aware of potential bias based on age, race, gender, etc., especially as they evaluate algorithms driven by artificial intelligence — insurers know to look for consistent favoritism toward, say, white men. But, he says, insurers tend to gloss over the problem of inconsistency, or “noise” — the fact that people come to very different conclusions based on the same set of facts, even when bias is removed from the equation.

Kahneman, who won the Nobel Prize in Economics in 2002 and who has driven so much of the progress on behavioral economics for decades, cites a study he did in 2015 that presented a series of cases to 48 underwriters at a large insurance company. Executives predicted that there would be roughly a 10% variance between the high and low prices that the underwriters provided after assessing the risks — but the typical variance was 55%. Many variances were even more extreme. One underwriter might set an annual premium at $9,500 and another at $16,700.

The tendency is to think that the decisions balance out, but Kahneman says such wide variance suggests that the insurer is actually making two mistakes. The $9,500 quote was likely underpricing and was either leaving money on the table or was winning unprofitable business. The $16,700 might be overpricing that costs the carrier business because competitors will offer better rates.

“Wherever there is judgment, there is noise, and more of it than you think,” according to the book, “Noise: A Flaw in Human Judgment,” which Kahneman wrote with Olivier Sibony and Cass R. Sunstein and which is being released today.

The book focuses heavily on judges’ decisions on prison sentences, both because they are so consequential and because they clearly illustrate the difference between consistent bias (which many companies are becoming good at assessing) and noise (which companies tend to underestimate and thus gloss over).

A study found that a certain set of facts led judges, on average, to impose seven-year sentences. But there was an average variance of 3 1/2 years — a long time. Some of the variance relates to bias: Conservative judges tend to consistently impose longer sentences. But some is just noise. Perhaps the judge has a personal story that makes him identify more with the defendant. Perhaps the judge has had a series of cases that made her more fed up based on the crime committed. Kahneman says variance even happens based on time of day, the day of the week, the mood of the person making the decision, etc.

While he doesn’t try to quantify how much noise reduces profitability for insurers, the sheer size of the numbers involved in underwriting, designing policies, assessing claims, etc. suggests that the potential gains are enormous if decisions can be made more consistently.

Kahneman and his co-authors argue that the starting point for combatting the problem is to conduct a “noise audit.” Insurers could do the sort of test that the authors did to assess how wide the variance is among their underwriters, adjusters, agents and perhaps others, decide what the effects on profitability likely are and determine how much effort should go into reducing the noise.

The book argues that algorithms will be a big piece of the solution — while acknowledging the need to watch out for systemic bias, largely by being super careful about the reliability of the data being fed into the algorithms. Algorithms are nearly free of noise: An algorithm faced with the same information will almost always make the same decision. And, while algorithms can make bad decisions, they can always be learning, meaning that bad decisions can be gradually corrected and turned into good ones.

There will be pushback. Judges largely hated the mandatory guidelines that were established following a major study in the mid-1970s that found huge variance in sentences. Doctors object to being ordered to treat patients a certain way, even when the mandates are based on evidence.

But the evolving state of medicine could provide a solution for insurers: In the same way that AI can now offer suggestions to doctors on diagnoses and treatment — while leaving the final decision to the humans — insurers could use algorithms to generate a suggested range of actions for underwriters, adjusters and agents. The algorithms would provide some guardrails that would at least reduce the unprofitable outliers at insurance companies and would keep learning, continually narrowing the recommended range and moving the choices toward profitability

Although I rarely recommend books — even ones I’ve written — I think this book provides a road map for a relatively straightforward way to improve the accuracy of insurers’ decisions. And, once you’ve become acquainted with Kahneman’s work, you can go back and read his ground-breaking work, “Thinking, Fast and Slow,” published in 2013.

While economists long based their work on the assumption of rational consumers who maximize their utility, we all know that assumption is silly — people are far from completely rational. And Kahneman has led the way in helping us understand how people actually behave, as opposed to how we might imagine they behave or hope they behave.



P.S. Here are the six articles I’d like to highlight from the past week:

Why Open Insurance Is the Future

More are turning to “open insurance” solutions, under which insurers leverage open APIs to share data and services with third parties.

It’s Time for Next Phase of Innovation

It’s time to break through the first phase of technology adoption and move into a new phase of tech-enabled innovation.

Intersection of AI and Cyber Insurance

While AI is sure to benefit society when wielded properly, cyber carriers remain conscious that AI’s proliferation is a double-edged sword.

Achieving a ‘Logical Data Fabric’

A logical data fabric has the capacity to knit together disparate data sources in insurers’ broad, hybrid universe of data platforms.

Managing Risks for Hydrogen Industry

There is, rightly, enthusiasm around hydrogen solutions for a low-carbon economy, but projects involve complex industrial and energy risks.

The Broad Reality of Diversity

As people return to the workforce, candidates with the potential to revolutionize our industry may present themselves.

How Basis for Buying Is Changing (Part 2)

How fast is too fast in insurance?

Most insurers would probably say that the recognizable point of an insurance process being “too fast” is the point at which poor decisions are made regarding risk. If the risk is the same either way, then there is no “too fast.”

In my last blog in this series on how buying decisions are changing, we discussed some of our findings from the Majesco Future Trends 2017 report and talked about how a generational shift of market boundaries and technology was creating a culture of impatience.

See also: How Basis for Buying Decisions Is Changing  

In today’s blog, we’ll explore how insurers are coping with the need for speed, without compromising on risk. We’ll look at how product adaptation and a transformed framework will benefit insurers by positioning them to meet needs with immediacy. Because human decisions are being made faster than usual, it places the onus on insurers to create products that can be quickly and easily understood. It also means building a framework that supports quick evidence gathering, rapid data transmission, instant analysis and immediate transactions.

Why is speed filled with potential risk?

There are essentially two reasons why quick decisions can be bad.

  1. If an insurer takes a shortcut to provide quick coverage, it may be missing key information regarding risk. Is the insurer getting the data and information it needs in a timely manner, or is it more concerned with providing a decision in a timely manner?
  2. If the customer is making a poor decision to gain quick coverage or if the customer quickly decides against coverage, the customer could be at greater risk. Does the customer understand the choices, both in terms of insurers and products? Will the choice just cover risk or help the customer monitor and reduce risk?

Behavioral science and rapid decisions

In our last blog, we mentioned Daniel Kahneman’s book, Thinking, Fast and Slow. Kahneman describes human decision making and thinking as a two-part system. System 1 thinking produces reflexive, automatic decisions based on instinct and experiences. These are “gut” reactions. System 2 thinking is slow, deliberate and based on reason and requires cognitive effort.

In an ideal world, insurers would be able to help customers to slow down and make better decisions. That world, however, has rapidly disappeared because of new expectations set based on experience in other markets or industries.  Just consider Amazon continually resetting the bar.

So, it is incumbent upon insurers to rise to the new “speed” bar and create a new model for rapid, yet limited risk insurance decisions. This is a large part of what insurtech has been trying to disrupt. Insurtechs have been borrowing principles of speed, psychology and behavioral economics from other markets and industries to persuade customers to do business with them while they are making quick decisions.

The highest-profile use in 2016 was Lemonade, a startup darling.  The company recently announced national expansion plans and has been widely cited for its disruption of the traditional insurance business model with a new one grounded in outside-in, innovative business processes, sophisticated technology and behavioral economics principles. Dan Ariely, well-known author of Predictably Irrational and other books, has helped the company create a truly different insurance experience through both process and perception.

Lemonade changed the customer experience along the entire value chain, based on Ariely’s insights about people’s decision-making processes. The AI chat-driven application and claims processes use a few simple questions, pulling in data as needed from other sources behind the scenes.  Lemonade claims it takes 90 seconds to complete a purchase and three minutes to get a claim paid (though it has also extensively promoted a recent 3-second claim).  These simple, transparent and fast processes require less System 2 thinking by customers, creating a simplified and engaging experience while ensuring that the data used for underwriting is the most important, credible and accurate, rather than relying on human memory.

Auto enrollment, social proof and honesty pressure

At the macro level, government, academic and corporate efforts have focused on encouraging greater employee participation in saving for retirement by devices like automatic enrollment and default contribution rates for 401k plans, and improving individual health insurance plan decisions by reducing choice overload, among others. The UK government has a Behavioural Insights Team (BIT) nicknamed the “Nudge Unit” whose mission is to “use insights from behavioural science to encourage people to make better choices for themselves and society.”

At the micro level, companies like Geico employ principles like social proof (i.e. “people like you choose…”) to increase shoppers’ confidence and nudge them toward selecting specific products and closing the sale immediately. This kind of evidence is designed to quickly move people off the fence of indecision and into the security of the social community insurance fold.

Lemonade tackles the question of customer honesty by employing a social benefit component. The company takes a 20% flat fee off the premium paid, with the balance used only to pay claims, then gives any excess to a charity of the customers’ choice. This sets up a quasi-“moral commitment” for the customer to act in the interests of that organization (by behaving responsibly and not filing a claim that will reduce the benefit to the charity). By explaining the model up front, Lemonade gains the mental assent to honesty during the crucial application phase. An applicant isn’t just buying insurance, she is “buying into” a bigger promise that includes risk protection when needed and support of a worthy cause for every dollar unused for claims.

See also: How We’re Wired to Make Bad Decisions  

All of these efforts help make both fast decisions and good decisions, significantly reducing or eliminating risk to gain speed in the process.

Shifting up to the next gear

Seeing how changes to customer-facing engagement can both improve and speed up decisions, we’re now faced with the impact of those decisions on technology throughout the business. Is it possible for insurers to innovate fast enough to make quick decisions pay off? Because the need for speed touches so many different areas of the business, insurers wanting to rewrite decision methodology may need to act more like startups — innovating from the outside in. In the Future Trends report, Majesco advocates that insurers re-imagine the insurance business by creating a new business model that embraces the demographic, market boundary and technology changes rather than restructuring the old model.

The new ideal is a cycle of continuous insight and improvement that may bear unintentional yet valuable fruit. When an insurer transforms itself to meet the demand for quick decisions on its standard products, it will also be laying the groundwork for systems that will support new product development — products that currently lie outside its realm. Once an insurer is prepared to gather evidence quickly, quote quickly and engage with speed — then every insurable person, event or property becomes a new opportunity for business. It is within today’s fast-paced lifestyles where insurance is likely to find new lodes of business opportunity from unserved or underserved markets and customers. Insurers that understand the nature of good decisions in a time-crunched culture will meet new customer needs without compromising themselves.

For a deeper look at how lifestyle trends are affecting insurance technology decisions, be sure to read Future Trends 2017: The Shift Gains Momentum.

How Basis for Buying Decisions Is Changing

Building a business around speed and convenience is nothing new. Fast food drive-thrus, cell phones and FedEx overnight delivery services were just some of the predecessors to today’s Ubers, apps and same-day Amazon orders. But in most of these cases, purchase decisions were based upon simple factors — “I’m hungry,” or “We need delivery of a legal document,” or “Of course it would be nice to be able to make a call from my car.”

There were other services for which people understood that immediacy wasn’t an option. Many financial decisions took time. If you wanted to earn a little extra interest by using a certificate of deposit instead of savings, you would have to wait months or years for maturity. Securing life insurance was a multi-week (sometimes multi-month) underwriting process. Applying for a home loan with multiple credit and background checks took time. For the most part, people accepted these elongated processes and delays with resigned and good-natured patience. This was life. Important decisions required time, not only in the preparation, but also in the education and execution. Two hours with a life insurance agent would allow you to learn about all of the products available and understand their complexity, and it would help the agent to fit products to your needs. You valued the time spent learning, understanding and choosing based on the trusted relationship with your agent.

The convergence of generational shifts and technological advancement created a new mindset that rewrote expectations and priorities for many. Patience is no longer always considered a virtue. Insurance relationships are no longer always valued. Time-crunched people seek time-saving services. Value is seen in immediacy, uniqueness and ease.

See also: Innovation: a Need for ‘Patient Urgency’  

Enter the new generation of insurance companies redefining the insurance engagement. Lemonade, TROV, Slice, Haven Life and others who are redefining speed and value to a new generation of buyers … are placing traditional, existing insurers on notice.  From purchasing a policy in less than 10 minutes to paying a claim in less than three seconds … speed and simplicity are the new competitive levers.

Out of necessity, this has changed an insurer’s view of competition. Insurers used to know their competitors. They understood their distinctive value propositions. They debated on what were the real product differentiators. Insurers understood the reach of their agents, their geographic limitations and the customer and agent loyalty they could count on because of their excellent service.

While all of these factors still guide insurance operations, the competitive landscape has shifted to different factors critical to acquiring and retaining customers. Insurers are feebly groping for just a tiny bit of space in consumer minds —enough to plant the seed of need and just a little more to water the plant into engagement and completing a transaction — because today’s consumer isn’t going to listen well enough to grasp distinctive details. He or she is looking for an easy and quick fit.

A 2015 study of Canadian consumers estimated that the average attention span had dropped to 8 seconds from 12 seconds in 2000, driven at least in part by consumers’ constant connections through digital devices.

Need. Purchase. Done. Happy.

A 2012 Pew survey of technology experts predicted what is now coming true, “the impact of networked living on today’s young will drive them to thirst for instant gratification, settle for quick choices and lack patience….trends are leading to a future in which most people are shallow consumers of information.”

Only five years later, insurers are feeling the impact.

A key reason many of the new, innovative companies are appealing to consumers and small and medium-sized businesses (SMBs) is because they simplify and remove some of the cognitive effort required to make decisions about insurance. In his book, Thinking, Fast and Slow, the Nobel Prize-winning behavioral economist Daniel Kahneman described human decision making and thinking as a two-part system. Greatly simplified, System 1 thinking produces quick (i.e. instantaneous and sub-conscious) reflexive, automatic decisions based on instinct and past experiences. These are “gut” reactions. System 2 thinking is slow, deliberate, reason-based and requires cognitive effort.

In general, most of the decisions we make each day are through System 1, which can be both good and bad; good because it increases the speed and efficiency of decision making, and because in most instances the outcomes are acceptable. However, not all outcomes are good, and many could have been improved had System 2 thinking been engaged. The problem with System 2 is that it takes effort, and humans naturally try to minimize effort.

See also: Insurtech: Unstoppable Momentum  

So, a traditionally complex industry is intersecting with a cognitive culture that is mentally trying to simplify, reduce effort and be more intuitive. This has consequences for decisions throughout the customer’s journey with an insurance company. Good decisions about complex issues like insurance should be based on System 2 thinking. However, during the research and buying processes, the cognitive effort to do so can lead many people to choose other paths like seeking shortcuts to in-depth research and analysis or delaying a decision altogether.

In a recent report, Future Trends 2017: The Shift Gains Momentum, Majesco examined how impatience is driving a shift in behavior that is causing insurers to look at the anatomy of decisions. What behaviors are relevant to purchase? To renewals? To service? How can insurers still provide risk protection to individuals who won’t take the time to learn about complex products? We’ve drawn some of these insights out of the report for consideration here.

For one thing, insurers clearly recognize that the trends affecting them are far broader and bigger than the insurance industry. Businesses and startups across all industries are capitalizing on the lucrative opportunity afforded by meeting the ever-increasing demands for speed and simplicity made possible by technology and re-imagined business processes. Amazon Prime, Netflix, Spotify, Uber/Lyft, ApplePay/Samsung Pay, Rocket Mortgage (Quicken Loans), Twitter, Instagram and other technology-based businesses represent contemporary offerings that have simplified the customer journey.

Retailers such as Walmart, Best Buy, Staples, Amazon and even eBay are testing same-day delivery for items ordered online. Simplifying a customer’s entire journey with a company by making it “easy to do business with” is more critical than ever for insurers.

What is the good news in the world of impatience? Insurers are quickly finding ways to counter the disparity between the need for speed and the need for good decisions. They are also using a bit of psychology to positively influence decisions, and they are buying back some brain space with techniques that both inform and engage.

In Part 2 of this series, we will look at these techniques as well as product adaptation, framework preparation and planning for transformation that will meet the demand for quick decisions. For more in-depth information on behavioral insurance impact, download the Future Trends 2017 report today.

Getting Back in Step With People’s Needs

The origins of life insurance show up at least as long ago as the Middle Ages, when the notion of providing mutual aid emerged in organized structures. People came together via benefit societies for those in need and for the good of all.

Similarly, modern-day carriers originated with mutual ownership – a construct that prioritized maintaining an asset pool to cover claims at any time, including ones that might occur decades in the future.

A lot has changed. The top 25 life insurance carriers, which control 72% of the market, are largely public companies, so they must serve the demands of shareholders, not just policyholders. State, federal and global regulatory authorities watch over insurers’ moves with many goals – a big one being financial stability of carriers. But these efforts do not solve a problem highlighted in this year’s Insurance Barometer StudyOne-third of American households would have an immediate problem paying basic living expenses if the primary breadwinner died. And an additional one-third has no idea what they would do should they find themselves in this situation.

See also: What’s Next for Life Insurance Industry?  

Ask people inside the sector the question, “Why doesn’t everyone buy the coverage they need, and may even know they need?” Responses are variations on three themes: (1) potential buyers perceive the products as too expensive; (2) they don’t understand how insurance works and what its value is; and (3) they put it low on the priority list relative to other financial commitments.

None of these explanations is flat out wrong. But settling for them risks derailing innovators from solving a problem that will continue to affect people in need and the rest of us, too. It is a problem worth solving.

Insurtech has become a hot sector, but life insurance gets relatively limited focus from either startups or investors. Why? Experts offer a few theories: It is complex — loss curves run for decades. Unlike auto and home insurance, there’s no requirement to own life insurance — so there is no definite group of buyers. Asset growth in this economic and regulatory environment has become trickier. Capital requirements are tougher. And maybe founders and funders themselves don’t want to look death or the greatest personal catastrophe in the eye.

While these reasons sound plausible, there is a way to think about how to uncover sources of value and solve a marketplace and social problem hiding in plain site. Here is a proposed three-part plan:

1. Reframe the problem.

Life insurance has historically addressed the problem, “What if I die too soon?” The questions asked now about financial health sound more like, “How can I be sure I’ll cover my monthly expenses given my earnings?” “How will I ever retire?” And, “What if I live too long?” Fears about dying too soon have been pushed down the priority list. In an era of longer life expectancy and lower inflation-adjusted income for many Americans, the new priorities are smart. Consider, therefore, how to solve these problems. Listen to people’s desire for products that pay the living, provide coverage for long-term care and medical expenses and are designed with far greater transparency than today’s living benefit products. (Try to read an annuity contract, and you will get the point.)

2. Understand what motivates people.

Loss aversion theory, first proven by Nobel Laureate Daniel Kahneman and colleague Amos Tversky, demonstrates that people prefer to avoid loss rather than pursue the opportunity to realize an equivalent gain. No surprise, then, that confronting one’s mortality is a topic to be avoided — it is the ultimate loss. This is especially the case given that many see no upside to buying a life policy: “When I win, I lose.” There will be traction for those innovators who can get to a nuanced definition of “trigger events,” beyond the tired and obvious ones. Trigger moments are when people will be more likely to evaluate the loss/gain relationship in a new light.

See also: 8 Start-ups Aiming to Revive Life Insurance  

3. Don’t just play around the margins of what already exists.

Be open to the possibilities that: (1) Potential buyers who say your product is too expensive are trying to tell you that the price/value relationship is weak. (2) People don’t understand the value of many life insurance products because these products are too complex. (3) In a world, where people fear the consequences of living too long, a product that focuses on one’s death seems out of step. Test the receptivity for product concepts that include living benefits and allow people to make tradeoffs among features.

On the critical path: (1) cracking the code to combine delivering value to the buyer and financial feasibility all the way through claims payment, (2) executing with minimal fine print and (3) creating products that can be distributed through a cost-effective, multi-channel platform that leans digital/call center, innovates on commission structures and defines a new agent archetype.

Building a Risk Culture Is Simple–Really

Yes, building risk culture is easy! Before I explain, let me first clear up a few weird misconceptions about risk culture that have been floating around in non-financial companies:

Making decisions under uncertainty is not natural for humans.

Back in the 1970s, scientists had a breakthrough in understanding how the human brain works, what influences our decisions, how cognitive biases affect our perception of the world and so on. Daniel Kahneman and Vernon Smith received a Nobel prize in economics back in 2002 “for having integrated insights from psychological research into economic science, especially concerning human judgment and decision-making under uncertainty.” I am amazed how many risk managers and consultants continue to simply ignore this research. Identifying, analyzing and dealing with risks is against human nature. Stop kidding yourself. The sooner we, as a professional community, accept this, the easier it will be to integrate risk management into decision making.

Managers do not take risks into account by default.

One of the biggest deceptions floated around is that most business processes already take into account risks and that decisions are made by management after careful consideration of risks. Not so. Naturally, managers do consider some of the more obvious risks, and there are exceptional cases where risk analysis is already integrated into the decision making. For the other 95% of the companies, existing processes and management tools ignore or purposefully hide significant risks. I bet that if risk managers, instead of running useless risk workshops, had a deep hard look, they would soon discover that budgets are overly optimistic, project plans are unrealistic and some corporate objectives are borderline naïve. Of course, the rest of the company is fine with how things are and will do everything to stop risk managers from getting involved.

See also: Building a Strong Insurance Risk Culture  

Making risk management everyone’s responsibility is just wishful thinking.

I don’t quite understand why, but there seems to be an idea that strong, robust, risk-aware culture is the ultimate objective. It sounds great, but it is physically impossible. And this is why I think so many risk managers have failed and so many more are struggling to make an impact. They are trying to move the rock that is not meant to be moved. This is probably the most important point of this article:

The only person in the company who thinks strong risk culture is a positive thing is the risk manager. The rest of the organization sees risk management as a direct threat to their personal interests, their income and their position in the corporate world.

Let me repeat: Most managers ignore risks and take uncalculated risks for a reason.

But not all managers and not all the time. And that’s where the risk manager comes in, trying to change the culture of CERTAIN individuals SOME of the time.

Risk management culture is not about hearts and minds.

By now, after reading everything I tried to communicate above, I hope you realize that management doesn’t care about risk culture. I mean they will still say the right words when the risk manager is present, but deep down nobody will care. The only chance for risk culture to stick is if it makes business sense for the individuals. And I don’t mean soft things like transparency, corporate governance and other nonsense, I mean direct impact on the bottom line or the personal security of an individual. The best examples of managers suddenly becoming very risk-aware were when I was able to show that by better managing risks individuals could protect their role, avoid prosecution, have a better business case for investors, save on insurance, save on financing costs or get higher bonuses.

And yet….  

And yet despite everything I said above, building risk culture is a piece of cake. Risk managers just have to realize that they won’t be able to convert everyone and that some people are beyond help. There is also no single solution that will do the job. It’s all about finding what makes each individual tick. It’s time-consuming, yes, but not difficult at all. Hence it can be equally applied by large corporations and small and medium-sized businesses.

Here are some practical ideas (make sure you click on the links in the article; each one leads to a short video explanation) to get you started:

  • Develop high-level risk management policy – It is generally considered a good idea to document an organization’s attitude and commitment to risk management in a high-level document, such as a risk management policy. The policy should describe the general attitude of the company toward risks, risk management principles, roles and responsibilities and risk management infrastructure, as well as resources and processes dedicated to risk management. Section 4.3.2 of the ISO31000:2009 also provides guidance on risk management policy.
  • Integrate risk appetites for different risk types into existing board-level documents; don’t create separate risk appetite statements.
  • Regularly include risk items on the board’s agenda
  • Consider establishing a separate risk management committee at the executive level or extend the mandate of the existing management committee – this worked like a miracle for me personally
  • Reinforce the “no blame” culture, on why to disclose and account for risks
  • Include risk management roles and responsibilities in existing job descriptions, policies and procedures and committee charters, not in a risk management framework document
  • Update existing policies and procedures to include aspects of risk management
  • Review and update remuneration policies
  • Provide risk awareness training regularly
  • Use risk management games
  • And, most importantly, get personally involved in business activities.

See also: Thinking Differently: Building a Risk Culture