Why is it hard to make the best financial decisions?

If you’re one of our clients at Mana, you’ve probably heard us advise you to “stay the course” with your investments, and to “simplify and automate” your savings. These are some of the most reliable adages in personal finance. Even if you’re not a Mana client, you might already know that doing this is a good idea. Maybe you’re already economically savvy, and familiar with the dangers of emotional investing. Or perhaps you are a seasoned master in the mundane art of controlled spending, consistent saving, and non-reactive budgeting. I say mundane because that’s exactly what good financial practice is - it’s steady and predictable, not a rollercoaster ride of emotion and instability. People with good money habits follow a simple set of rules and make consistent decisions. 

You might know these rules, but do you understand why financial experts and wealthy individuals use them? Do you understand them well enough to apply them in other areas of your life? 

Today we’re going to discuss one of the most foundational theories of behavioral economics and psychology to illuminate how the natural human instinct to avoid losses can actually keep us from making savvy financial decisions. Gaining insight into why responsible money actions sometimes feel difficult or unintuitive can help you reflect more deliberately and ultimately make better choices in the future. Besides, understanding cognitive processes and human decision making is just plain interesting! And don’t worry if you feel like you haven't developed these good habits yet - this post is for everyone - even readers who feel trapped on a bad carnival ride of spending and debt. We’re going to break down the science of good and bad decisions, and talk about how to avoid common cognitive traps that prevent people from making the best financial choices. 

In 1979, Daniel Kahneman and Amos Tversky published a paper titled “Prospect Theory: An Analysis of Decision under Risk” in which they laid out a theory of human decision making that would eventually earn them the Nobel Prize. Prospect Theory is a model that describes how people balance risk and reward when making decisions, and how humans tend to overvalue potential losses, and undervalue potential gains.  

Prospect Theory demonstrates that humans are disproportionately affected by the prospect of losses vs. gains in decision making. Chart from BoyceWire.

To understand why prospect theory is important, consider a more conventional way of thinking about how we make choices. People like to think of themselves as mathematically rational decision makers. We take information about the world around us and make the best decisions based on those facts. In a phrase, this is Expected Utility. We can illustrate this with a coin toss bet: consider a scenario where every time the coin lands on heads, you win $100, and every time the coin lands on tails, you lose $1. Humans can do the math, figuring a 50% chance of winning $100 on any given flip and a 50% chance of losing $1 on any given flip. The expected utility can be calculated as pWIN(50% * 100) - pLOSS(50% * 1) = $49.50. Most people would take this bet, and rightly so - these are good winning odds - you can expect to walk away with more money than if you don’t take the bet. But what if the scenario involved a bigger loss? Let’s say you still win $100 for heads, but now you lose $20 for every tails. The expected utility is now $40. Still pretty good odds, but suddenly the decision feels more difficult. In fact, something curious happens as researchers push the loss values closer to the win values in these coin toss experiments: people stop taking the bet long before the expected utility reaches 0, which is not mathematically rational decision making. It turns out that assuming humans would operate based on expected utility was a deeply flawed notion. Prospect Theory correctly demonstrated that people do not behave strictly according to the mathematical utility of the options in front of them. Instead, we apply uneven decision weights to the utility of gain over the disutility of loss. Moreover, people’s perceived likelihood of value estimates are often totally incorrect, and the context of various decisions can induce strong, predictable biases in our prediction and understanding of likelihood. In the rest of this post, we’ll explain how each of these biases rule our everyday decision making behaviors, and discuss how to prevent them from causing harm to your wellbeing. 

But first...let’s illustrate prospect theory with a classic financial decision: what to do with an unexpected salary bonus?

Note: this example is for illustrative purposes only, and should not be construed as financial advice.

Let’s say you receive an $11,000 bonus (lucky you!), and you are trying to decide between two simple investment options:

Option 1: a fixed rate bond. Let’s say this bond reliably returns 6% interest to its holders, and because it’s a special bond, has 0% chance of you losing your money.

Option 2: investing in a flashy new tech company. Analysts are predicting a 70% chance that an upcoming company announcement will increase its stock value by 25% next quarter and a 30% chance that the company will go under.

If you gave these options to a mathematically rational robot, it would choose the high likelihood stock investment. It would make this decision based on expected utility-- the expected utility of the stock investment is higher than the expected utility of the bond. 70% is a fantastic probability of success! Plus, even if the company goes out of business and you lose it all (a truly worst case scenario), this bonus was unexpected and probably wouldn’t affect your overall financial well being. Nonetheless, many real people would still choose the fixed rate bond in this scenario, because it offers no probability of loss, even if the possible gain is much smaller. In fact, you probably felt yourself wondering about the risks associated with this tech stock. What if the stock doesn’t increase? You might have noticed the word “new” tech company. What if their product fails? How much will you lose? Humans are not rational probability estimators, and in fact we’re quite bad at predicting the likelihood of losses and gains. And of course, if this were a real-life decision, there would be many additional factors or options to consider, making your decision space even more difficult to assess. 

So, why does this stock investment feel so risky for people?

Reason #1: Certainty Bias

The human brain was not designed to deal with uncertainty. On the contrary, our sensory systems have evolved to help us make quick decisions in order to survive. We rely on patterns and heuristics to reduce our need for slow, critical thought. When was the last time you approached a building doorway and measured to check if you would fit through? How about the last time you counted individual leaves to make sure you were looking at a tree? Hopefully never, and that’s because our brains do quick, pre-conscious calculations and estimates so we can move through the world with little effort. Once our brains are certain about something, we continue to use that information and it becomes very hard to re-evaluate that rule. We like assurance and known entities, which is why the bond option is so appealing in the above scenario. As a rule, humans overweight options that are certain, and are unduly risk-averse when it comes to potential gains. Most people would rather take a small guaranteed win vs. taking a chance at winning a larger sum when there is a risk of losing or getting nothing. A real world example of this is consumer preference for being rewarded with a 10% off coupon for joining a mailing list, vs. filling out a form to enter in a $2,000 sweepstakes raffle. Even though the coupon is only useful if you spend more money (a probabilistic loss!), the unlikely odds of winning the free-to-enter raffle make that option less appealing. Put simply, humans would rather take a small-but-guaranteed prize over the slim chance of a large reward. 

This bias obviously affects investment choices, but it can also cause problems in day to day life. Certainty bias causes people to stick with suboptimal products or services, simply because they’re familiar, and trying something new feels too risky. It guides peoples’ travel choices, food preferences, and many other entertainment decisions. 

Reason #2: Framing Effects

Take a second and look somewhere away from your device screen. Now, when you put your eyes back on this page, it was probably pretty easy to figure out where to start reading again. Chances are, you didn’t start reading through the article from the beginning until you found this sentence. Instead, you likely used the bold font heading above to quickly focus your attention. Okay, now try to find the word “potential” in the section above (I’ll wait!). That probably felt a lot more difficult and laborious, because you didn’t have a good visual cue to rely on. 

The isolation effect shows that when humans consider a set of information, our brains naturally focus on unique elements while disregarding similar ones. That’s because considering each individual option requires a lot of effort and, once again, our brains were designed to do everything possible to reduce cognitive effort! This is why real world investing feels even more complicated than the simple scenario in this blog. More information and options means slower thinking with less certainty - both of which make us uncomfortable. 

When we make decisions, we like things to be framed for us, to signal what we should pay attention to and help us feel more certain in our choice. Here’s another question: would you rather save your money with a bank that has a 92% customer satisfaction rate, or a bank with an 8% customer dissatisfaction rate? A second look over the previous sentence reveals that these banks offer equivalent service. And yet, framing the second bank negatively (in terms of dissatisfaction rate) primes people to think about the potential for negative outcomes (especially the prospect of losing money), which makes them feel better about choosing the first bank. Situational framing influences many of our day to day decisions without us noticing. 

Reason #3: Loss Aversion

Losing, and especially losing money, is perceived as an incredibly undesirable experience. This heuristic is one of the biggest culprits of poor financial decision making. Kahneman and Tversky famously demonstrated that humans will behave in a way that minimizes their potential losses, even when the probability of those losses occurring is very low. While neuroscientists still don’t understand why our brains are wired this way, loss-avoidant behaviors are well documented and pervasive in our lives. Insurance companies prey on our loss-aversion by advertising long lists of costly scenarios, making us believe that the a) odds of one of them occurring is higher than it is, and b) that avoiding them by paying a monthly insurance fee is the economically safe option. Gamblers report feeling worse after winning $150 and then losing $120 more, and feeling better after losing $70 and winning back $100. In both cases, they end up with a net gain of $30, but the powerful framing of loss makes the second scenario more appealing. 

Outside of finance, loss aversion can influence how we spend our time or take care of our bodies. New exercise routines are hard to commit to because our initial feelings of physical discomfort are more aversive and easier to focus on than the long-term positive health benefits of consistent workouts. In life, our losses indeed loom much larger than our gains. 

So, how can you use this information to make better choices?

Hopefully you now have a clearer understanding of why it’s so hard to make good decisions. You’re probably wondering how to do better, and how some people seem to make good financial choices with ease. The good news is that not all mental rules and biases are bad. It turns out that we can teach ourselves useful heuristics too! Remember that investing phrase, “stay the course”? This simple rule combats all three of the core biases in prospect theory. When markets perform poorly, we often get the mathematically irrational urge to sell quickly and avoid further loss. By remembering to stay invested, we can cope with uncertainty by simply removing it from our decision space. We can consider a broader timeline of information (instead of fixating on an isolated drop in performance, we can look at longer time horizons and see that the market has a consistent upward trend), and we can overcome emotional reactions and avoid fear-based loss aversion. “Simplify and automate your savings” is another super helpful rule. Many people have trouble gauging how much they should be saving each month, and where they should be saving their money. Building a successful savings plan is a lot like starting a new exercise routine: at first, the losses are more apparent and painful than the gains (less money to spend shopping or eating out!), which is why people often fail to save enough manually. By automating the process, you can avoid the powerful urge to disrupt it when your biases come into play. Simplifying your savings strategy by consolidating accounts or choosing a strategic set of investment options will help you combat framing effects (fewer choices, less mental effort!), and feel more certain about your decisions. Any opportunity we can give ourselves to slow down our cognitive process and carefully consider a decision is beneficial. The pitfalls described in this post are mostly avoidable with a bit of critical thought. 

And finally, it’s essential to remember that life is complicated. It’s okay that humans are not perfectly rational decision makers, because the choices we make don’t exist in a vacuum. It’s easy to model losses and gains over a coin toss or a game of blackjack, but it quickly becomes impossible to build the perfect investment equation for a two-income family with multiple assets and liabilities and a baby on the way... Scientists still do not understand what makes humans so risk averse, and why our brains sometimes rely on disadvatageous rulesets (although these traits have seemingly helped our species survive over the long run). Until these cognitive problems have obvious solutions, sound financial decision making will remain a challenging endeavor. This is where working with an experienced financial planner can really help. Navigating complexity and uncertainty is much easier with support. At Mana, we’ve spent years immersed in the science of decision making as well as the real-world challenges of life design and wealth management. Our mission is to educate and empower clients through evidence-based, compassionate finance. We know that putting good ideas into action is possible with the right plan, and finding your match in financial guidance can help you make great choices without the mental and emotional strain. 

Madison Elliott is a Cognitive Science PhD Candidate at The University of British Columbia in Vancouver, BC, Canada. Madison leads data engineering and usability at Mana Financial Life Design (FLD). Mana FLD provides comprehensive financial planning and investment management services to help clients grow and protect their wealth throughout life’s journey. Mana FLD specializes in advising ambitious professionals who seek financial knowledge and want to implement creative budgeting, savings, proactive planning and powerful investment strategies. Madison brings her combined background in cognitive science, computer science and clinical psychology with her professional UX design and engineering experience to optimize workflows at Mana FLD and improve people’s lives.