This report describes 20 flaws, biases, and causes of bad behavior I’ve seen pop up often when people deal with money.

1. Earned success and deserved failure fallacy: A tendency to underestimate the role of luck and risk, and a failure to recognize that luck and risk are different sides of the same coin.

I like to ask people, “What do you want to know about investing that we can’t know?”

It’s not a practical question. So few people ask it. But it forces anyone you ask to think about what they intuitively think is true but don’t spend much time trying to answer because it’s futile.

Years ago I asked economist Robert Shiller the question. He answered, “The exact role of luck in successful outcomes.”

I love that, because no one thinks luck doesn’t play a role in financial success. But since it’s hard to quantify luck, and rude to suggest people’s success is owed to luck, the default stance is often to implicitly ignore luck as a factor. If I say, “There are a billion investors in the world. By sheer chance, would you expect 100 of them to become billionaires predominately off luck?” You would reply, “Of course.” But then if I ask you to name those investors – to their face – you will back down. That’s the problem.

The same goes for failure. Did failed businesses not try hard enough? Were bad investments not thought through well enough? Are wayward careers the product of laziness?

In some parts, yes. Of course. But how much? It’s so hard to know. And when it’s hard to know we default to the extremes of assuming failures are predominantly caused by mistakes. Which itself is a mistake.

People’s lives are a reflection of the experiences they’ve had and the people they’ve met, a lot of which are driven by luck, accident, and chance. The line between bold and reckless is thinner than people think, and you cannot believe in risk without believing in luck, because they are two sides of the same coin. They are both the simple idea that sometimes things happen that influence outcomes more than effort alone can achieve.

 Related: When Should We Trust Predictions? This Answer Will Surprise You!