Need Not Greed: Bonuses, Risk–Taking And Evolution
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What to do with those 'greedy' bankers
In the wake of the most recent financial crisis, financial regulatory bodies across the world have sought ways to curb the excessive risk–taking of bankers. Most often, this is done by capping bonuses and developing clawback policies (Gray, 2016). Such decisions are based on the widespread view that financial incentives are a factor for risk–taking. That the potential to earn large personal payoffs is so attractive that many individuals are willing to take excessive risks in order to earn them. This is the classical 'homo–economicus' view of human behavior, where people are considered rational actors, motivated to maximize personal utility for reasons of self–interest (Aktipis & Kurzban, 2004; Thaler, 2000). In other words, be greedy.
But…. what if bankers didn’t take risks to earn their bonuses for reasons of greed, but for reasons of need?
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We are 'needy' humans
Bankers are of course ‘homo–sapiens’ not ‘homo–economicus’. So they are driven and influenced by the same innate mechanisms that guide and influence us all. So why would we seemingly be willing to take risks to earn more? What actually motivates and drives risk–taking? The answer may lie in how we have evolved.
Throughout history, our ancestors constantly faced problems. Often the same problems over and over again. The particular conditions of the environment and the problems encountered sculpted specific adaptations to overcome them. Sort of like a lone tree on an unsheltered hill. It is constantly battered by winds, and over time it adapts to deal with this by curving over, allowing the wind to pass easily. Similarly, humans have evolved behavioral adaptations which exist to solve a particular problem our ancestors faced in a particular domain.
One of the problems which risk–taking solved, was ensuring we had enough energy (i.e. we ate) in unpredictable foraging environments (Caraco, Martindale, & Whittam, 1980). When foraging, our ancestors may have faced a number of choices; they could forage in the area they knew was not overly abundant but fairly consistent in terms of food levels (i.e. the low variance, low risk option) or they could forage in a more variable area that sometimes had a lot of food and sometimes not much at all (i.e. the high variance, high risk option). The choice depends on the person’s need levels. If their need, in terms of energy requirements, are fairly well satiated, then why bother going to the highly variant area? The low risk option will suffice. However, when the person’s need is high, they are close to starvation and energy levels are depleting, then taking the chance with the risky option might just payoff. It is certainly worth the risk, as the low variant option won’t offer enough energy to ensure survival.
Thus, humans have evolved to be very sensitive to need levels. Ensuring needs are met ensures survival. Consequently, we tend to assess our current situations in terms of whether it is meeting our needs. When needs are unmet, (i.e. our current state is disparate to our desired goal state) and a low risk option offers little chance of meeting our need, we are innately motivated to take risks (Gonzales, Mishra, & Camp, 2016; Mishra, 2014).
Need – satiation: the ultimate driver of risk–taking
Evolutionary perspectives operate at an ultimate level (Scott–Phillips, Dickins, & West, 2011). They seek to explain why something exists or what its function is, rather than offer a proximate explanation of how it works (Saad, 2011). Theorizing that need satiation is the ‘ultimate level’ driver of risk–taking gives such behavior an origin and a rationale. More importantly, such innate drives are human universals and so have broad application for understanding risk–taking in many different contexts (Witt, 2016).
An interesting aspect of many bonus systems, particularly those in the banking sector, is that they are contingent on meeting a particular performance level. Banks set targets and individuals have to meet those targets in order to be eligible for reward. Furthermore, not meeting those targets may be detrimental to the individual — it might limit their progression or result in them losing their job. In essence, their survival is somewhat dependent on performing and meeting those targets. Unbeknown to managers, this may be creating a ‘need’ situation comparable to those our ancestors faced.
Imagine a salesperson who has a target to sell $10,000 worth of products each month. This essentially becomes a required ‘need’ level. What if he experiences poor sales a few months in a row? This puts him in a high need situation, as the likelihood he will achieve his target is reduced and his ability to do so is compromised. Such an individual will be more likely to prefer a gamble where he has a 10% chance of making $10,000 of sales, rather than accept a certain sale of $1,000. In the finance sector, yearly rather than monthly targets are set, and many such professionals recount how people down on target towards the end of the year tend to up their risk–taking (Shapira, 2002). Furthermore, most accounts of rogue traders describe how their risk–taking increased with every loss, as they sought to recoup the losses and break–even (Abdel–khalik, 2014).
The evolutionary perspective described here provides an explanation for why this happens. Bonuses arguably don’t motivate people to take risks because they are greedy. Rather, they impose a threshold which individual have to or need to meet. By doing so, they evoke the evolutionary function of risk–taking — need satiation. Humans have ensured their survival by evolving to take risks when their current situation does not meet their desired goal state (Mishra, 2014).
What is the implication of this?
Recognizing that risk–taking is influenced by something so innate, has specific implications for interventions (McDermott, Fowler, & Smirnov, 2008). Rather than trying to cap bonuses, the focus should be on carefully calibrating performance targets. Much of the theory behind goal–setting rests on the premise that the harder a target is to achieve, the greater the effort it will motivate (Locke & Latham, 2002). Consequently, many organisations, not just those in finance, set employees hard to reach goals. However, if the target is so hard to reach, it may evoke risk–taking as individual’s perceive themselves to be in a situation significantly disparate to where they need to be. Of course, taking risks is not necessarily a bad thing. In fact, it is often required. Problems arise when risk–taking becomes excessive. From this evolutionary perspective, the greater the disparity between current state and desired goal state, the more willing someone is to take risks.
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Understanding this ultimate driver of risk–taking may also help people make better decisions. For example, in financial markets traders, are expected to make decisions based on ‘running their winners and cutting their losers’. However, many traders describe how difficult that it is to do. They tend to take profits too early and chase losses (Willman, Fenton–O’Creevy, Nicholson, & Soane, 2002). Such behavior is understandable when you recognise the need satiation function of risk–taking — we evolved to take risks to meet needs, but as soon as needs are met we lock in that level. We have not evolved to maximize, but to satisfice and accept good enough decisions (Naumof, 2016).
When facing difficult economic circumstances, such as the financial crisis, it is often easy to forget that human nature is involved. Designing organizational systems with the evolutionary adaptations which underlie our decision-making, provides us with novel ways to overcome further crises and enhance the functioning of many organizations.
Disclaimer: The views and opinions expressed in this article are those of the authors and do not necessarily reflect the official policy or position of The Decision Lab.
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About the Author
Belinda is a PhD Candidate at the University of Greenwich, London. She studies decision–making under risk and uncertainty and believes that insights from evolutionary psychology can help improve our understanding of what influences risk–taking. She is particularly interested in applying evolutionary psychology to improve the decision–making of investors and financial traders.