Finding the behavioural roots of financial failure

Common psychological traps at the root of risk

The human factor: influences on financial decision-making

While regulators continue to place significant pressure on firms to improve their internal systems and controls, they have also become more interested in firms' risk culture – though, without a strict set of regulatory requirements, financial institutions have been left to figure out for themselves how to assess or change behaviour.

Reminders of past conduct failings are never too far away. In May the Federal Reserve chair Janet Yellen recapped yet again the weaknesses that set the stage for the 2008 financial crunch: "The crisis revealed that risk management at large, complex financial institutions was insufficient to handle the risks that some firms had taken," she said at an event in Washington, citing compensation programmes that failed to appropriately account for longer-term risks and lax controls that contributed to unethical and illegal behaviour.

With personal conduct at the heart of many loss events, regulators and academics are undertaking more detailed analysis on the cognitive failures that lead to poor decision-making, such as overconfidence, group think and ambiguity aversion. Though it may not be a regulatory requirement, such research could then be used by firms to set appropriate behavioural risk indicators in their scenario analysis. Advocates for the more judgment-led approach say this will allow them to better assess and minimise the expected impacts of an operational risk event – while producing more realistic models that take human nature into account.

Follow the stampede

The psychology behind the risk-seeking and overconfidence seen in the lead-up to the collapse of Lehman Brothers in 2008 remains a classic case study of cognitive bias, particularly as the atmosphere of unrealistic optimism affected not only traders and bankers, but also the central bankers who were happy to trust banks taking riskier positions in the markets, the politicians who pushed for light-touch regulation, and the general public.

"Behavioural finance tells us that when we become overconfident, we see less risk," says Theo Kocken (pictured), chief executive of risk management firm Cardano.

The theory that people become more relaxed about risk at a time when caution is actually needed most is largely associated with US economist Hyman Minsky, who argued throughout his professional life that stability leads to instability. Minsky argued that no matter how much experience we have, no matter how many brilliant ideas and new rules are put in place in the years immediately following a crisis, everyone develops financial amnesia in periods of strong growth and surging markets and makes the same mistakes over again. In this way, he suggests, capitalism is inherently unstable – a theory that, though not widely regarded by his peers throughout his lifetime, has attracted more attention post-2008 as a means to explain the onset of the recent financial crisis.

Prompted by the findings of behavioural finance, Martin Wheatley, chief executive of the Financial Conduct Authority (FCA), has encouraged bankers to be aware of both their own cognitive biases and those of their customers. Under his stewardship, the FCA has been using behavioural economics to identify and prioritise consumer risks, using insights from psychology to explore why people often behave in an irrational and uncalculated way.

Testing for group think

Some of the behavioural biases that regulators are focusing on are the perceptions and social influence inherent with group dynamics. While regulating banks often entails establishing complex rules, Cardano's Kocken warns that putting too much focus on specific regulations – and not making time to have regular conversations about what is really risky for an organisation – can be an indicator of growing risk. "Operational risk is not just counting up your mistakes and filling in forms, but improving your processing and avoiding devastating errors," he says – and points out the danger of "selective attention" causing people to miss radical changes in the bigger picture (see here for Christopher Chabris' and Daniel Simon's studies on selective attention).

So another way of assessing compliance is by having regular conversations with boards, looking for signs of overconfidence, risk-taking behaviour or an illusion of control among the group – and the signs of 'group think'.

Social psychological influences are one of the strongest shapers of behaviour, says Richard Cech, senior bank examiner in operational risk governance at the Federal Reserve Bank of New York. "People just don't have an appreciation for how strong group influences are on their behaviour. It's not like you make a conscious choice to conform to the group, you've conformed even before you've thought about it. The group is a very strong driving force for behaviour, including in many cases a person's approach to ethics and change."

Speaking at the same event as Yellen, managing director of the International Monetary Fund, Christine Lagarde, called for the industry's focus to stay on bank culture for this reason: "Whether something is right or wrong cannot be simply reduced to whether or not it is permissible under law. What is needed is a culture that induces bankers to do the right thing, even if nobody is watching."

Unfortunately, the linear and hierarchical structures of financial institutions can actually hinder the decision process, potentially opening a firm up to more risk, according to Santander's group head of op risk quantification and advanced analytics, Bertrand Hassani. "We should go for [a system] where people don't forget that any decision made by them will have an impact on others," he says.

This would entail a better understanding of enterprise risk management on a day-to-day basis, rather than people abiding by specific rules for the sake of it. "I have family in Morocco, and when you ask people there why they wear seat belts in their cars, they'll say it's because of the police," he says. Market players may well see regulation in the same way.

"What regulators want to achieve is noble," Hassani says. "But I tend to believe that between the theory and the practice, there is a huge gap. The balance between regulatory expectations and the way that banks implement requirements will always be hard to meet, as the targeted objectives are different."

A good place to start would be the ERM integrated framework from the COSO group of accounting industry bodies, which is intended to address holes in governance structures. The group also issues guidance on internal control and fraud deterrence. "However many UK firms don't use this enterprise risk framework," says Mike Booth, consultant at Bovill. "Despite the fact they could really benefit from adopting this approach. I believe this is because risk management for some firms is often primarily driven by the need to quantify regulatory capital requirements, rather than the end-goal of risk mitigation."

Addressing ambiguity aversion

Whether modelling for capital requirements or risk management scenarios, indicators need to be realistic rather than what is comfortable and familiar for a manager. A 2014 film on economic cycles co-written by Theo Kocken, called Boom Bust Boom, focuses on the inherent faults of modelling in today's financial sector, largely due to a gap in understanding between financial mathematics (the theory) and financial markets (what happens in practice). One example of cognitive bias is ambiguity aversion. "We don't like to be ambiguous about how the world works, and so we move into probability theories and hide behind mathematics," Kocken says.

But in an operational sense, such models pose a high degree of risk: "In reality, what happens in the financial markets is much more fierce and detrimental than the model tells you." Much of the model risk associated with the financial crisis could have been alleviated by including real behavioural indicators, he says, rather than leaving it to the purely mathematical.

Cech echoes the theory: "If your model doesn't capture the dynamics of behaviour then it is not going to predict anything in an interesting way. And it's not going to be a predictive feature, because all it's going to do is simply say the future is probably going to look like the past."

This aversion is also evident in what the FCA terms "decision-making rules of thumb", where people, when given a wide range of options, often choose the one most familiar to them to avoid the ambiguous or uncertain.

Modelling with real behavioural indicators

The FCA is using theories of behavioural economics on an internal basis, training its staff and carrying out thematic work in particular markets or products, including the communication of disclosures, retirement plans and renewal quotes. Ex-FCA lawyer and now senior associate at Pinsent Masons, Michael Ruck, doesn't believe the UK regulator is likely to pursue enforcement action if banks don't have specific training programmes on behavioural economics. "Rather, they're using these theories to inform their supervisory side, by helping firms look at ways of best practice," he says.

Cech sees merit in using causal analysis to identify the real drivers of behaviour – including group dynamics and that of customers – even if such analysis would have to be done on a trial-and-error basis for a long period of time to accurately identify correlations.

"If you have the right data, and the right model of what causes what, you can start to make projections with improved statistical support," he says.

Agent-based simulation could be used to insert behavioural expectations into scenario models. In fact, there are several ways to approach such a task. "But for any of them to go forward requires a sense of the organisation as a behaving thing, and models that will focus on what drives behaviour," he says. "If we spent more time analysing group process, we might be able to see patterns more easily."

He cites the use of middle-level variables as key risk indicators, gained from regular testing of employees' product knowledge (particularly for complex derivatives traders) and perception of stress (that may implicate day-to-day decisions), as a good approach to measuring and understanding vulnerabilities over a period of time.

"But it's a process. Firms will take a stab at using a variable, or a key risk indicator to test a cause." In this way, some causes may not produce clear correlations to an event, but will add to the data pool that operational risk desperately needs.

A possible indicator suggested by Santander's Hassani is for risk managers to regularly assess the appropriateness of decisions over time – against the number of incidents or management of losses, for instance. Kocken agrees with this approach, arguing that all market practitioners should regularly 'back-test' their past decisions against market outcomes to refine their risk indicators and identify flaws and biases in decision-making processes.

One such indicator could be that a low perception of risk – gleaned by investor interviews and implied volatility in option markets – actually means that risk is very high. Another could be mounting debt. "If people are buying on margins, such as borrowing money from the bank to buy stocks, and those levels are going higher, then that's an indicator that the markets are getting more euphoric and more unstable." And Kocken also suggests keeping an eye on the tone in the market, or in the news, where history has shown that a higher ratio of optimistic phrases can signal greater risk over time.

The important thing to remember is that it's not just one indicator that tells a firm what could happen, says Kocken. "It's a set of indicators, and if all of them are in the red, then there is something really tricky going on."