Investment banks – and the financial services industry at large – continue to bear the reputational scares of some high-profile ethical scandals. In spite of numerous efforts for avoiding ethical risk, emotional contagion, a key factor of ethical risk remains largely overlooked. Hence, it is critical to address the question of how emotional contagion arises and how it can be detected.
Following a number of high-profile ethical scandals in investment banks, the call for changing corporate culture is increasingly gaining traction. However, beyond the fact that cultural change programmes often fail to deliver upon their expected outcomes, such programmes may not be required – or should, at least, be revisited – in order to tackle emotional contagion – the often-overlooked key factor of ethical risk. This should hardly come as a surprise considering that at the end of the day, “you bring your emotions to work. They drive behaviour and other feelings. Think of people as emotion conductors”.1
Emotional contagion is a three-step process through which an individual’s emotions transfer to another individual within a group. During the first stage, non-conscious mimicry occurs, whereby individuals subtly copy one another’s non-verbal cues. During the second stage, a feedback process occurs, whereby individuals translate non-verbal cues into an emotion. During the third stage, a full contagion process occurs, whereby the emotions and behaviours of individuals within a group become synchronised. Two factors are likely to influence this three-step process of emotional contagion, namely, the valence (positive or negative) of the emotion and the arousal level wherein the emotion is expressed.[ms-protect-content id=”9932″]
Emotional contagion can occur through face-to-face group interactions as well as through virtual group interactions (e.g., social networks). A number of contextual, cultural and psychological factors contribute to exacerbate emotional contagion in the context of investment banks. Despite the focus on rational decision-making, investment banks is far from immune to emotions and, subsequently, to emotional contagion. Investment banks and, in particular, high performance teams are often facing stressful conditions. In response to these stressful conditions, the level of various hormones changes (e.g., glucocorticoids and catecholamines). In turn, such changes in hormones can generate significant emotional changes and greatly affect the contagious potential of emotions by generating strong valence-based emotions and high energy levels.
Since the global financial crisis, investment banks have taken decisive steps to decrease ethical risk. However, the digital revolution poses new risks. The rise of social networks, such as encrypted messaging apps used across investment banks, is increasing the risk of renewed widespread ethical risk. Therefore, tackling the question of emotional contagion is growing in importance. This article shows how two core cultural factors, specific to high performing teams in investment banks, contribute to emotional contagion and how, in turn, this latter increases ethical risk. This article also proceeds to show how human-driven alongside analytics-driven solutions can detect emotional contagion and help high performance teams within investment banks build their resilience towards emotional contagion.
Factors Driving Emotional Contagion
In the context of high performing teams in investment banks, two core cultural factors generate the need for individuals to identify with a group, which contributes to individuals’ susceptibility towards emotional contagion.
The two core cultural attributes of investment banks (especially on the trading floor) are uncertainty and smartness (e.g., star employees). The relationship between uncertainty and smartness is dyadic, since the latter protects an individual from the anxiety generated by the former. However, this is not to say that differences do not exist within these organisations. Uncertainty is rooted in the high degree of risk and remarkable feedback speed, which translates into an everyday job uncertainty. As such, “every single day you realise that your job could be gone the next day. You have a downturn in the market and they lay off hundreds of people or you have a downturn in just your desk’s (particular product area) performance; all of a sudden they need to lay off people. Your company decides they don’t want to be in that product anymore; they lay off an entire department. I just think that’s part of life here”.2 Smartness (i.e., star employees) is rooted in the definition of what it takes and what it means to be successful. Individuals are encouraged to focus on their individual success and those who beat the system, rather than conforming to it, might get a significant identity and status payoff.3
In turn, these two core cultural factors are motivations for individuals to identify with a group and to conform. Indeed, according to social identity theory4, uncertainty reduction and self-enhancement are the motivations for individuals to identify with a group. In terms of the uncertainty reduction, group identification reduces subjective uncertainty and relieves associated anxiety because identification mutes neural activity in parts of the brain that process anxiety5. In terms of self-enhancement, individuals need to enhance their self-esteem, which is their overall evaluation of their self-worth6. As soon as group identification occurs, individuals’ susceptibility towards emotional contagion increases.
From Emotional Contagion to Ethical Risk
Evidence suggests that emotional contagion may be evolutionary adaptive by enabling groups to respond appropriately to their environment. Negative emotions tend to narrow the range of groups’ possible thought –action repertoires7 and are an important motivator of action.8 Negative emotions trigger outcome-focussed interactions due to the narrowed scope of attention, cognition and action and therefore drive individuals within the group to focus on task completion. Time pressure can also contribute to this narrowed scope, as a group begins to display anxiety, impatience and despair and consequently the emphasis on project completion increases substantially.9 Positive emotions tend to broaden the range of groups’ possible thought-action repertoires. As such, groups experiencing positive emotions list more things that they would like to do after an induction of positive emotions.
In the context of high performance teams within investment banks, provided that the emotional energy level of the group is sufficiently high, negative emotions can increase ethical risk, as less attention for anything but the task at hand (i.e., generating performance) is provided. Furthermore, especially under conditions of time pressure anger is likely to be triggered (i.e., perceived tensions between ethical requirements and performing the task) and will narrow possible actions to confrontation and attack. These actions of confrontation and attack can be implicit whereby the group engages in ethical violations. Positive emotions can also increase ethical risk as increased performance can lead the group to push the boundaries further and the increased cohesion can lead individuals within the group to display more conformity. Good performance generates positive emotions that can serve as an evidence for the group that it can push its limits further next time, thus increasing ethical risk. Furthermore, success in the face of risk reinforces a sense of group identification and, subsequently conformity, with a group belonging to an elite culture (i.e., smartness), which increases ethical risk.
From Emotional Detection to Emotional Immunity
Two types of detection can be envisaged, a human-driven detection alongside an analytics-driven detection. Once emotional contagion has been tracked and analysed, cognitive behavioural therapy (CBT) can be deployed to help individuals build immunity towards emotional contagion.
In terms of the human-driven detection, training should be provided to individuals within high performance teams – and team leaders in particular. This training should help individuals identify and fight the bias of filtering emotion-related information in the work context and increase individuals’ capacity for recognising emotions accurately.
In terms of the analytics-driven detection, two forms can be considered, namely, individuals’ tracking and social networks tracking to detect susceptibility towards emotional contagion. In terms of individuals’ tracking, over the last few years, a number of solutions have been created for tracking emotions. These solutions include apps such as Therachat and Moodnotes that allow individuals to input and record thoughts and emotions on the go so as to unpack the instances and circumstances that lead to negative or positive emotions and wearables such as Emotiv Insight that records brainwaves to identify an individual’s level of attention, focus, engagement, interest, excitement, affinity, relaxation and stress. In addition, voice-based real time apps such as Beyond Verbal can analyse an individual’s as well as other people’s voice patterns to capture emotions. Whilst individuals’ tracking can be considered as slightly sensitive in a work context, examples of it already exist. Indeed, in 2013 Bank of America ran a programme to track employees with productivity sensors. When the tracking indicated when and where employees were more productive, Bank of America changed the physical layout of its offices to sustain employee satisfaction. Along similar lines, investment banks can pilot emotions-tracking apps or wearables among individuals in high performance teams.
Emotional contagion can also occur in the absence of non-verbal cues typically encountered in in-person interactions. Hence, investment banks can track emotions in social networks by leveraging existing APIs for detecting text-based emotions. Social networks tracking should try as much as possible to distinguish emotional contagion from other emotional alignment effects (e.g., sympathy, empathy, etc.). It should then reconstruct the emotions conveyed by the messages each individual was exposed to before posting his/her own messages. As such, the tracking would identify whether the stimuli are correlated with the responses (i.e., emotions subsequently expressed by the individual).10
The views expressed in this article are the author’s views and not Deloitte LLP’s.
About the Author
Dr. Alexandria Dobra-Kiel is Assistant Manager in Deloitte focussing on corporate strategy and behavioural analytics and a Guest Lecturer at Warwick Business School. She obtained her PhD from the University of Warwick and her MPhil from the University of Cambridge. Prior to Deloitte, Alexandra worked as a Senior Associate at Duff & Phelps, as an Analyst at Accenture and as a Seconded Analyst at the Accenture Institute for High Performance. She is invited speaker at leading business schools and firms and the recipient of a number of prestigious international honours and awards including Academy of Management, Falling Walls and the Swiss National Science Foundation.
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