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Banking and the Conduct Risk Conundrum: What is the Solution?

Conduct-driven scandals continue to plague the banking sector, despite punitive fines in excess of $345 billion since the Financial Crisis, and attendant public outrage. Extensive regulation has been introduced in an attempt to prompt ethical behavior, and organizations have responded with reactive measures. What is needed instead is a proactive approach to the culture and conduct risk conundrum.


Misconduct and related scandals have been an unfortunate feature of the financial industry for decades, in every key financial market. Today, however, this challenge is receiving unprecedented attention: from customers, employees, shareholders, regulators, policy-makers, and society more broadly. Consider three prominent recent examples.

Perhaps most poignantly, at present, Australia has just endured a year-long investigation into misconduct among its banks, known as the Royal Commission into Misconduct in the Banking, Superannuation and Financial Services Industry. To say that the findings were upsetting is an understatement.

As detailed in its Final Report, released on February 1st, misconduct among the Australian banks in recent years has been fairly shocking in both nature and degree: charging fees for no service; plundering the accounts of the dead for “financial advice” and even life insurance (without hint of irony); and more. High profile hearings that preceded the production of the Report have led to public uproar, punitive fines, rolling heads, and a reshaping of the Australian regulatory apparatus.

Events in Australia take place against a backdrop of misconduct scandals in several other major markets. As the Commission’s Report was being released Down Under, in the U.S., the headlines were filled with news that Goldman Sachs might withhold or even claw back millions in remuneration awarded to senior executives, to include former CEO Lloyd Blankfein, following the “1MDB scandal” in Malaysia, which involved alleged fraudulent activity on the part of Goldman employees.

And, at about the same time, in Europe, eight global banks were accused by the EU Commission of collusion in rigging the sovereign bond market. Investigations continue but billions in fines are expected. Again, this comes as a consequence of alleged misconduct that leadership failed to prevent.

Misconduct in the banking and finance sector may not necessarily be a larger issue now than it has been in years past, but today attention to such concern certainly seems to have reached new levels and, more and more so, firm culture is looked to as an explanation.



As former NY Fed president William Dudley has styled it, “Context drives conduct.”

While “tone from the top” may be an important driver of what employees believe to be acceptable behavior, the far larger driver is the behavioral expectation of peers. Tone from the top acts a bit like the speed-limit sign at the side of the highway. How fast one actually drives, however, is largely a function of how quickly the cars around you are moving. Firm culture operates in a similar manner.

The ability to manage conduct successfully therefore turns on an ability to properly understand the underlying cultural drivers of that behavior. As leading network scientist Nicholas Christakis offers in a recently published column, “Dishonesty, proscribed behaviors, and fraud may well spread via processes of social contagion, like all other observed human behaviors. It is not about bad apples; it is about bad barrels. People will behave in a risky manner when they perceive that their peers are doing similarly.”
In the last few years it has become increasingly clear that regulators understand this, and they have begun to call for “culture audits” as a means of proactively anticipating misconduct and, thus, off-setting the risk thereof.



If culture is to be managed it must first be made “visible” and actionable.

In a recent speech, the NY Fed’s head of supervision asked how data analytics tools might be helpful in this regard. “The potential of big data analytics to revolutionize approaches in many areas of business has been talked about for years, and is now beginning to become a reality,” he argued, anticipating that “we might see firms routinely leverage broader data to make stronger predictions about potential misconduct risk.”

Computational social science has much to offer us here. It is well established that interpersonal trust and perceived ‘psychological safety’ among employees and managers is key to creating high-performance teams within the workplace. Computational social science techniques allow us to measure and map these interpersonal trust dynamics, sifting signal from company data sets to produce heretofore unavailable insights into the drivers of employee conduct.

RegTech firms like Starling are putting these new computational capabilities to work, building tools that provide management with actionable insights by sifting through massive company data sets to distill “digital artifacts” that point to likely behavior and performance outcomes, with high predictive reliability.

Through such data analytics, company leadership is positioned to engage proactively to anticipate, and shape, culture and the behavioral consequences that impact the organization and its stakeholders.