The fight against white collar crime is enhanced if organizations identify misconduct before it becomes a criminal act. In our latest Expert Talk, Dr. Eugene Soltes — author of “Why They Do It: Inside the Mind of the White Collar Criminal” — considers the crime-fighting role of data analytics and machine learning.
- Perpetrators of white collar crime often lack awareness of the harm that their actions cause, believing the crime is victimless because it involves big business.
- It is not uncommon for high integrity organizations that are overwhelmingly successful and compliant to harbor sub-cultures that engage in misconduct.
- As criminal behavior is not always obvious at the time, data analytics and machine learning can be powerful tools in pinpointing concerns in the fight against financial crime.
While in a traditional classroom or university setting, students are quick to condemn white collar crime. In the real world, a host of unexpected factors come into play.
Firstly, the crime being committed is often not as obvious as one might imagine. Moreover, individuals have to make decisions at speed, and often work in environments where homogenous corporate thinking may inadvertently stifle the opinion of individuals who would otherwise speak out against a particular course of action.
These factors allow white collar crime to flourish. A further fundamental driver is that those who commit this type of crime lack awareness of the actual harm that their crimes cause.
White collar criminals do not ever see the people they are hurting, and this makes it easier for them to perpetuate their crimes.
Financial crime is not victimless
Fueling the awareness gap is the pervasive assumption that financial crime only affects big business and is therefore ‘victimless’ — but this could not be further from the truth.
Refinitiv is committed to raising awareness of financial crime, and to this end our 2018 global financial crime survey analyzed responses from over 2,300 senior managers and C-suite individuals across 19 countries.
As part of the survey, we conducted interviews with leading NGOs to uncover the wider humanitarian consequences of financial crime across the world.
Our research revealed that financial crime aids and abets humanitarian tragedies such as modern slavery, in which approximately 40.3 million people worldwide are trapped.
There are a host of further examples of financial crime impacting individual lives, not least lost tax revenue that could have funded essential services such as education and healthcare.
Even given the awareness gap, why does white collar crime thrive in some organizations?
Dr. Eugene Soltes, who is Associate Professor of Business Administration at Harvard Business School and the author of Why They Do It: Inside the Mind of the White Collar Criminal, attempts to answer this question in the latest Refinitiv Expert Talk.
He says that it is not uncommon to observe high integrity organizations that are overwhelmingly successful and compliant, but nonetheless harbor sub-cultures that engage in misconduct.
Often these sub-cultures may involve several senior level individuals.
He comments: “This is where people can go home at the end of the day and they don’t think they’re mobsters. What they are involved in is corporate misconduct that they’re surrounded by and engaged in, and they don’t see the disconnect.”
This disconnect is further complicated by the fact that there are many examples in which organizational behavior crosses the ethical line, but is nonetheless legal.
Ethical leadership demands that decisions remain on the right side of ethics, regardless of legality, because reputational damage can be much more serious than regulatory consequences.
Where is the wrongdoing?
With hindsight, it is usually easy to spot decisions that were inherently bad, but potential wrongdoing is not always obvious at the time that a decision is being made.
It is therefore necessary for organizations to focus on how they can spot potential issues early in the game. This is where advances in data analytics can help.
With the ability to extract more useful information from the immediate environment, organizations can potentially become better at spotting potential problems.
By enabling companies to see trouble ahead, this technology empowers them to intercede before any transgression has actually occurred.
Data analytics and machine learning
Best practice tells us that there is no substitute for conducting thorough and rigorous due diligence, but the plethora of data available today also places a tremendous burden on often overstretched compliance teams.
Technology has become the key differentiator that sets successful organizations apart. Recent advances in data analytics and machine learning mean that we now have the tools to assess risk intelligently, reduce compliance burdens and lower costs.
Understanding potential misconduct and pinpointing it before it happens is a ‘needle in the haystack’ exercise. However, technology is stepping up to the plate by allowing firms to maximize their existing resources, work smarter and fight financial crime with renewed efficacy.
Read our Expert Talk: Seeing and avoiding the financial crime before you commit it