What Motives Do You See In Frauds?

The challenges in understanding why frauds occur and what triggers fraudulent behaviour has been the subject of research by many psychologists.

  • Can you say that sudden lifestyle changes in a person with ordinary means of income can denote something? That may not be fair to judge if he / she has inherited a legacy from ancestors.
  • Can you say that judgements based on bias and prejudice for a particular race, based on their skin colour, features, country of origin, religion or caste be pinned down for suspicion?
  • Have we not heard of icons of the industry fall from grace because they connived to defraud public money?

It is indeed a challenge to find out causal relationships between the human mind and actions that follow in different situations.

“Tone at the top” is the way a top management or the Board practices good governance and ethics in all its business dealings. Merely preaching through policy announcements is not enough to decide whether the working environment is non-conducive for misdeeds being committed and concealed by fraudsters. If the message from the top is loud, clear and consistent at all times, in all its processes and dealings with its customers, suppliers, Government and compliance agencies, then one can reasonably assume that the philosophy behind good corporate governance is prevailing in that organization.

But the above postulate is merely oversimplifying the answer as to why frauds occur even in the best run corporates? Surely the psychology of a person indulging in fraudulent activities goes beyond this. Whenever we talk of fraud being committed, we cannot ignore the human behaviour associated with it and the reasons for the same, in order to proactively manage the risk of fraud incidents. Forensic science is often times associated with the saying that “you have to think like a fraudster in order to catch one.”

I have been piqued by questions on who commits frauds. What is their compulsion? What behaviour do they bring to the organizations they work in? Is it possible or correct to diagnose past patterns and come to a conclusion about possible fraud scenarios? Is it ethical to study and profile an employee (psychology) or a group of employees (sociology) who connive and collaborate to defraud whenever possible (criminology)?

Firstly, what are the motivating factors that one can ascribe to fraudsters?

  1. He / she is driven by greed for money or materials to improve their lifestyle and want a quick way to make money. The insecurity of not being able to create wealth within a short time may push people to take advantage of situations.
  2. They observe the working environment and internal controls within the organization and find out loopholes which are favourable to them.
  3. Some think that the organization is so huge and cash-rich, that it is no big deal if it loses some money or materials.
  4. They think that they would not be discovered if they don’t repeat a pattern that analytical tools or even AI or machine learning cannot correlate.
  5. Not being found out makes it ‘cool’ for the perpetrator. There have been cases where many young developers hack passwords and re-write codes to their advantage without it being found out for a long time.
  6. Outside agencies like suppliers and customers lure the employees into dishonest practices that are covered up in collusion. Corruption and conflict of interest generally are rampant within business functions like purchase kickbacks from suppliers or customer discounts or write-offs.
  7. Bring themselves into trustworthy positions and gain the confidence of their partners, associates, customers, suppliers, employees and colleagues and whoever else matters in their business dealings, and by winning them over with their smooth talk.

Secondly, is whistle blowing or complaints against fraudulent transactions an effective method?

  1. The honest employees or small investors blowing the whistle, find it difficult to question unethical practices if the top management decides otherwise or fool the auditors under the garb of “creative accounting”. In such situations nobody can save the organization from succumbing to fraudulent practices. No amount of technology or tools that are deployed in the company to throw up alerts about possible frauds will help because in the ultimate analysis the fraud findings are not acted upon but thrown to the winds.
  2. If the main investor of an organization, the top management and / or the Board of Directors have an objective to make quick money through unethical business transactions, there is nothing you can do to find out until almost at the end of the loss event. They move with alacrity to wind up and abandon business when the first whiff of their nefarious deeds starts leaking into the public domain. (Case in point are bank scams like the PMC Bank, Yes Bank, etc.)
  3. Then of course there are the suave, well-educated top executives who engage in financial accounting frauds, either on their own (because they see the window of opportunity) or under pressure from their bosses to indulge in window-dressing annual accounts to defraud the public investors. (Case in point Satyam scam in India). The CFOs are after all employees bound to obey the dictates of the Board or CEO.

Widely disseminated by the Association of Certified Fraud Examiners (ACFE), the fraud triangle has three elements, viz. Perceived Incentives/ Pressures, Perceived Opportunities, and Rationalization of Fraudulent Behaviour (see Figure 1).

Most of the recruiters and human resource departments in organizations may be subconsciously bringing in “bias” and “first impressions” about potential recruits and managers may have their own ways of over-emphasis on character traits and under-estimating situational factors say, during a performance appraisal.

Thirdly, can we rely on Artificial Intelligence (AI in short) to bring in objective observations? This brings us to the question of ethics in AI profiling.

“The main purposes of an artificially intelligent agent probably involve sensing, modelling, planning and action, but current AI applications also include perception, text analysis, natural language processing (NLP), logical reasoning, game-playing, decision support systems, data analytics, predictive analytics, as well as autonomous vehicles and other forms of robotics (P. Stone et al. 2016).”

There is no doubt that AI plays a major advantage in well known, narrow situations like finding exceptions in transactions, looking at patterns that suggest financial frauds, etc.

But can we say the same that AI is accurate in facial recognition, speech and text analysis? Numerous studies have demonstrated the ease with which hackers could, in principle, fool face-and object-recognition systems with specific minuscule changes to images. (Imagine, for example, an airport security system that won’t let you board your flight because your face is confused with that of a criminal, or a self-driving car that, because of unusual lighting conditions, fails to notice that you are about to cross the street.).

Using historical data to train AI models may result in machines copying mistakes of the past. Machine learning will pick up past patterns of possible fraudulent events or transactions – they give you a statistical correlation as output, but would not give you the causes for the same – whether low-income employees indulged in fraud or whether it was collusion between employees or third parties or whether it was management conniving to perpetrate siphoning of funds.

Machine algorithms generally use private data in both in legal and ethical ways, but the problem starts when you have regulatory compliances like the GDPR or other data privacy laws and you need to audit not only to assure that data is secure but also to understand the AI applications and its algorithms. Take the case of Deep Learning (DL) which is advanced machine learning, where there is no human intervention and the algorithms are written and kept modified over every ‘learning’ by the computer itself – can the regulators have confidence when there is no idea on how AI is coming up with answers?

In summary, fraud investigation and analysis of behaviour needs not only objective evidences but also a subjective approach that differs from case to case. This is an evolving subject and we have to wait and see if human psychology, sociology and criminology gives a rational approach. Mere use of tools can only point to suspicions – but there would be cases of both false positives and false negatives.

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