Africa has a catalogue of challenges, and corruption is chief among them. But why is the scourge of corruption rife? At the recent World Economic Forum held in Durban, South Africa, African leadership advocate Lindiwe Mazibuko said that corruption on the continent was due to ‘the kind of people we are putting in positions of leadership’.
“We need to redefine leadership, and how we think about it, if we’re going to reach these high-minded goals we have set for ourselves,” she said.
We need to redefine leadership, and how we think about it, if we’re going to reach the high-minded goals we have set for ourselves.” Lindiwe Mazibuko
Data is a powerful tool for the prevention of corrupt practices and, more importantly, for creating predictive models that allow us to identify the possibility of a transgression. A forensic approach, coupled with knowledge of what incentivises corruption, will increasingly be necessary if Africa is serious about curbing the problem.
Modern history has taught us to view dishonesty from the singular prism of morality. And naturally, we respond to acts of corruption with outrage or disbelief on the basis of ethics. However, it is becoming clearer that it is of greater value if we start analysing dishonesty from an economic perspective.
It’s a Matter of Opportunity
On the road to clamping down on corruption with data analysis, we should first interrogate human behaviour. The school of behavioural economics, for instance, looks beyond the frame of morality to infer that deception is not based on character but rather on opportunity. If applied to price fixing, behavioural economics does not focus on the moral values of those involved, but on how their actions are likely to be incentivised.
Data is a powerful tool for the prevention of corrupt practices.
Generally, price fixers rationalise the overcharging of customers over a sustained period in the same way that the brain justifies one lie after the other. Given the opportunity, those involved are likely to hike prices and will repeatedly do so until they are outed. Our collective inquiry should then graduate from ‘How could they do such a thing?’ to a more appropriate ‘What did they stand to achieve by doing such a thing?’ Insights drawn from this exercise allow us to pre-empt wrongdoing by corporations.
A Foolproof Method of Detection
According to Manoj Chiba, data science lecturer at the Gordon Institute of Business Science and senior advisory consultant at Zetta Solutions, the key to understanding dishonesty lies in the idea of deviations from the norm, or what is expected.
“If an individual is cheating on his/her spouse of seven years, for example, they will begin changing their patterns of movement,” said Chiba. “This is often equated to coming home later, buying flowers when this is not the norm, or the converse – stopping the buying of flowers. The real idea behind this is that individuals are extremely habit-based and changes in these patterns can be seen in the data.”
This approach is also a trusted guide in the financial service industry. Special scrutiny is given when an individual with a sustained history of debt suddenly experiences a spike in their transactions. This deviation from the norm is easily tracked via an evident data pattern.
“This approach allows for linkages to be made across different types of cases and then allows for [in-]depth understanding; that is, how different aspects of corruption around an individual may tie together,” Chiba said.
Chiba added that in cases of public procurement, data can also be used to understand tender irregularities. Governments around the world are using data mining to investigate the general lengths of bidding processes. In instances where bid times are shorter than normal, it is a sure case that favouritism has been shown to award a tender – a longstanding prevalence in a country such as South Africa. This ultimately allows for recourse to be taken by authorities.
The multinational service firm Ernst and Young released a paper in 2015, which indicated that data could also be used to identify where and how companies spend money illicitly. It looked at the geographical use of money, the reasons for expenditure and by which employees.
A forensic outlook such as this reveals patterns in data that allow companies to drill down and understand the root causes of transactions and consequently identify high-risk profiles (individuals, in most cases), as well as work out how to monitor and take preventive rather than reactive action.
Introducing the Future
To invoke Mazibuko, Africans across the continent’s various regions need to reflect on whom they choose to lead them. This becomes more relevant as the world moves towards the fourth industrial revolution, when digital breakthroughs such as artificial intelligence and robotics will be the order of the day. We need to be led by young, nimble minds who believe in the veracity of data to solve our problems. These times of uncertainty call for it.