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Editors

Harry Cassin
Publisher and Editor

Andy Spalding
Senior Editor

Jessica Tillipman
Senior Editor

Richard L. Cassin
Editor at Large

Elizabeth K. Spahn
Editor Emeritus

Cody Worthington
Contributing Editor

Julie DiMauro
Contributing Editor

Thomas Fox
Contributing Editor

Marc Alain Bohn
Contributing Editor

Bill Waite
Contributing Editor

Shruti J. Shah
Contributing Editor

Russell A. Stamets
Contributing Editor

Richard Bistrong
Contributing Editor

Eric Carlson
Contributing Editor

Bill Steinman
Contributing Editor

How to read the 2019 TRACE Risk Matrix

We see it every year: A new edition of a corruption ranking is released, and the first thing people ask is which countries have moved up or down in ranking. It is common knowledge among compliance officers that a country’s position on such an index is just a starting point for a thorough corruption risk assessment, but there is still a danger that nuances will get lost in the high-level presentation of the data.

A helpful tonic can be to ask how those scores are calculated. In compiling our annual TRACE Bribery Risk Matrix — the 2019 edition of which was released last month — we proceed based on a theory about the factors that contribute to business bribery risk. The theory, rooted in research and experience, is that bribery risk is affected by four factors.

  • Opportunity: Most directly, there is a risk of bribery when representatives of a company engage in interaction with a government official. It is helpful to know roughly how much interaction with public officials to anticipate, what the person on the other side of the desk might be expecting, and what kind of leverage that official might hold by virtue of authority.
  • Deterrence: What deters corruption? First, social norms have been shown to have a significant effect on a person’s willingness to engage in bribery. Those norms can be gauged in different ways: how people respond when asked if bribery is acceptable, or if their actions show respect for government and its legitimacy. Second, there is the fear of being caught and punished. In the TRACE Matrix, we examine how effectively the government pursues criminal law enforcement, with emphasis on prosecuting public corruption.
  • Transparency: While opportunity and deterrence have a direct effect on the likelihood of encountering bribery, other factors have a more structural influence on whether corruption can take root. For example, does the government conduct itself transparently? Does it make a point of being ultra-secretive? Or is it more neutral, not going out of its way to either hide or publicize information? Analyzing a system’s approaches to transparency can indicate its priorities.
  • Oversight: For all its inherent value, transparency is most effective when the press is free to investigate and report. It also helps if there are people and civic institutions with the time and energy to act on that information and effectively restrain governmental abuse.

The Matrix considers each of these domains but does not treat them equally. Opportunity is given the most weight in calculating the final score, while deterrence receives the least, based in part on the difficulty of evaluating its effectiveness. The transparency and oversight domains are weighted equally, though not as heavily as opportunity.

While they are helpful, rankings and scores alone cannot tell the whole story about a particular country. Corruption develops differently depending on governmental and societal conditions. For example, countries with a democratic form of government tend to place more constraints on executive power, giving the population significant responsibility for detecting and resisting corruption through a free press and civil society institutions. Authoritarian governments may be less welcoming of public scrutiny but will be unfettered if they decide, for reasons of their own, to undertake anti-corruption efforts.

While it is difficult to quantify these contextual factors, we can leverage data to establish a sense of similarities between countries. This year, we introduced the Bribery Risk Typology, which groups jurisdictions according to factors like state fragility, degrees of democracy and autocracy, natural resources, economic size and complexity, and strength of enforcement and civil society. Crucially, the Typology recognizes that different factors are more relevant in different situations — for example, civil society has a greater effect on the corruption environment under a democracy, while in more authoritarian systems, the quality of enforcement becomes more important.

We can see this in action through a brief comparison. South Africa and Rwanda are both on the good side of medium-risk: With overall Matrix scores of 42 and 46 respectively, they rank first and third on the African continent. But there are significant differences in their domain scores:

Opportunity Deterrence Transparency Oversight
South Africa 65 33 24 27
Rwanda 36 36 50 68

 

In the Typology, South Africa is considered a stable democracy with a less complex economy and a civil society on the weaker end. With that understanding, the fact that South Africa is relatively strong on transparency becomes more important.

There may be greater opportunities for kleptocracy and grand corruption in South Africa than in countries with more diversified economies or stronger civil society institutions, but there is also a greater chance schemes will be exposed and addressed. Meanwhile, the country’s relatively poor regulatory efficiency keeps it from reaching a lower level of overall bribery risk.

Rwanda, on the other hand, is a fragile state with an autocratic government, but without the increased risk that accompanies extensive oil reserves. Its total score of 46 is slightly worse than South Africa’s 42, but note how it compares to countries of a similar profile on the Typology: Togo, Cameroon, Sudan, Ethiopia, Laos, Eritrea and Burundi — all medium-high or high-risk. Rwanda is the only one whose score is better than the global mean.

How can we account for that? Rwanda’s government services are a model of efficiency within the developing world and outshine many within the developed world as well. That efficiency is accompanied by a low bribery expectation score of 31. This suggests that, from a front-line government interaction perspective, Rwanda raises fewer alarms than most of its neighbors.

Looking solely at the overall rankings on an anti-corruption index does not provide this kind of insight. We would see both countries resting in the second quartile and might wonder from year to year whether they have moved up or down. But there is a lot more to think about and understand by exploring the data.

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