Support of Risk Management Through Careful Selection of Anti-corruption Measures – a Critical Evaluation of Compliance Management Activities

Malcolm Gammisch, Signe Balina

Abstract


Purpose of the article: Organizations tend to apply Compliance Management System (CMS) as means to reduce risk. The fraud or corruption risk can be reduced by applying anti-corruption measures. The usefulness of these anti-corruption measures is not always questioned. Therefore measures might be applied which have little or no value in reality. Compliance Management Systems might be enhanced if hints can be found which measures are helpful for the organizations.
Methodology/methods: In a laboratory experiment possible cause-effect relations for anti-corruption measures were tested in an international setting. Populations from different countries were selected to test also differences in the national settings.
Scientific aim: The research aims at finding most effective anti corruption mechanisms and makes suggestions which kind of measures have a positive impact and which are negligible. This research presents the results of an experimental approach to further strengthen activity in the area of CMS. It highlights the use of CMS in order to conduct business through persons which are ethically sensitized.
Findings: The research highlights that not all applied measures do have a positive impact on decisions which have to be taken in ethical dilemma situations. Furthermore for single areas it became obvious that only specific measures do have an impact, general measures do not have an impact.
Conclusions: The effectiveness of CMS depends on a careful selection of the right activities. Nevertheless elements could be identified which are likely to have a stronger impact on the decision making than others. These should be in the focus when designing, evaluating and/or implementing a CMS. The approach should be embedded in an overall risk analysis to make sure that the relevant compliance risks are covered.

Keywords


anti-corruption measures, Compliance Management Systems, laboratory experiment

JEL Classification


C91, D73

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Online: 2015-04-13