Verhaltenspsychologisch begründete Wahrnehmungsfehler bei der Identifikation betrieblicher Risiken. Evidenzbasierte Entwicklung eines Risk Intake-Modells basierend auf theoretischen Grundlagen und empirischer Evaluierung

This thesis investigates the inner workings of the risk identification process. Risk identification is part of a broader framework, the risk management system. Organisations implement enterprise risk management (ERM) systems to adequately identify and manage risks and opportunities, which are often critical for continued success of the company. Spectacular failures and collapses of large organisations in the past were frequently linked to problems with the effectiveness of their ERM systems. Hence, legal requirements in Switzerland, Germany, and many other jurisdictions oblige firms to implement risk management at top management and supervisory levels.

Surprisingly though, globally accepted risk management standards and related norms do not specify precisely what must be done to identify risks and opportunities that the organisation faces. The standards and norms tacitly assume that risk identification works without the need for detailed guidance or elaboration. ERM systems, specifically the risk identification process, require human analysis with an inherent large degree of subjectivity and judgment. As such, the risk identification is prone to systematic bias in human judgment, which impacts the effectiveness of the process. To date, neither academic research nor practice-oriented literature investigate which biases might occur and how these impact the outcome of the risk identification process.

This research project draws on models from behavioural economics, decision theory, process management, and psychology to arrive at a detailed breakdown of the risk identification process. It also identifies possible biases that might play a role. Results from a systematic literature review are corroborated through a series of expert interviews. Experts are seasoned risk managers, corporate decision makers, and researchers in the risk management field. The result is a comprehensive insight into the risk identification process and a catalogue of applicable cognitive biases. Recommendations are provided on how organisations can mitigate these biases and thereby leverage the quality of the risk identification process.