For most banks, the international financial crisis of 2007-2009 arrived suddenly and unexpectedly. Some argue that the banks failed because of excessive risk taking. Whether or not a bank failed, it would have had a certified enterprise risk management (ERM)[1] in place that included risk measurement (RM), as justified and promoted by regulatory bodies (Basel Accords[2]). Could the observed, excessive risk-taking amongst senior bank managers be blamed on the difficulty in dealing with the concept of RM in ERM – a concept developed for and refined in the financial sector (Chua, 1996; Porter, 1995; McGoun, 1992, 1995)? Over the past 30 years, regulatory organizations for banks have advocated an increase in the use of RM in banks. This has been successful in the sense that RM is well-established in regulatory documents for banks, such as the Basel Accords. Notably, some researchers have strongly criticized the theoretical underpinnings of RM (Broadbent et al., 2008; Chua, 1996; Keasey and Hudson, 2007; McGoun, 1992, 1995; McGoun et al., 2003), given the confusion between calculable risk and uncertainty (unique situations for which no reference classes with known probability distribution can be specified). The research literature that focuses on ERM partly supports and partly rejects the views of regulators and policymakers on the value of ERM in the financial industry (Baxter et al., 2013; Beasley et al., 2005; Hayne and Free, 2014; Hoyt and Liebenberg, 2011; Pagach and Warr, 2011). To understand the causes of the variety of uses and usefulness of ERM, however, the most promising track seems to be the elaboration of an understanding of influences on the use and usefulness of RM. RM is a newcomer in a world of sophisticated models, so there is need for further examination of the efforts to integrate RM with existing control systems. This research focuses on the usefulness of RM, and specifically on senior bank managers’ decision-making. RM has received little explicit research attention, with a few exceptions: Wahlström (2006, 2009), Mikes (2009, 2011) and Hall et al. (2015). According to Wahlström, the use of RM in banks is a consequence of the degree of centralization in the organizational structure: The more centralized the bank, the more difficult it is to use RM. In Mikes (2009, p. 22) model, the attitude toward numbers and calculations among senior bank managers explains the attitude toward quantifying risks and the use of RM in managing risk. Hall et al. (2015) discuss whether these difficulties in using RM may be attributable to the difficulties that managers experience in integrating these data in the judgmental process of their decision-making. Because RM should be integrated into a complexity of management control regimes, it is necessary not merely to study the influence of the organizational structure (Wahlström, 2006, 2009) or attitudes toward numbers (Mikes, 2009, 2011). The analysis should also be conducted from the perspective of senior bank managers and from their way of perceiving RM in their control context and their way of perceiving the concept of risk – not merely from the perspective of risk experts (Hall et al., 2015).