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A Prediction-Postdiction Model of Risk Regulation and Governance in Banking: Infusing a Perspective from Psychology Theory
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Business Studies.
2017 (English)Conference paper, Oral presentation only (Refereed)
Abstract [en]

After the 2007–08 financial crisis, risk management failures in banks have drawn increasing regulatory attention, in turn promoting increasing risk-governance development. Regulatory efforts to refine policy temporarily leads to increased confidence by politicians and society in the risk management concept, but when a failure occurs, public intolerance increases dramatically, threating the legitimacy of financial institutions. The cyclical nature of this empirical phenomenon would seem to be closely related to how events are interpreted, not just by individuals but by society in general. Borrowing a term used in psychology, our understanding of this cyclical process may be improved by using what we might call the prediction-postdiction model of risk regulation and governance. The cycle has been the basis for considerable debate in public hearings, amongst regulatory bodies and in academic publications. Much of that debate has focused on the further development of formal policies, structures, and processes with very little attention given to the significance of individual actors or acknowledging the complexity and variation of practices in individual banks. In that void, multiple assumptions fill a space in order that politicians, the media, and even regulatory authorities, can reconcile predictive and post-hoc accounts. By drawing on psychological theory (cf. Hall 2016) and using empirical evidence from a case study of a large European bank, I propose that a better understanding of the crisis-regulation cycle can be achieved by applying the prediction-postdiction model. This may help us to see how some of the actions undertaken may be ineffective or even dysfunctional, as they build on assumptions which are dubious or wrong. The model can aid us in examining how the operation and effects of risk-management practices influence individual mental processes and behaviors over time. In doing so I offer deep empirical descriptions from a wide variety of individual perspectives on risk management's influence on behavior and how in aggregate this, in turn, influences organizational outcomes. Finally, I explain how these tentative findings can be used in future research.

Place, publisher, year, edition, pages
2017.
Keyword [en]
Accounting, Control, Regulation, Prediction, Postdiction, Risk
National Category
Business Administration
Research subject
Business Studies
Identifiers
URN: urn:nbn:se:uu:diva-242123OAI: oai:DiVA.org:uu-242123DiVA: diva2:782419
Conference
40th European Annual Congress (EAA)
Available from: 2015-01-21 Created: 2015-01-21 Last updated: 2017-10-31
In thesis
1. Regulation's Influence on Risk Management and Management Control Systems in Banks
Open this publication in new window or tab >>Regulation's Influence on Risk Management and Management Control Systems in Banks
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

This dissertation explores regulation’s influence on risk management and management control systems (MCS) in banks. The dissertation comprises of an introductory chapter, two published book chapters, one of which is an extensive literature review, and two working papers, presented at several European conferences. The overall objective of this dissertation is to explore how banks are responding to banking regulation in light of the 2007-08 financial crisis and what the implications of those responses are, particularly in relation to risk management and MCS, and their interactions. The overall research question is therefore: what influence does regulation have on risk management and management control systems in banks over time? The intended ambition is to contribute to existing knowledge on the relationship between bank regulation, risk management, and MCS by providing several practical and theoretical contributions. The dissertation employs an adapted theoretical framework and uses institutional theory and contingency theory to expose tensions between, the demands for uniformity residing in banking regulation, and the demands for uniqueness residing inside banks themselves as they seek to maintain control over the design and use of their organizational controls. The empirical material used in the longitudinal case study is gathered from a large European bank. The main findings of the dissertation are as follows. In Paper I, the findings show that banking regulation’s influence on risk management and management control is mixed, which in turn can influence risk management’s integration with MCS. The paper also finds that very little knowledge exists about regulation’s influence on risk management and MCS. In Paper II, the findings show that while regulatory influence in IT control has increased over time, banks continue to exercise significant influence over regulatory demands. In Paper III, the findings show how regulation’s influence varies considerably over time and that increased regulatory pressure can lead to a higher degree of integration between risk management and MCS across the three dimensions of integration. In Paper IV, the findings show how regulation’s influence is shaping the mental processes of management and employees, and can vary significantly based on several identified factors.

Place, publisher, year, edition, pages
Uppsala: Företagsekonomiska institutionen, 2017. 120 p.
Series
Doctoral thesis / Företagsekonomiska institutionen, Uppsala universitet, ISSN 1103-8454 ; 189
Keyword
Banking regulation, Risk management, Management control systems, Integration
National Category
Economics and Business
Research subject
Business Studies
Identifiers
urn:nbn:se:uu:diva-332037 (URN)978-91-506-2663-6 (ISBN)
Public defence
2017-12-12, Hörsal 2, Ekonomikum, Kyrkogårdsgatan 10, Uppsala, 13:15 (English)
Opponent
Supervisors
Available from: 2017-11-21 Created: 2017-10-23 Last updated: 2017-11-21

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