A big data state of mind

Epistemological challenges to accountability and transparency in data-driven regulation

Dados Bibliográficos

ID12080359
AutoresShirley Kempeneer (0000-0002-3228-0946, Tilburg University, autor correspondente)
Ano2021
Volume38
Fascículo3
Páginas101578-101578
Data de publicação2021-03-23
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoGovernment Information Quarterly (JOURNAL)
Identificadores do periódicoISSN: 0740-624X • E-ISSN: 1872-9517
EditoraElsevier BV (PUBLISHER)
DOI10.1016/j.giq.2021.101578
OpenAlexW3137762527
IdiomaEN
Citações recebidas6
Referências citadas42

In a sense, the 2008 financial crisis was a crisis of theory. Regulators, banks, and financial markets all had encompassing theoretical models about how the economy worked, but they all failed to predict the looming crisis. As such, regulators increasingly turn to big data to understand banks' health. Despite the prominence of big data in society, its use in the public sector remains grossly understudied. This paper explores the regulatory use of big data in the case of the EU-wide banking stress test, a key regulatory indicator. The paper draws on interviews with supervisors at the European Central Bank (ECB), European Banking Authority (EBA) and National Bank of Belgium (NBB), as well as with consultants and risk directors in Belgian banks, to explain how big data-driven regulation affects the relationship between regulators and regulated entities. It draws particular attention to the epistemological component of using large data sets in decision-making: a big data state of mind. The article more specifically shows how the underlying epistemology, rather than simply the bigness of datasets, affects the relationship between regulators and regulated entities, and the regulatory process at large. The paper concludes that regulators' big data state of mind calls for new practical and legal guidelines regarding the validity of data-driven knowledge claims. Moreover, it shows how accountability based on descriptive transparency no longer makes sense in the ‘age of the algorithm’, suggesting a shift towards relational transparency and joint knowledge production

Accountability · Big data · Business · Economics · Financial crisis · Political science · Public relations · State (computer science · Too big to fail · Transparency (behavior · Computer Science · Corruption and Economic Development · Crime, Illicit Activities, and Governance · Law · Regulation and Compliance Studies · Accounting