Regulatory risk disclosure in the banking industry: a scoring model approach

HOFINGER, Johannes (2021). Regulatory risk disclosure in the banking industry: a scoring model approach. Doctoral, Sheffield Hallam University.

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Link to published version:: https://doi.org/10.7190/shu-thesis-00383
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    Abstract

    Banks communicate their regulatory risk exposures through disclosure reports to market participants. These reports are based on the Basel III Pillar 3 guidelines, implemented in the European Union in form of the Capital Requirements Directive and Regulation (CRD IV/CRR). Agency theory views such disclosures as one viable option to reduce the information asymmetry between the banks’ managers and investors. Also, high-quality risk disclosures can strengthen the competitive position of banks through lower cost of capital and higher stock liquidity. It is therefore in the interest of banks to prepare high-quality disclosures and evaluate current disclosure practices. This thesis proposes a scoring model that measures the quality of bank regulatory risk disclosures and thereby supports banks and their stakeholders in their decision-making process on risk communication. The model builds on a two-dimensional framework including 1) a risk dimension comprising credit risk, market risk, operational risk, other risks including liquidity risk, and risk management in general; and 2) a quality dimension covering the criteria readability, comprehensiveness, meaningfulness, time comparability, and sector comparability. The quality criteria are operationalised and applied to the risk categories to facilitate the calculation of composite disclosure scores for regulatory risk disclosure reports of a sample of thirty large European-headquartered banks for the period 2016 to 2018. Prior research shows that disclosure quality depends on both qualitative and quantitative elements. Therefore, a multi-methods approach is applied in this thesis to build the scoring model based on a pragmatic research philosophy. In the research design, qualitative elements are captured with semantic content analysis, while quantitative elements are explored using factor analysis. The calculation of composite disclosure scores results in an average composite disclosure score of 3.86 (out of a maximum of 5) with a spread of about 20% to both sides. The analysis finds that reading difficulty across individual disclosure reports is generally very high, disclosure quantity varies substantially, banks are reluctant to provide forward-looking information, and only few information on time and sector comparability is included. This, therefore, makes it difficult for different stakeholders to benefit from bank disclosure reports and leaves ample space for banks to improve on their risk communication. The main academic contribution of this thesis is the development of a scoring model that captures the quality of regulatory risk disclosures in the EU banking industry. Such a practice-based model does not yet exist and has long been called for in prior literature. This research also introduces a comprehensive word-based approach that is an adequate proxy for measuring disclosure quality. Finally, the thesis adds to the understanding of how the term “information content” is interpreted differently across EU banks in the context of agency theory. 4 For the professional contribution, the proposed scoring model enables banks to analyse their current disclosure practices and points them to areas for improvements. Supervisory authorities and analyst houses also benefit from the scoring model through a more efficient and effective analysis of disclosure reports. Finally, consultancies and software firms can benefit from such a model to expand their offerings on business intelligence. JEL classification: M48 (Government Policy and Regulation) Keywords: Banking risk reporting; Regulation; Disclosure; Basel III Pillar 3; CRD IV/CRR; Quality scoring model.

    Item Type: Thesis (Doctoral)
    Additional Information: Director of studies: Nigel Garrow / Thesis Supervisors: Samah Issa and Eva Stumpfegger
    Research Institute, Centre or Group - Does NOT include content added after October 2018: Sheffield Hallam Doctoral Theses
    Identification Number: https://doi.org/10.7190/shu-thesis-00383
    Depositing User: Colin Knott
    Date Deposited: 10 Sep 2021 11:42
    Last Modified: 10 Sep 2021 11:45
    URI: http://shura.shu.ac.uk/id/eprint/29032

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