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Record W2898700353 · doi:10.1108/ara-03-2018-0068

Client importance, bank risk, and systemic risk

2018· article· en· W2898700353 on OpenAlexaff
Li Li, Mary Ma, Victor Song

Bibliographic record

VenueAsian Review of Accounting · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAuditing, Earnings Management, Governance
Canadian institutionsUniversity of British ColumbiaYork University
Fundersnot available
KeywordsSystemic riskBusinessAuditAccountingRisk assessmentFinancial risk managementRisk managementEarningsOriginalityFinancial crisisFinanceEconomicsPsychology

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to investigate the effects of audit client importance on future bank risk and systemic risk in US-listed commercial banks. Design/methodology/approach The authors use archival research method. Findings The authors mainly find that client importance is negatively related with future bank-specific crash risk and distress risk, and also with sector-wide systemic crash risk and systemic distress risk in the future. The authors also report some evidence that these relations become more pronounced during the crisis period than during the non-crisis period. Moreover, the effect of client importance on systemic risk is found to strengthen in banks audited by Big-N auditors, by auditors without clients who restate earnings, and by auditors with more industry expertise. Research limitations/implications These findings contribute to the auditing and systemic risk literature. Practical implications This study has implications for regulating the banking industry. Originality/value This study provides original evidence on how client importance affects bank-specific risk and systemic risk of the banking industry.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.672
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.006
GPT teacher head0.219
Teacher spread0.213 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2018
Admission routes1
Has abstractyes

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