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Record W3121480601 · doi:10.2308/accr.2010.85.6.2011

An Empirical Analysis of Auditor Independence in the Banking Industry

2010· article· en· W3121480601 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Accounting Review · 2010
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAuditing, Earnings Management, Governance
Canadian institutionsMcMaster University
Fundersnot available
KeywordsAuditor independenceAccountingBusinessLoanAuditEarnings managementEarningsIndependence (probability theory)CorporationBanking industryExternal auditorAuditor's reportInherent risk (accounting)Financial systemFinanceInternal auditJoint audit

Abstract

fetched live from OpenAlex

ABSTRACT: We examine auditor independence in the banking industry by analyzing the relation between fees paid to auditors and the extent of earnings management through loan loss provisions (LLP). We also examine whether this relation differs across large banks whose managements are required under the Federal Deposit Insurance Corporation Improvement Act to evaluate internal control over financial reporting and whose auditors must attest to the effectiveness of such internal controls, and small banks that are not subject to those requirements. We find that unexpected auditor fees are unrelated to earnings management for large banks. For small banks, we find greater earnings management via under-provisioning of LLP by banks that pay higher unexpected total and nonaudit fees to the auditor. These results suggest that auditor fee dependence on the audit client is associated with earnings management via abnormal LLP and is a potential threat to auditor independence for small banks. Our findings are relevant to policymakers contemplating new regulations in light of the recent banking crisis.

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.

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)0.006
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.220
Threshold uncertainty score0.959

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.004
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.295
Teacher spread0.276 · 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