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Record W3125796779 · doi:10.5539/ijef.v7n9p219

The Impact of Information Security on Banks’ Performance in Egypt

2015· article· en· W3125796779 on OpenAlexvenueno aff
Nader Alber, Myvel Nabil

Bibliographic record

VenueInternational Journal of Economics and Finance · 2015
Typearticle
Languageen
FieldComputer Science
TopicBlockchain Technology Applications and Security
Canadian institutionsnot available
Fundersnot available
KeywordsInformation security management systemBusinessAsset (computer security)Asset qualityITIL security managementProfitability indexConventional PCIInformation securityInformation security managementLoanFinanceQuality (philosophy)AccountingComputer securityComputer scienceCapital adequacy ratioSecurity information and event managementSecurity serviceCloud computing securityIncentiveEconomics

Abstract

fetched live from OpenAlex

This paper attempts at investigating the impact of information security on the performance of Egyptian banks. This has been conducted using a sample of 13 banks (out of 32 banks), during 2013. Information security is measured by the degree of the application of ISO 27001 and PCI-DSS standards on Egyptian Banks, while banks' performance is measured by indicators of profitability and asset quality. ISO 27001 specifies the requirements for establishing, implementing, operating, monitoring, reviewing, maintaining and improving a documented Information Security Management System (ISMS). Besides Payment Card Industry Data Security Standards (PCI-DSS) is a comprehensive standard is intended to help organizations protectively protect customer account data. Results indicate that implementation of ISO 27001 standards may affect profitability indicators as measured by “Return on Capital”, while implementation of PCI-DSS standard may affect asset quality as measured by “Non-Performing Loan Ratio”.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.022
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.010
GPT teacher head0.237
Teacher spread0.227 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations11
Published2015
Admission routes1
Has abstractyes

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