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Record W2387248080

Business Continuity Model: A Reality Check for Banks in India

2006· article· en· W2387248080 on OpenAlexvenueno aff
Sunil Rai, Lakshmi Mohan

Bibliographic record

VenueThe Journal of Internet Banking and Commerce · 2006
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSupply Chain Resilience and Risk Management
Canadian institutionsnot available
Fundersnot available
KeywordsOperationalizationComputer scienceVariety (cybernetics)Business continuityVulnerability (computing)Business modelProcess managementResilience (materials science)Plan (archaeology)Event (particle physics)Action (physics)Action planKnowledge managementRisk analysis (engineering)BusinessComputer securityMarketingManagementArtificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

We have developed a framework to address the issues related to Business Continuity Management (BCM) and applied it to banks in India. The paper discusses the need for BCM in banks and presents a model to design, implement, operationalize and assess a business continuity plan. The proposed BCM model covers five components relating to the Organizational Soft issues, Processes, People, Technology and Facilities Management; and, defines a variety of metrics to measure the “Resilience” and “Vulnerability” of a bank in the event of business disruptions. The model has been applied to conduct a “reality check” of BCM implementation in 8 large and 14 medium/small banks in India. The value of the model lies in its ability to identify the gap areas for bank management to take corrective action.

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)0.004
metaresearch head score (Gemma)0.012
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.078

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0020.002
Scholarly communication0.0040.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.247
Teacher spread0.230 · 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

Citations5
Published2006
Admission routes1
Has abstractyes

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