MétaCan
Menu
Back to cohort
Record W4380482049 · doi:10.6000/1929-4409.2020.09.312

Bank Deposit and Credit Policy Management in the Field of Individual Customer Service

2022· article· en· W4380482049 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal of Criminology and Sociology · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Systems and Logistics Management
Canadian institutionsnot available
Fundersnot available
KeywordsCustomer satisfactionBusinessService qualityService (business)SWOT analysisQuality (philosophy)Customer relationship managementWork (physics)The InternetMarketingComputer scienceEngineering

Abstract

fetched live from OpenAlex

The article is devoted to the problem of individual customer service quality improvement in the field of provided deposit and credit services. This problem is a priority in determining any commercial bank strategy, since both deposit and credit policies determine the effectiveness of a credit institution development, which largely depends on the level of customer satisfaction. This study aims to determine the management aspects of the deposit and credit policy improvement in the field of commercial bank customer servicing. In the course of the work, they used the elements of system analysis, statistical research methods (summary and grouping, calculation of average values), and SWOT analysis. To assess customer satisfaction, the authors studied the Internet reviews of the largest regional bank of the Primorsky Territory of Russia - PJSC SKB of Primorye "Primsotsbank". The use of the indicated methods in the study made it possible to assess the quality of services provided to clients, identify the problems in their service sector, and develop the measures for their elimination. The results obtained are the basis for making managerial decisions to improve the deposit and credit policy of the studied bank and can be used in commercial banks' practice.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.425
Threshold uncertainty score0.200

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.066
GPT teacher head0.298
Teacher spread0.231 · 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