MétaCan
Menu
Back to cohort
Record W2301921224

Bancassurance: Leveraging on the Synergy between Banking and Insurance Industry

2010· article· en· W2301921224 on OpenAlexaboutno aff
Ajai Kumar Singhal, Rohit Kumar Singh

Bibliographic record

VenueSSRN Electronic Journal · 2010
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicInsurance and Financial Risk Management
Canadian institutionsnot available
Fundersnot available
KeywordsBancassuranceLeverage (statistics)BusinessInsurance industryWork (physics)Banking industryLife insuranceCommerceFinanceKey person insuranceIndustrial organizationInsurance policyRisk poolActuarial scienceEngineering
DOInot available

Abstract

fetched live from OpenAlex

By opening the economy for foreign players to enter and compete in the market, numerous challenges and opportunities beckoned the domestic players in India. The banking and insurance sectors also got affected by this and started to reenergize their work and revamped the whole system to face the situation. They also initiated business into some new areas and as a result, both these sectors came together to leverage the opportunities available to them so as to reap the prospects of individual specializations. Thus, the concept of bancassurance emerged. It is the detailed agreement and arrangement between the banks and insurance company in which the insurance products are distributed properly by effectively utilizing the banks distribution channels. It is regarded as a one-stop shop where a complete range of banking and insurance products are made available. It originated in France and is a new concept in India and Asia, but it has its success story in Europe, the USA and Canada. This research paper is an attempt to assess the vital aspects of bancassurance and evaluate how this synergy is leveraging benefits for banking and insurance.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
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 score0.131
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.005
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 head0.017
GPT teacher head0.212
Teacher spread0.195 · 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 designTheoretical or conceptual
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

Citations7
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueSSRN Electronic JournalSame topicInsurance and Financial Risk ManagementFrench-language works237,207