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Record W3198610305

Financial Inclusion Plan – Progress and Prospects

2020· article· en· W3198610305 on OpenAlexaff
Prasanna Prakash

Bibliographic record

VenueSSRN Electronic Journal · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMicrofinance and Financial Inclusion
Canadian institutionsHorizon College and Seminary
Fundersnot available
KeywordsFinancial inclusionUnbankedBusinessFinanceFinancial servicesFinancial planFinancial systemInclusion (mineral)EarningsFinancial analysisAccounting managementAccountingAccounting information system
DOInot available

Abstract

fetched live from OpenAlex

Financial Inclusion is the most significant aspects in the present scenario for inclusive growth and development of the country. Financial inclusion can be described as the provision of affordable financial services, viz savings, credit, insurance services, access to payments and remittance facilities by the formal financial system to those who are excluded. Financial inclusion is considered as a vital indicator of development and wellbeing of a society. Financial Inclusion is considered as an effective means to sustainable economic growth and is intended to ensure that each citizen of the country is able to use their earnings a national financial resource for redeployment in productive sectors of the economy. Financial inclusion plan (FIP) is the Reserve Bank of India (RBI) designed financial inclusion measures to be implemented by commercial banks to provide banking services in unbanked villages. Under Financial inclusion plan, banks can provide its services in any selected mode including opening of a branch, business correspondents etc. The main objective of the present study is to examine the various financial inclusion plans initiated by the commercial banks and to evaluate the progress of financial inclusion in India. The study is based upon secondary data and it is analytical and descriptive in nature. The research paper concludes that the financial inclusion plans adopted by the commercial banks improved the financial inclusion and it helps in the economic development of the country.

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)0.001
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 score0.074
Threshold uncertainty score0.775

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.014
GPT teacher head0.205
Teacher spread0.191 · 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.

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

Citations2
Published2020
Admission routes1
Has abstractyes

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