MétaCan
Menu
Back to cohort
Record W4283011763 · doi:10.3390/jrfm15060270

Informal Finance: A Boon or Bane for African SMEs?

2022· article· en· W4283011763 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

VenueJournal of risk and financial management · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMicrofinance and Financial Inclusion
Canadian institutionsnot available
Fundersnot available
KeywordsCollateralFinanceAccess to financeContext (archaeology)BusinessInformal sectorFinancial servicesFinancial literacyStructured financeOrder (exchange)Developing countryMicrofinanceService (business)EconomicsEconomic growthMarketingFinancial crisis

Abstract

fetched live from OpenAlex

The aim of this study was to ascertain what can be done by the informal finance sector to close the credit gap in order to improve access to finance by SMEs. SMEs are the backbone of many economies as a result of generating employment and improving GDP. Despite playing such a major role in African economies, SMEs have been excluded from the financial systems. The informal finance sector plays a vital role by providing finance to small businesses. The study employed a literature survey with a primary focus on empirical studies that have been conducted in the African context. The study found that, generally, there are two circumstances under which most small businesses depend on informal finance. Firstly, informal finance is used as a last resort by SMEs that fail to access credit from the formal finance sector, owing to, among other issues, information asymmetry, lack of collateral security and perceived high default rates. Further, low financial literacy and the absence of credit bureaus in developing countries also contribute to the failure to access finance from formal institutions. Secondly, some entrepreneurs opt for informal finance even if they are eligible for formal finance as a result of its flexibility, convenience and simple administrative procedures. Notwithstanding the above benefits of informal finance, informal lenders are regarded as exploiting the clients by charging high interest rates. In addition, this sector suffers from limited resources; hence, it fails to fully service SMEs that require larger funding and are not eligible for formal finance. Invariably, all the studies that have been carried out confirm that access to finance is a major obstacle to the growth and development of SMEs. The development and empowerment of SMEs cannot be ignored as an important driver of the developmental agenda of most economies globally. The main policy recommendations that flow from this study, based on the policy syndrome of improving access to finance (financial inclusion) by the SME sector, include (1) the establishment of a suitable regulatory framework which will nurture the informal finance sector while promoting consumer protection, and (2) linking the formal and informal sector. On the other hand, SMEs should improve their risk management practices and also embrace FinTech platforms in order to access credit.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.910
Threshold uncertainty score0.751

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.015
GPT teacher head0.210
Teacher spread0.196 · 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