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Record W4415250587 · doi:10.1145/3757539

17 Years of Fintech for Financial Inclusion: A Systematic Review and Critical Value Analysis

2025· article· en· W4415250587 on OpenAlexaff
Christoph Becker, Samar Sabie

Bibliographic record

VenueProceedings of the ACM on Human-Computer Interaction · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinTech, Crowdfunding, Digital Finance
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsUnderpinningFinancial inclusionWork (physics)ReflexivityFinancial analysisThematic analysisValue (mathematics)Financial services

Abstract

fetched live from OpenAlex

The use of ICT tools and platforms to support the financial practices of underserved communities has been growing, but on-ground experiences have been mixed and sometimes detrimental. To achieve the potential benefits of technologies for financial inclusion, a deeper understanding of the design of digital financial interventions is essential. We systematically and critically reviewed studies that developed and implemented technological interventions for financial inclusion from 2007 to 2024. Our analysis examines the types of financial technologies developed, the devices and technical channels used, the research methodologies employed, and the target populations. Additionally, we conducted a reflexive thematic analysis to investigate the values underpinning these studies. By analyzing 30 articles, we interpreted a total of 13 value themes-including trust, accessibility, robustness, and compatibility. Our work highlights a complex interplay of values, structural considerations, technical attributes, financial practices, and economic factors that underlie the design of financial technologies.

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)0.000
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.051
Threshold uncertainty score0.513

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.002
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 head0.024
GPT teacher head0.314
Teacher spread0.290 · 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 designSystematic review
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
Published2025
Admission routes1
Has abstractyes

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