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Record W7097221693

WORKING PAPER SERIESFEDERAL RESERVE BANK of ATLANTA WORKING PAPER SERIES Technological Change, Financial Innovation, and Diffusion in Banking

2009· article· en· W7097221693 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicEconomic Growth and Development
Canadian institutionsnot available
Fundersnot available
KeywordsAtlantaFinancial innovationProduction (economics)WelfareFinancial servicesTechnological changeQuarter (Canadian coin)Position (finance)
DOInot available

Abstract

fetched live from OpenAlex

Abstract: This paper discusses the technological change and financial innovation that commercial banking has experienced during the past twenty-five years. The paper first describes the role of the financial system in economies and how technological change and financial innovation can improve social welfare. We then survey the literature relating to several specific financial innovations, which we define as new products or services, production processes, or organizational forms. We find that the past quarter century has been a period of substantial change in terms of banking products, services, and production technologies. Moreover, while much effort has been devoted to understanding the characteristics of users and adopters of financial innovations and the attendant welfare implications, we still know little about how and why financial innovations are initially developed. JEL classification: G21, O31, O33 Key words: technological change, financial innovation, banking The authors thank Pam Frisbee for research assistance. Helpful comments were provided by Allen Berger, Jose Negrin, and seminar participants at the Banco de México and Autonomous University of Mexico. The views expressed here are the authors ’ and not necessarily those of the Federal Reserve Bank of Atlanta or the Federal Reserve System. Any remaining errors are the authors’ responsibility.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.639
Threshold uncertainty score0.545

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.029
GPT teacher head0.222
Teacher spread0.193 · 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 designObservational
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

Citations0
Published2009
Admission routes1
Has abstractyes

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