The impact of the diffusion of a financial innovation on company performance: an analysis of SWIFT adoption
Bibliographic record
Abstract
How does a major financial network innovation influence firm performance? Despite much speculation we have little hard quantitative evidence about the impact of technology diffusion in financial services. In this paper we use the entire adoption history for SWIFT (the Society for Worldwide Interbank Financial Telecommunication- standards provider and messaging carrier) matched to bank-level panel data for the US, Canada and 27 European countries. Our dataset covers almost 7,000 banks (including 1,689 SWIFT adopters) between 1998 and 2005. We find that adoption appears to have large effects on profitability, but it takes several years before any positive return is discernible, consistent with the idea of significant complementarities between new technologies and firm organization. The profitability effect operates by both raising sales and decreasing operating costs and is greater for smaller firms than larger firms. Although the long-run effects are similar, US and UK banks appear to reap the benefits from adoption more quickly than their Continental European counterparts. This is consistent with the idea that the impact of information and communication technologies is stronger in the US than Europe due to lower adjustment costs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".