Does sustainability matter for Fintech firms? Evidence from United States firms
Bibliographic record
Abstract
Purpose This study aims to look at how financial technology (FinTech) companies adhere to sustainable standards in contrast to their counterparts. Following the validation of its new sustainability index, this study looks into the impact of sustainability on the stock performance of FinTech companies. Design/methodology/approach To efficiently test the hypotheses, sample has been collected from the Bloomberg of all FinTech and non-FinTech companies from the USA. The final sample comprises 1,712 company-year observations over the investigation period 2010–2019. The methodology entails ordinary least squares regressions and generalized panel methods of moments (GMM). Findings The results suggest that the developed sustainability index is a valid proxy for sustainability measures and directly relates to stock performance. Besides, the evidence indicates that non-FinTech companies display superior sustainability and stock performance compared to FinTech companies. The present results corroborate with stakeholder theory, which implies that quality sustainability performance will alleviate the agency issue and safeguard the shareholders’ interest. Research limitations/implications Despite the fact that it presents the limitation of not considering other dimensions of financial performance, this research is important as it highlights the sustainability practices by the FinTech and non-FinTech companies, offering insights to researchers, policymakers, regulators, financial reports users, investors, environmental union, employees, clients and society. Originality/value This paper is novel because it is unique in evaluating the sustainability practices in FinTech and non-FinTech firms.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.005 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".