What Is the Relationship between Corporate Social Responsibility and Financial Performance in the UK Banking Sector?
Bibliographic record
Abstract
This study rigorously investigates the intricate dynamics between Corporate Social Responsibility (CSR), quantified through Environmental, Social, and Governance (ESG) scores, and financial performance (FP), measured via the return on assets (ROA) and return on equity (ROE), within the UK banking sector. Our analysis is based on a comprehensive dataset from Bloomberg. This research encapsulates data from 32 banks publicly listed on the London Stock Exchange over a six-year span from 2017 to 2022. Employing panel data regression models while controlling leverage and bank size, we delve into the relationship between banks’ CSR engagements, as reflected in their ESG scores, and their financial outcomes. Our findings indicate a negative correlation between the ESG score and both the ROA and ROE, suggesting that elevated CSR commitments may inversely impact short-term financial returns. This finding not only challenges prevailing narratives within the sector but also fosters a crucial discourse on the balance between ethical banking practices and profitability. The implications of this research study are manifold, extending to policymakers, banking executives, and investors, suggesting a revaluation of CSR strategies in alignment with long-term value creation and sustainable banking. This study not only enriches academic discourse on CSR within the financial sector but also serves as a beacon for future inquiries into the evolving landscape of responsible banking, advocating for a nuanced understanding of CSR’s role in shaping the financial and ethical contours of the banking industry.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".