An Assessment of Sustainable Banking Performance in Sub‐Saharan Africa—Does Doing Good and Doing Well Go Hand in Hand?
Bibliographic record
Abstract
ABSTRACT This paper evaluates sustainable banking performance and its relationship with financial performance among 99 banks across six Sub‐Saharan Africa (SSA) countries. Prior research has shown that there are limited studies on benchmarking sustainable banking performance, and the relationship between sustainable banking and financial performance remains inconclusive. We conducted a benchmarking of sustainable banking performance using a 44‐indicator framework and a 4‐stage ranking system. Regression analysis is used to examine the relationship between sustainability and financial performance. Results indicate that most banks in SSA are in the early stages of adopting sustainable banking practices. A positive relationship exists between sustainable banking performance and financial performance. This finding aligns with good management theory. This win–win situation offers a compelling case for banks to integrate sustainability into their core strategies, creating economic value while addressing social and environmental challenges. Banking regulators can leverage sustainable banking to implement regulations that promote sustainable development in the region.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".