The effect of financial technology on Islamic banks performance in Jordan: Panel data analysis
Bibliographic record
Abstract
Thanks to technological advancements in finance, Islamic banking might surely spread throughout developing nations and become more viable in the financial industry. The present investigation aims to thoroughly explore the impact of fintech upon Islamic banks and also investigate how fintech facilities affect Islamic banks performance within Jordan. A strategy known as a quantitative-descriptive inquiry was used in the inquiry. This study made use of yearly data (a panel data) that was collected from banking organizations using statistics based on yearly reports provided by Jordan Islamic bank, Safwa Islamic Bank and International Arab Islamic Bank listed alongside the Amman Stock Exchange between 2017 and 2021. The study discovered that financial performance of Islamic Banks was significantly impacted by Fintech services including online banking along with mobile banking. The increased beta value predicts that between 2017 to 2021, the financial prosperity of Arab Islamic International Bank, Jordan Islamic Bank, and Safwa Islamic Bank would be positively correlated with Fintech services. Additionally, it was discovered that SMS Financing and crowdsourcing had a detrimental impact on Islamic Banks financial performance. The investigation concludes by recommending that Islamic banking included in the study step up their attempts to educate the public about Islamic banking facilities.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".