Credit Provision Strategy during Financial Crisis Using Bank Accounting Data
Bibliographic record
Abstract
This paper examines the changes in credit provision for the Greek Banking Sector before and during the financial crisis. Also, it investigates the impact of specific loan characteristics in shaping the overall interest rate of new and existing business loans. A data set with monthly accounting data of Greek Banks for the period January 2003 to June 2011 is utilized, thus incorporating the crisis effects. The study findings reveal the beginning of the credit crunch at the third quarter of 2009. As far as new loans are concerned, it was found that large loans are priced less than the small ones. Moreover, the results show the greater and positive contribution of small loans to the derivation of the total lending interest rate. Furthermore, it is found that the bargaining power of large borrowers during the crisis causes a negative impact of large loans on the total interest rate. Finally, it is shown that in the existing loan portfolio, the crisis significantly reduces the effect of short-term loans, while simultaneously intensifies the positive effect of medium and long-term loans. The findings have important managerial implications for bank managers and policymakers.
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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 | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 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".