Gestión de riesgos financieros. Experiencia en un banco latinoamericano1
Bibliographic record
Abstract
El presente documento busca presentar los principales conceptos de riesgos financieros presentes en la banca; en particular, se trabajará el caso de un banco peruano, considerando aspectos tales como la gestión de riesgos, Basilea III y la crisis económica internacional. El caso se desarrolla en el primer semestre del 2012 en el mercado peruano. The present document attempts to present the basic concepts of financial risk present in a bank, and in particular will present the case of a Peruvian bank, taking into accounts aspects such as risk management, the Third Basel Accord (Basel III) and the international financial crisis. The case was developed in the last quarter of 2012 in the Peruvian market. O presente documento procura apresentar os principais conceitos de riscos financeiros presentes na banca; irá trabalhar-se em particular com um banco peruano, considerando aspectos tais como a gestão de riscos, Basilea III e a crise económica internacional. O caso ocorre no primeiro semestre de 2012 no mercado peruano.
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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 | 0.001 | 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 | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".