Comparative analysis of evaluation models in insurance solvency
Bibliographic record
Abstract
Adoption and implementation of a new model for calculating the solvency of insurance at European level since 2016 by legislating Directive 2009/138/EC, known as Solvency II Directive, was the end of a long process of testing and analysis of insurance market European bodies conducted by the European Commission level. But before the actual implementation from 1 January 2016 the new solvency regime Solvency II on the European level, the European Commission has issued during 2015 a number of decisions on equivalence of the prudential regime and solvency for insurance and reinsurance headquartered central in third countries, which apply to group solvency calculation models different, depending on the rules of non-EU jurisdiction concerned. Thus, agreements were signed patterns equivalent solvency regime Solvency II with number eight countries: Bermuda, Switzerland, Australia, Brazil, Canada, Mexico, the US and Japan, for a period of ten years. After analyzing those models resulted primarily important risks in the standard formula calculation of solvency. As a result, there were three countries that are aligned in terms of calculating the solvency margin model Solvency II, while in the remaining countries the differences are due to insufficient coverage of the variables taken into account related mainly technical risk and market. In conclusion, the adoption of Solvency II regime in Europe is a challenge in terms of quality compared to the rest of the countries that apply different models of solvency.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".