An Asset and Liability Management System for Towers Perrin-Tillinghast
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Towers Perrin-Tillinghast employs a stochastic asset-and-liability management system for helping its pension plan and insurance clients understand the risks and opportunities related to capital market investments and other major decisions. The system has three major components: (1) a stochastic scenario generator (CAP:Link); (2) a nonlinear optimization simulation model (OPT:Link); and (3) a flexible liability- and financial-reporting module (FIN:Link). Each part improves over existing technology as compared with traditional actuarial approaches. The integrated investment system links asset risks to liabilities so that company goals are best achieved. For example, US WEST saved $450 to $1,000 million in opportunity costs in its pension plan by following the advice of the asset-and-liability system.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 it