{ "schema_version": "1.0", "study_id": "S31", "run_id": "S31-02c309de-1e141502", "code_version": "02c309de271f6bb119a598b0c5972a3a697e553b", "source_sha256": { "research_program/__init__.py": "5abb4829b477fd3068ee4c11dad2b59cd33e90aad06a17a5e9fb2f840a75abf1", "research_program/evaluation.py": "09a5d060c34b8cd1e5a3330d90f5ff3e12adbca8cfe1ebe3297da2b91d227e45", "research_program/io.py": "16de123c16d80bce5eb8d6766224dec1729d7c00449c2528f2348d86ad68d35f", "research_program/validate.py": "3e6a591e2b77799bdf73683db438b2998e2e457340626c98b7ceed510ab3329e", "studies/S31/config.json": "8046884f44a808fd627634bdcdd498aebb0295b84bbb06f9e7d4dbf0d92d8af4", "studies/S31/ingest.py": "d8304d4085f153d0bd16142ee7e33277cd8223a357f574c5382c12d7144d2a6d", "studies/S31/models.py": "6ce90415fb9e790702f6f28209e853d6915ea6db3c4226994d6196ea487aa44f", "studies/S31/study.py": "7715cb9edd1be81a38b12af7f9d09116909539e7833ff08ef32a1567cb6b1b0d", "uv.lock": "97473cae5fb96bc8206d92cf3d53ab5c9fd5c6ece919d2fc4b24018dbb42c459" }, "evaluated_on": "2026-09-29", "data": { "source_url": "https://doi.org/10.57745/P0KHAG", "release": "CASdatasets 1.2-0, Recherche Data Gouv dataset version 1.1, July 12, 2024", "sha256": "1e141502a3477b4890a7be989b10fe6c4503170a4b846d2ba6c953763c0c7284", "license": "Etalab Open Licence 2.0 (dataset metadata); GPL >=2 (package code)", "citation": "Dutang, C.; Charpentier, A.; Gallic, E. Insurance dataset. Recherche Data Gouv. doi:10.57745/P0KHAG. CASdatasets 1.2-0, file doi:10.57745/ULR0ZA.", "file_sha256": { "freMTPL2freq": "61c079d31e76a4f09045326ccdbcab0180c32c90f7f42d7bb05192700797cb1f", "freMTPL2sev": "3bcf875b67ad23268698ad3e330365c4a4f41918e125f40d3a325786fa40e793" } }, "target": { "label": "Aggregate historical nominal claim euros per recorded policy-year", "estimand": "Conditional expected claim frequency times event-weighted conditional severity, or direct expected pure premium", "prediction_cutoff": "Assumed pre-claim policy characteristics; source timestamps cannot independently confirm field timing", "horizon": "Recorded exposure duration; approximate source years 2011–2013, no policy dates", "unit": "Policy; associated claims allocated together" }, "cohort": "SHA-256 policy-held-out final 20%; independent Ile-de-France geographic stress with region omitted from predictors", "samples": { "total": 677991, "total_claims": 26444, "test": 136271, "test_claims": 5426, "test_claiming_policies": 5114, "development": 405817, "development_claims": 15725, "validation": 135903, "validation_claims": 5293, "final_fit": 541720, "final_fit_claims": 21018 }, "models": [ { "id": "constant", "label": "Training portfolio mean", "specification": "Training portfolio frequency and severity means" }, { "id": "glm", "label": "Poisson–Gamma regression", "specification": "Frozen glm, selected setting 0.0001; training-only feature transforms and exposure/claim-count weights. See protocol." }, { "id": "tweedie", "label": "Direct Tweedie regression", "specification": "Frozen tweedie, selected setting 0.0001; training-only feature transforms and exposure/claim-count weights. See protocol." }, { "id": "boosting", "label": "Boosted frequency–severity", "specification": "Frozen boosting, selected setting 7; training-only feature transforms and exposure/claim-count weights. See protocol." } ], "metrics": [ { "model": "constant", "name": "tweedie_deviance", "estimate": 81.23300058, "unit": "exposure-weighted Tweedie deviance; power 1.5", "split": "final", "lower": 77.12185274, "upper": 86.27718101, "confidence": 0.95 }, { "model": "constant", "name": "absolute_error", "estimate": 303.63061343, "unit": "EUR per policy-year", "split": "final", "lower": 289.40308959, "upper": 321.61174559, "confidence": 0.95 }, { "model": "constant", "name": "predicted_observed_loss_ratio", "estimate": 1.16404229, "unit": "ratio", "split": "final", "lower": 1.03666082, "upper": 1.28907298, "confidence": 0.95 }, { "model": "glm", "name": "tweedie_deviance", "estimate": 78.42402834, "unit": "exposure-weighted Tweedie deviance; power 1.5", "split": "final", "lower": 73.70595849, "upper": 84.46266958, "confidence": 0.95 }, { "model": "glm", "name": "absolute_error", "estimate": 286.31459013, "unit": "EUR per policy-year", "split": "final", "lower": 271.80953275, "upper": 304.02161794, "confidence": 0.95 }, { "model": "glm", "name": "predicted_observed_loss_ratio", "estimate": 1.07429454, "unit": "ratio", "split": "final", "lower": 0.95713169, "upper": 1.19170978, "confidence": 0.95 }, { "model": "tweedie", "name": "tweedie_deviance", "estimate": 78.75876084, "unit": "exposure-weighted Tweedie deviance; power 1.5", "split": "final", "lower": 73.85859365, "upper": 85.14193018, "confidence": 0.95 }, { "model": "tweedie", "name": "absolute_error", "estimate": 294.17640629, "unit": "EUR per policy-year", "split": "final", "lower": 279.91229442, "upper": 311.89943245, "confidence": 0.95 }, { "model": "tweedie", "name": "predicted_observed_loss_ratio", "estimate": 1.13450912, "unit": "ratio", "split": "final", "lower": 1.00939219, "upper": 1.25991812, "confidence": 0.95 }, { "model": "boosting", "name": "tweedie_deviance", "estimate": 77.89351863, "unit": "exposure-weighted Tweedie deviance; power 1.5", "split": "final", "lower": 72.73815151, "upper": 84.71719032, "confidence": 0.95 }, { "model": "boosting", "name": "absolute_error", "estimate": 266.77147693, "unit": "EUR per policy-year", "split": "final", "lower": 252.33756184, "upper": 284.91651356, "confidence": 0.95 }, { "model": "boosting", "name": "predicted_observed_loss_ratio", "estimate": 0.93629276, "unit": "ratio", "split": "final", "lower": 0.83727518, "upper": 1.03754308, "confidence": 0.95 } ], "uncertainty": "Paired policy bootstrap: 500 final and geographic-stress draws, 250 per segment; 95% percentile intervals conditional on fitted models and the observed empirical loss tail. No independent-year or catastrophe uncertainty claim.", "assumptions": [ "Source risk fields are hypothetically available before claims; exact timing and claim-development maturity are not verified.", "Policy IDs define the sampling unit, but multiple policies may share unobserved drivers or shocks.", "The capped sensitivity limits each claim to EUR 50000 and changes the estimand; it is not a source contract limit.", "Expense loading is an explicit 0–50% scenario: estimated pure premium divided by one minus loading." ], "limitations": [ "Historical French motor data do not validate a current insurance price or rate filing.", "No policy dates support a temporal holdout or ultimate-claim development model.", "Nominal euros are not inflation-adjusted and some amounts reflect settlement conventions.", "Heavy losses and unobserved dependence can make empirical bootstrap intervals too narrow for future risk.", "Driver age and geography are descriptive benchmark features, not causal effects or a fairness certification.", "No policyholder eligibility or pricing action is taken; expense scenarios exclude taxes, profit, capital and regulatory constraints.", "Independent technical review is pending." ], "tables": { "audit": { "policies": 677991, "claims": 26444, "claiming_policies": 24944, "missing_cells": 0, "duplicate_frequency_rows": 0, "repeated_severity_rows_retained": 235, "unmatched_claims": 0, "count_disagreements": 0, "exposures_over_one_year": 1224, "exposure_years": 358482.83546298, "total_loss_eur": 59909216.5, "maximum_claim_eur": 4075400.56, "claims_above_cap": 88, "uncapped_loss_above_cap_eur": 17917329.27, "capped_total_loss_eur": 46391887.23, "largest_claim_share_of_loss": 0.06802627, "top_one_percent_claim_loss_share": 0.3801399 }, "tuning": [ { "model": "glm", "setting": 0.0001, "tweedie_deviance": 79.43051736, "absolute_error": 308.98431031, "predicted_observed_loss_ratio": 0.95585339 }, { "model": "glm", "setting": 0.01, "tweedie_deviance": 81.28373535, 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