{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:UAI42RWPQKW43DV4SFRS55Y3AJ","short_pith_number":"pith:UAI42RWP","schema_version":"1.0","canonical_sha256":"a011cd46cf82adcd8ebc91632ef71b026aa5130089f208c4c9dfc856f7641323","source":{"kind":"arxiv","id":"2303.01923","version":3},"attestation_state":"computed","paper":{"title":"Bayesian CART models for insurance claims frequency","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG","q-fin.ST","stat.AP"],"primary_cat":"stat.ML","authors_text":"Charles Taylor, Georgios Aivaliotis, Lanpeng Ji, Yaojun Zhang","submitted_at":"2023-03-03T13:48:35Z","abstract_excerpt":"Accuracy and interpretability of a (non-life) insurance pricing model are essential qualities to ensure fair and transparent premiums for policy-holders, that reflect their risk. In recent years, the classification and regression trees (CARTs) and their ensembles have gained popularity in the actuarial literature, since they offer good prediction performance and are relatively easily interpretable. In this paper, we introduce Bayesian CART models for insurance pricing, with a particular focus on claims frequency modelling. Additionally to the common Poisson and negative binomial (NB) distribut"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2303.01923","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2023-03-03T13:48:35Z","cross_cats_sorted":["cs.LG","q-fin.ST","stat.AP"],"title_canon_sha256":"6b3b9ffe0c803ec2cae3b8b4e14989149912a4a132b824abd456c5c2bb160999","abstract_canon_sha256":"6faf52eb4ea25950138bf327d569b3e445d5e424afe3163fd371c85a8119d3b1"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:18:56.413387Z","signature_b64":"MKUZacabwTDaNMV4Mc3DTJcUleNxo1IINEgxWG7tW35z4380wHy6d2JdHFlmvhFjYVIfk7hnVIkj9+cTqW3LAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a011cd46cf82adcd8ebc91632ef71b026aa5130089f208c4c9dfc856f7641323","last_reissued_at":"2026-07-05T07:18:56.412792Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:18:56.412792Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Bayesian CART models for insurance claims frequency","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG","q-fin.ST","stat.AP"],"primary_cat":"stat.ML","authors_text":"Charles Taylor, Georgios Aivaliotis, Lanpeng Ji, Yaojun Zhang","submitted_at":"2023-03-03T13:48:35Z","abstract_excerpt":"Accuracy and interpretability of a (non-life) insurance pricing model are essential qualities to ensure fair and transparent premiums for policy-holders, that reflect their risk. In recent years, the classification and regression trees (CARTs) and their ensembles have gained popularity in the actuarial literature, since they offer good prediction performance and are relatively easily interpretable. In this paper, we introduce Bayesian CART models for insurance pricing, with a particular focus on claims frequency modelling. Additionally to the common Poisson and negative binomial (NB) distribut"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2303.01923","kind":"arxiv","version":3},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2303.01923/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2303.01923","created_at":"2026-07-05T07:18:56.412860+00:00"},{"alias_kind":"arxiv_version","alias_value":"2303.01923v3","created_at":"2026-07-05T07:18:56.412860+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2303.01923","created_at":"2026-07-05T07:18:56.412860+00:00"},{"alias_kind":"pith_short_12","alias_value":"UAI42RWPQKW4","created_at":"2026-07-05T07:18:56.412860+00:00"},{"alias_kind":"pith_short_16","alias_value":"UAI42RWPQKW43DV4","created_at":"2026-07-05T07:18:56.412860+00:00"},{"alias_kind":"pith_short_8","alias_value":"UAI42RWP","created_at":"2026-07-05T07:18:56.412860+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/UAI42RWPQKW43DV4SFRS55Y3AJ","json":"https://pith.science/pith/UAI42RWPQKW43DV4SFRS55Y3AJ.json","graph_json":"https://pith.science/api/pith-number/UAI42RWPQKW43DV4SFRS55Y3AJ/graph.json","events_json":"https://pith.science/api/pith-number/UAI42RWPQKW43DV4SFRS55Y3AJ/events.json","paper":"https://pith.science/paper/UAI42RWP"},"agent_actions":{"view_html":"https://pith.science/pith/UAI42RWPQKW43DV4SFRS55Y3AJ","download_json":"https://pith.science/pith/UAI42RWPQKW43DV4SFRS55Y3AJ.json","view_paper":"https://pith.science/paper/UAI42RWP","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2303.01923&json=true","fetch_graph":"https://pith.science/api/pith-number/UAI42RWPQKW43DV4SFRS55Y3AJ/graph.json","fetch_events":"https://pith.science/api/pith-number/UAI42RWPQKW43DV4SFRS55Y3AJ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/UAI42RWPQKW43DV4SFRS55Y3AJ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/UAI42RWPQKW43DV4SFRS55Y3AJ/action/storage_attestation","attest_author":"https://pith.science/pith/UAI42RWPQKW43DV4SFRS55Y3AJ/action/author_attestation","sign_citation":"https://pith.science/pith/UAI42RWPQKW43DV4SFRS55Y3AJ/action/citation_signature","submit_replication":"https://pith.science/pith/UAI42RWPQKW43DV4SFRS55Y3AJ/action/replication_record"}},"created_at":"2026-07-05T07:18:56.412860+00:00","updated_at":"2026-07-05T07:18:56.412860+00:00"}