{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:CPDV6HIQ4BB52TYP2YS6Y7NQ3K","short_pith_number":"pith:CPDV6HIQ","schema_version":"1.0","canonical_sha256":"13c75f1d10e043dd4f0fd625ec7db0da8385cd7a4d414d4e9e532729544a2f4b","source":{"kind":"arxiv","id":"2109.12546","version":1},"attestation_state":"computed","paper":{"title":"Synthetic Data Generation for Fraud Detection using GANs","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":["cs.CR"],"primary_cat":"cs.LG","authors_text":"Artur d'Avila Garcez, Charitos Charitou, Simo Dragicevic","submitted_at":"2021-09-26T09:51:44Z","abstract_excerpt":"Detecting money laundering in gambling is becoming increasingly challenging for the gambling industry as consumers migrate to online channels. Whilst increasingly stringent regulations have been applied over the years to prevent money laundering in gambling, despite this, online gambling is still a channel for criminals to spend proceeds from crime. Complementing online gambling's growth more concerns are raised to its effects compared with gambling in traditional, physical formats, as it might introduce higher levels of problem gambling or fraudulent behaviour due to its nature of immediate i"},"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":"2109.12546","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2021-09-26T09:51:44Z","cross_cats_sorted":["cs.CR"],"title_canon_sha256":"ceff2d97b81479f86671a763eaee13741c2bd6e7842c97d86e2353e1c617f3bb","abstract_canon_sha256":"dd338d3a0e74c7c39a22da54feef32170e20f8f35e433fae048306a4be1d988e"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:17:22.455773Z","signature_b64":"SIYSkp6zvsNlFFdI9w3bWQMmMtovOfMksnFJUjNldC+zG2Vy9z4aZfDRq7K9pYramcqZjj8lvLQJhGLIrHPuBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"13c75f1d10e043dd4f0fd625ec7db0da8385cd7a4d414d4e9e532729544a2f4b","last_reissued_at":"2026-07-05T03:17:22.455347Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:17:22.455347Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Synthetic Data Generation for Fraud Detection using GANs","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":["cs.CR"],"primary_cat":"cs.LG","authors_text":"Artur d'Avila Garcez, Charitos Charitou, Simo Dragicevic","submitted_at":"2021-09-26T09:51:44Z","abstract_excerpt":"Detecting money laundering in gambling is becoming increasingly challenging for the gambling industry as consumers migrate to online channels. Whilst increasingly stringent regulations have been applied over the years to prevent money laundering in gambling, despite this, online gambling is still a channel for criminals to spend proceeds from crime. Complementing online gambling's growth more concerns are raised to its effects compared with gambling in traditional, physical formats, as it might introduce higher levels of problem gambling or fraudulent behaviour due to its nature of immediate i"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2109.12546","kind":"arxiv","version":1},"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/2109.12546/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":"2109.12546","created_at":"2026-07-05T03:17:22.455405+00:00"},{"alias_kind":"arxiv_version","alias_value":"2109.12546v1","created_at":"2026-07-05T03:17:22.455405+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2109.12546","created_at":"2026-07-05T03:17:22.455405+00:00"},{"alias_kind":"pith_short_12","alias_value":"CPDV6HIQ4BB5","created_at":"2026-07-05T03:17:22.455405+00:00"},{"alias_kind":"pith_short_16","alias_value":"CPDV6HIQ4BB52TYP","created_at":"2026-07-05T03:17:22.455405+00:00"},{"alias_kind":"pith_short_8","alias_value":"CPDV6HIQ","created_at":"2026-07-05T03:17:22.455405+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2504.21574","citing_title":"Generative AI in Financial Institution: A Global Survey of Opportunities, Threats, and Regulation","ref_index":16,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/CPDV6HIQ4BB52TYP2YS6Y7NQ3K","json":"https://pith.science/pith/CPDV6HIQ4BB52TYP2YS6Y7NQ3K.json","graph_json":"https://pith.science/api/pith-number/CPDV6HIQ4BB52TYP2YS6Y7NQ3K/graph.json","events_json":"https://pith.science/api/pith-number/CPDV6HIQ4BB52TYP2YS6Y7NQ3K/events.json","paper":"https://pith.science/paper/CPDV6HIQ"},"agent_actions":{"view_html":"https://pith.science/pith/CPDV6HIQ4BB52TYP2YS6Y7NQ3K","download_json":"https://pith.science/pith/CPDV6HIQ4BB52TYP2YS6Y7NQ3K.json","view_paper":"https://pith.science/paper/CPDV6HIQ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2109.12546&json=true","fetch_graph":"https://pith.science/api/pith-number/CPDV6HIQ4BB52TYP2YS6Y7NQ3K/graph.json","fetch_events":"https://pith.science/api/pith-number/CPDV6HIQ4BB52TYP2YS6Y7NQ3K/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/CPDV6HIQ4BB52TYP2YS6Y7NQ3K/action/timestamp_anchor","attest_storage":"https://pith.science/pith/CPDV6HIQ4BB52TYP2YS6Y7NQ3K/action/storage_attestation","attest_author":"https://pith.science/pith/CPDV6HIQ4BB52TYP2YS6Y7NQ3K/action/author_attestation","sign_citation":"https://pith.science/pith/CPDV6HIQ4BB52TYP2YS6Y7NQ3K/action/citation_signature","submit_replication":"https://pith.science/pith/CPDV6HIQ4BB52TYP2YS6Y7NQ3K/action/replication_record"}},"created_at":"2026-07-05T03:17:22.455405+00:00","updated_at":"2026-07-05T03:17:22.455405+00:00"}