{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:FYDNFOYZMQIMXB2UVHC2AEOE45","short_pith_number":"pith:FYDNFOYZ","canonical_record":{"source":{"id":"2107.13673","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2021-07-29T00:02:06Z","cross_cats_sorted":["q-fin.GN"],"title_canon_sha256":"be1391945752be3054347f3afc767e928e36cf89b2124880b94ff7866d7e6ab1","abstract_canon_sha256":"4f2f38a0fefe03f1bd22edb6867e82de2292ff1c7fec7cbb228a34265cb8f09e"},"schema_version":"1.0"},"canonical_sha256":"2e06d2bb196410cb8754a9c5a011c4e776bd39c1e7b767edd9bfa41f616021e0","source":{"kind":"arxiv","id":"2107.13673","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2107.13673","created_at":"2026-07-05T03:01:57Z"},{"alias_kind":"arxiv_version","alias_value":"2107.13673v2","created_at":"2026-07-05T03:01:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2107.13673","created_at":"2026-07-05T03:01:57Z"},{"alias_kind":"pith_short_12","alias_value":"FYDNFOYZMQIM","created_at":"2026-07-05T03:01:57Z"},{"alias_kind":"pith_short_16","alias_value":"FYDNFOYZMQIMXB2U","created_at":"2026-07-05T03:01:57Z"},{"alias_kind":"pith_short_8","alias_value":"FYDNFOYZ","created_at":"2026-07-05T03:01:57Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:FYDNFOYZMQIMXB2UVHC2AEOE45","target":"record","payload":{"canonical_record":{"source":{"id":"2107.13673","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2021-07-29T00:02:06Z","cross_cats_sorted":["q-fin.GN"],"title_canon_sha256":"be1391945752be3054347f3afc767e928e36cf89b2124880b94ff7866d7e6ab1","abstract_canon_sha256":"4f2f38a0fefe03f1bd22edb6867e82de2292ff1c7fec7cbb228a34265cb8f09e"},"schema_version":"1.0"},"canonical_sha256":"2e06d2bb196410cb8754a9c5a011c4e776bd39c1e7b767edd9bfa41f616021e0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:01:57.562826Z","signature_b64":"WrSaJUfYvDwtnmw2U20zmkCsF+BAgYL/WkYez/hpTji8aXffFB8EYAyvpXPT7UpvD9cbipFpjI2Y4FFU7K3UCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2e06d2bb196410cb8754a9c5a011c4e776bd39c1e7b767edd9bfa41f616021e0","last_reissued_at":"2026-07-05T03:01:57.562347Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:01:57.562347Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2107.13673","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T03:01:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QKDlrD3CfUfIElTPLWAlGJqBL1f4ySARalqD5JadDbut6vH0rbHHF1vTbGseCcblyyJKhIi654Vcl6lZWIZACg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T17:14:23.007767Z"},"content_sha256":"af02dddfc6f8ce4e5a3b870a14cfe864da641ecdd91c61bf09bdff319b246faf","schema_version":"1.0","event_id":"sha256:af02dddfc6f8ce4e5a3b870a14cfe864da641ecdd91c61bf09bdff319b246faf"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:FYDNFOYZMQIMXB2UVHC2AEOE45","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Relational Graph Neural Networks for Fraud Detection in a Super-App environment","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["q-fin.GN"],"primary_cat":"cs.LG","authors_text":"Alejandro Correa-Bahnsen, Andr\\'es Rodr\\'iguez-Rey, Cesar Charalla Olazo, Jaime D. Acevedo-Viloria, Jose Alberto Ramos, Luisa Roa, Soji Adeshina","submitted_at":"2021-07-29T00:02:06Z","abstract_excerpt":"Large digital platforms create environments where different types of user interactions are captured, these relationships offer a novel source of information for fraud detection problems. In this paper we propose a framework of relational graph convolutional networks methods for fraudulent behaviour prevention in the financial services of a Super-App. To this end, we apply the framework on different heterogeneous graphs of users, devices, and credit cards; and finally use an interpretability algorithm for graph neural networks to determine the most important relations to the classification task"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2107.13673","kind":"arxiv","version":2},"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/2107.13673/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T03:01:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/rBJY8pqDqVPYaGArRsium4ZBb2kVuXa+3yhZtqekHL8ApTVAAruL0YPssq9ht5VsZaB8BDqBLM3yOnEbMFPDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T17:14:23.008967Z"},"content_sha256":"9ac8f1b343a4864cd4b9a71de1cc23341f1b7c780892bd620ad7d9b1c5e28d6b","schema_version":"1.0","event_id":"sha256:9ac8f1b343a4864cd4b9a71de1cc23341f1b7c780892bd620ad7d9b1c5e28d6b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/FYDNFOYZMQIMXB2UVHC2AEOE45/bundle.json","state_url":"https://pith.science/pith/FYDNFOYZMQIMXB2UVHC2AEOE45/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/FYDNFOYZMQIMXB2UVHC2AEOE45/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-11T17:14:23Z","links":{"resolver":"https://pith.science/pith/FYDNFOYZMQIMXB2UVHC2AEOE45","bundle":"https://pith.science/pith/FYDNFOYZMQIMXB2UVHC2AEOE45/bundle.json","state":"https://pith.science/pith/FYDNFOYZMQIMXB2UVHC2AEOE45/state.json","well_known_bundle":"https://pith.science/.well-known/pith/FYDNFOYZMQIMXB2UVHC2AEOE45/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:FYDNFOYZMQIMXB2UVHC2AEOE45","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"4f2f38a0fefe03f1bd22edb6867e82de2292ff1c7fec7cbb228a34265cb8f09e","cross_cats_sorted":["q-fin.GN"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2021-07-29T00:02:06Z","title_canon_sha256":"be1391945752be3054347f3afc767e928e36cf89b2124880b94ff7866d7e6ab1"},"schema_version":"1.0","source":{"id":"2107.13673","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2107.13673","created_at":"2026-07-05T03:01:57Z"},{"alias_kind":"arxiv_version","alias_value":"2107.13673v2","created_at":"2026-07-05T03:01:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2107.13673","created_at":"2026-07-05T03:01:57Z"},{"alias_kind":"pith_short_12","alias_value":"FYDNFOYZMQIM","created_at":"2026-07-05T03:01:57Z"},{"alias_kind":"pith_short_16","alias_value":"FYDNFOYZMQIMXB2U","created_at":"2026-07-05T03:01:57Z"},{"alias_kind":"pith_short_8","alias_value":"FYDNFOYZ","created_at":"2026-07-05T03:01:57Z"}],"graph_snapshots":[{"event_id":"sha256:9ac8f1b343a4864cd4b9a71de1cc23341f1b7c780892bd620ad7d9b1c5e28d6b","target":"graph","created_at":"2026-07-05T03:01:57Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2107.13673/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large digital platforms create environments where different types of user interactions are captured, these relationships offer a novel source of information for fraud detection problems. In this paper we propose a framework of relational graph convolutional networks methods for fraudulent behaviour prevention in the financial services of a Super-App. To this end, we apply the framework on different heterogeneous graphs of users, devices, and credit cards; and finally use an interpretability algorithm for graph neural networks to determine the most important relations to the classification task","authors_text":"Alejandro Correa-Bahnsen, Andr\\'es Rodr\\'iguez-Rey, Cesar Charalla Olazo, Jaime D. Acevedo-Viloria, Jose Alberto Ramos, Luisa Roa, Soji Adeshina","cross_cats":["q-fin.GN"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2021-07-29T00:02:06Z","title":"Relational Graph Neural Networks for Fraud Detection in a Super-App environment"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2107.13673","kind":"arxiv","version":2},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:af02dddfc6f8ce4e5a3b870a14cfe864da641ecdd91c61bf09bdff319b246faf","target":"record","created_at":"2026-07-05T03:01:57Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"4f2f38a0fefe03f1bd22edb6867e82de2292ff1c7fec7cbb228a34265cb8f09e","cross_cats_sorted":["q-fin.GN"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2021-07-29T00:02:06Z","title_canon_sha256":"be1391945752be3054347f3afc767e928e36cf89b2124880b94ff7866d7e6ab1"},"schema_version":"1.0","source":{"id":"2107.13673","kind":"arxiv","version":2}},"canonical_sha256":"2e06d2bb196410cb8754a9c5a011c4e776bd39c1e7b767edd9bfa41f616021e0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2e06d2bb196410cb8754a9c5a011c4e776bd39c1e7b767edd9bfa41f616021e0","first_computed_at":"2026-07-05T03:01:57.562347Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:01:57.562347Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"WrSaJUfYvDwtnmw2U20zmkCsF+BAgYL/WkYez/hpTji8aXffFB8EYAyvpXPT7UpvD9cbipFpjI2Y4FFU7K3UCA==","signature_status":"signed_v1","signed_at":"2026-07-05T03:01:57.562826Z","signed_message":"canonical_sha256_bytes"},"source_id":"2107.13673","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:af02dddfc6f8ce4e5a3b870a14cfe864da641ecdd91c61bf09bdff319b246faf","sha256:9ac8f1b343a4864cd4b9a71de1cc23341f1b7c780892bd620ad7d9b1c5e28d6b"],"state_sha256":"946c84ca19af8f9a82cea7d8c1721654b821c36e1371f69f1b28617fb8493ce5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"l7w0r9jixg/2lfkF7/z9d/00gt1bR9yAJ7mc0rZpksgBVkfhw1YzdC0nSlJfGbBGZiB5ro73hSJl++anr9B6Cw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-11T17:14:23.017334Z","bundle_sha256":"b82abc64a206fdbe905feedd92bf1967e937a247bff67668f2aae87600341f7c"}}