{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:M53YJEYHWYUYTFJVSR4WGLO5AT","short_pith_number":"pith:M53YJEYH","canonical_record":{"source":{"id":"1907.01800","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-fin.RM","submitted_at":"2019-07-03T09:00:00Z","cross_cats_sorted":["q-fin.GN"],"title_canon_sha256":"fd644384bde305d5c001e306b804054c36e3fda0a119ba771f002dffce1e1408","abstract_canon_sha256":"353d10c0b809361166ae847a0318d831d2f09b4a6ebacedad67f2e6db52fb44c"},"schema_version":"1.0"},"canonical_sha256":"6777849307b6298995359479632ddd04c4509a8a43b628461c34d8f9bcb1b5c0","source":{"kind":"arxiv","id":"1907.01800","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.01800","created_at":"2026-05-17T23:41:35Z"},{"alias_kind":"arxiv_version","alias_value":"1907.01800v1","created_at":"2026-05-17T23:41:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.01800","created_at":"2026-05-17T23:41:35Z"},{"alias_kind":"pith_short_12","alias_value":"M53YJEYHWYUY","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_16","alias_value":"M53YJEYHWYUYTFJV","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_8","alias_value":"M53YJEYH","created_at":"2026-05-18T12:33:21Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:M53YJEYHWYUYTFJVSR4WGLO5AT","target":"record","payload":{"canonical_record":{"source":{"id":"1907.01800","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-fin.RM","submitted_at":"2019-07-03T09:00:00Z","cross_cats_sorted":["q-fin.GN"],"title_canon_sha256":"fd644384bde305d5c001e306b804054c36e3fda0a119ba771f002dffce1e1408","abstract_canon_sha256":"353d10c0b809361166ae847a0318d831d2f09b4a6ebacedad67f2e6db52fb44c"},"schema_version":"1.0"},"canonical_sha256":"6777849307b6298995359479632ddd04c4509a8a43b628461c34d8f9bcb1b5c0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:41:35.011580Z","signature_b64":"u04ONjFr9AfnadZCHnt3fL8FExY3Si709/B1nX8S3xP9X+j8kYnHUyMVjmu8B4w0a0aTaZnwtF4NGfLpLMq1Aw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6777849307b6298995359479632ddd04c4509a8a43b628461c34d8f9bcb1b5c0","last_reissued_at":"2026-05-17T23:41:35.010812Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:41:35.010812Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1907.01800","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:41:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EMmin+Gk3F5dDgTZHOvjfdF5kCFsYd82t8dRa9dUctGv6mL9fnzWYQ54Rn/MYq91nInHDFrCW3ZpaOP142wvCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T03:31:36.004398Z"},"content_sha256":"36c87233bf3d04346285fb78b3ce3cbdbc2a5e913f64b7fc8d5b9cddbcfbf5cb","schema_version":"1.0","event_id":"sha256:36c87233bf3d04346285fb78b3ce3cbdbc2a5e913f64b7fc8d5b9cddbcfbf5cb"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:M53YJEYHWYUYTFJVSR4WGLO5AT","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"P2P Loan acceptance and default prediction with Artificial Intelligence","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["q-fin.GN"],"primary_cat":"q-fin.RM","authors_text":"Jeremy D. Turiel, Tomaso Aste","submitted_at":"2019-07-03T09:00:00Z","abstract_excerpt":"Logistic Regression and Support Vector Machine algorithms, together with Linear and Non-Linear Deep Neural Networks, are applied to lending data in order to replicate lender acceptance of loans and predict the likelihood of default of issued loans. A two phase model is proposed; the first phase predicts loan rejection, while the second one predicts default risk for approved loans. Logistic Regression was found to be the best performer for the first phase, with test set recall macro score of $77.4 \\%$. Deep Neural Networks were applied to the second phase only, were they achieved best performan"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.01800","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":""},"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":"2026-05-17T23:41:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3xA2yY7wg2Kz75fDyXsr7O3S2hOG4CsPT5vLlmQ+DSQl5l0kd5+A2Z8vbjFGVK+VMSbcmvgTQACneNdQHXc2AA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T03:31:36.004777Z"},"content_sha256":"a6c3f44b78066f5a55156782edbb14c907b2482f75413dfbd78b35e26bc8c35b","schema_version":"1.0","event_id":"sha256:a6c3f44b78066f5a55156782edbb14c907b2482f75413dfbd78b35e26bc8c35b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/M53YJEYHWYUYTFJVSR4WGLO5AT/bundle.json","state_url":"https://pith.science/pith/M53YJEYHWYUYTFJVSR4WGLO5AT/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/M53YJEYHWYUYTFJVSR4WGLO5AT/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":"2026-05-28T03:31:36Z","links":{"resolver":"https://pith.science/pith/M53YJEYHWYUYTFJVSR4WGLO5AT","bundle":"https://pith.science/pith/M53YJEYHWYUYTFJVSR4WGLO5AT/bundle.json","state":"https://pith.science/pith/M53YJEYHWYUYTFJVSR4WGLO5AT/state.json","well_known_bundle":"https://pith.science/.well-known/pith/M53YJEYHWYUYTFJVSR4WGLO5AT/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:M53YJEYHWYUYTFJVSR4WGLO5AT","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":"353d10c0b809361166ae847a0318d831d2f09b4a6ebacedad67f2e6db52fb44c","cross_cats_sorted":["q-fin.GN"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-fin.RM","submitted_at":"2019-07-03T09:00:00Z","title_canon_sha256":"fd644384bde305d5c001e306b804054c36e3fda0a119ba771f002dffce1e1408"},"schema_version":"1.0","source":{"id":"1907.01800","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.01800","created_at":"2026-05-17T23:41:35Z"},{"alias_kind":"arxiv_version","alias_value":"1907.01800v1","created_at":"2026-05-17T23:41:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.01800","created_at":"2026-05-17T23:41:35Z"},{"alias_kind":"pith_short_12","alias_value":"M53YJEYHWYUY","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_16","alias_value":"M53YJEYHWYUYTFJV","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_8","alias_value":"M53YJEYH","created_at":"2026-05-18T12:33:21Z"}],"graph_snapshots":[{"event_id":"sha256:a6c3f44b78066f5a55156782edbb14c907b2482f75413dfbd78b35e26bc8c35b","target":"graph","created_at":"2026-05-17T23:41:35Z","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"},"paper":{"abstract_excerpt":"Logistic Regression and Support Vector Machine algorithms, together with Linear and Non-Linear Deep Neural Networks, are applied to lending data in order to replicate lender acceptance of loans and predict the likelihood of default of issued loans. A two phase model is proposed; the first phase predicts loan rejection, while the second one predicts default risk for approved loans. Logistic Regression was found to be the best performer for the first phase, with test set recall macro score of $77.4 \\%$. Deep Neural Networks were applied to the second phase only, were they achieved best performan","authors_text":"Jeremy D. Turiel, Tomaso Aste","cross_cats":["q-fin.GN"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-fin.RM","submitted_at":"2019-07-03T09:00:00Z","title":"P2P Loan acceptance and default prediction with Artificial Intelligence"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.01800","kind":"arxiv","version":1},"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":"sha256:36c87233bf3d04346285fb78b3ce3cbdbc2a5e913f64b7fc8d5b9cddbcfbf5cb","target":"record","created_at":"2026-05-17T23:41:35Z","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":"353d10c0b809361166ae847a0318d831d2f09b4a6ebacedad67f2e6db52fb44c","cross_cats_sorted":["q-fin.GN"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-fin.RM","submitted_at":"2019-07-03T09:00:00Z","title_canon_sha256":"fd644384bde305d5c001e306b804054c36e3fda0a119ba771f002dffce1e1408"},"schema_version":"1.0","source":{"id":"1907.01800","kind":"arxiv","version":1}},"canonical_sha256":"6777849307b6298995359479632ddd04c4509a8a43b628461c34d8f9bcb1b5c0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6777849307b6298995359479632ddd04c4509a8a43b628461c34d8f9bcb1b5c0","first_computed_at":"2026-05-17T23:41:35.010812Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:41:35.010812Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"u04ONjFr9AfnadZCHnt3fL8FExY3Si709/B1nX8S3xP9X+j8kYnHUyMVjmu8B4w0a0aTaZnwtF4NGfLpLMq1Aw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:41:35.011580Z","signed_message":"canonical_sha256_bytes"},"source_id":"1907.01800","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:36c87233bf3d04346285fb78b3ce3cbdbc2a5e913f64b7fc8d5b9cddbcfbf5cb","sha256:a6c3f44b78066f5a55156782edbb14c907b2482f75413dfbd78b35e26bc8c35b"],"state_sha256":"59124a3acfc1332cfce8536d8c3b324a73c859b6922ad5c0dc586e4c004ea3dc"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tKwGTIveZg+qHO7SDhGXcCIDhTWm1irb6KzUcYYWL+9TplFtOm6+HWyAR3kZqXS3Ys0wJoA+A5CSSW0bvH6JAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-28T03:31:36.007040Z","bundle_sha256":"15147ed8428aaf079cfa571de6fab617632396241186bbb43357be644fe92a50"}}