{"id":"https://openalex.org/W7150758426","doi":"https://doi.org/10.48550/arxiv.2604.02899","title":"Extracting Money Laundering Transactions from Quasi-Temporal Graph Representation","display_name":"Extracting Money Laundering Transactions from Quasi-Temporal Graph Representation","publication_year":2026,"publication_date":"2026-04-03","ids":{"openalex":"https://openalex.org/W7150758426","doi":"https://doi.org/10.48550/arxiv.2604.02899"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.02899","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.02899","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.02899","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133062359","display_name":"Haseeb Tariq","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Tariq, Haseeb","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5133016389","display_name":"Marwan Hassani","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hassani, Marwan","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5133062359"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11838","display_name":"Crime, Illicit Activities, and Governance","score":0.8884000182151794,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11838","display_name":"Crime, Illicit Activities, and Governance","score":0.8884000182151794,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10270","display_name":"Blockchain Technology Applications and Security","score":0.020800000056624413,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.007699999958276749,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/money-laundering","display_name":"Money laundering","score":0.9458000063896179},{"id":"https://openalex.org/keywords/database-transaction","display_name":"Database transaction","score":0.625},{"id":"https://openalex.org/keywords/financial-transaction","display_name":"Financial transaction","score":0.5629000067710876},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5052000284194946},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.48890000581741333},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.47119998931884766},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.44600000977516174}],"concepts":[{"id":"https://openalex.org/C2780005421","wikidata":"https://www.wikidata.org/wiki/Q151900","display_name":"Money laundering","level":2,"score":0.9458000063896179},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7070000171661377},{"id":"https://openalex.org/C75949130","wikidata":"https://www.wikidata.org/wiki/Q848010","display_name":"Database transaction","level":2,"score":0.625},{"id":"https://openalex.org/C164516710","wikidata":"https://www.wikidata.org/wiki/Q1166072","display_name":"Financial transaction","level":3,"score":0.5629000067710876},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5052000284194946},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.48890000581741333},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.47119998931884766},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.44600000977516174},{"id":"https://openalex.org/C112313634","wikidata":"https://www.wikidata.org/wiki/Q7886648","display_name":"Complement (music)","level":5,"score":0.3984000086784363},{"id":"https://openalex.org/C182306322","wikidata":"https://www.wikidata.org/wiki/Q1779371","display_name":"Order (exchange)","level":2,"score":0.39489999413490295},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.37549999356269836},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.3619000017642975},{"id":"https://openalex.org/C2985140798","wikidata":"https://www.wikidata.org/wiki/Q28813","display_name":"Financial fraud","level":2,"score":0.3449999988079071},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.3400000035762787},{"id":"https://openalex.org/C72108876","wikidata":"https://www.wikidata.org/wiki/Q844565","display_name":"Transaction processing","level":3,"score":0.28600001335144043},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2678000032901764},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.26750001311302185},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.26649999618530273}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.02899","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.02899","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.02899","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.02899","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.8039728999137878}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Money":[0,112],"laundering":[1,23,92],"presents":[2],"a":[3,152,156],"persistent":[4],"challenge":[5],"for":[6,172,178,186],"financial":[7,59,97,160],"institutions":[8,60],"worldwide,":[9],"while":[10,50],"criminal":[11],"organizations":[12],"constantly":[13],"evolve":[14],"their":[15],"tactics":[16],"to":[17,32,44,67,89,107,176],"bypass":[18],"detection":[19,114,149,203],"systems.":[20,70],"Traditional":[21],"anti-money":[22],"approaches":[24],"mainly":[25],"rely":[26],"on":[27,147],"predefined":[28],"risk-based":[29],"rules,":[30],"leading":[31],"resource-intensive":[33],"investigations":[34],"and":[35,129,133,140,155,182,209],"high":[36],"numbers":[37],"of":[38,52,119,127,131,137,158,188],"false":[39],"positive":[40],"alerts.":[41],"In":[42,71],"order":[43],"restrict":[45],"operational":[46],"costs":[47],"from":[48,80],"exploding,":[49],"billions":[51],"transactions":[53,95],"are":[54,61,122,211],"being":[55],"processed":[56],"every":[57],"day,":[58],"investing":[62],"in":[63,96,103,125,135,168,205],"more":[64,183],"sophisticated":[65],"mechanisms":[66],"improve":[68],"existing":[69,201],"this":[72],"paper,":[73],"we":[74],"present":[75],"ExSTraQt":[76],"(EXtract":[77],"Suspicious":[78],"TRAnsactions":[79],"Quasi-Temporal":[81],"graph":[82],"representation),":[83],"an":[84,166],"advanced":[85],"supervised":[86],"learning":[87],"approach":[88],"detect":[90],"money":[91],"(or":[93],"suspicious)":[94],"datasets.":[98,162,191],"Our":[99,207],"proposed":[100],"framework":[101,121,146,197],"excels":[102],"performance,":[104],"when":[105],"compared":[106],"the":[108,138,169,179,189],"state-of-the-art":[109],"AML":[110,202],"(Anti":[111],"Laundering)":[113],"models.":[115],"The":[116],"key":[117],"strengths":[118],"our":[120,145,196],"sheer":[123],"simplicity,":[124],"terms":[126,136],"design":[128],"number":[130],"parameters;":[132],"scalability,":[134],"computing":[139],"memory":[141],"requirements.":[142],"We":[143,163,192],"evaluated":[144],"transaction-level":[148],"accuracy":[150],"using":[151],"real":[153,180],"dataset;":[154,181],"set":[157],"synthetic":[159,190],"transaction":[161],"consistently":[164],"achieve":[165],"uplift":[167],"F1":[170],"score":[171],"most":[173],"datasets,":[174],"up":[175],"1%":[177],"than":[184],"8%":[185],"one":[187],"also":[193],"claim":[194],"that":[195],"could":[198],"seamlessly":[199],"complement":[200],"systems":[204],"banks.":[206],"code":[208],"datasets":[210],"available":[212],"at":[213],"https://github.com/mhaseebtariq/exstraqt.":[214]},"counts_by_year":[],"updated_date":"2026-04-07T06:06:30.997549","created_date":"2026-04-07T00:00:00"}