{"id":"https://openalex.org/W3094604133","doi":"https://doi.org/10.1145/3383455.3422563","title":"Deep Q-network-based adaptive alert threshold selection policy for payment fraud systems in retail banking","display_name":"Deep Q-network-based adaptive alert threshold selection policy for payment fraud systems in retail banking","publication_year":2020,"publication_date":"2020-10-15","ids":{"openalex":"https://openalex.org/W3094604133","doi":"https://doi.org/10.1145/3383455.3422563","mag":"3094604133"},"language":"en","primary_location":{"id":"doi:10.1145/3383455.3422563","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3383455.3422563","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3383455.3422563","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the First ACM International Conference on AI in Finance","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3383455.3422563","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Hongda Shen","orcid":null},"institutions":[{"id":"https://openalex.org/I82495205","display_name":"University of Alabama in Huntsville","ror":"https://ror.org/02zsxwr40","country_code":"US","type":"education","lineage":["https://openalex.org/I82495205"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hongda Shen","raw_affiliation_strings":["University of Alabama in Huntsville"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Alabama in Huntsville","institution_ids":["https://openalex.org/I82495205"]}]},{"author_position":"last","author":{"id":null,"display_name":"Eren Kurshan","orcid":null},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Eren Kurshan","raw_affiliation_strings":["Columbia University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Columbia University","institution_ids":["https://openalex.org/I78577930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5204,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.7349381,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9983000159263611,"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"}},"topics":[{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9983000159263611,"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"}},{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9977999925613403,"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"}},{"id":"https://openalex.org/T10270","display_name":"Blockchain Technology Applications and Security","score":0.9919999837875366,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/payment","display_name":"Payment","score":0.6456999778747559},{"id":"https://openalex.org/keywords/upstream","display_name":"Upstream (networking)","score":0.5264999866485596},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5145999789237976},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.3864000141620636},{"id":"https://openalex.org/keywords/downstream","display_name":"Downstream (manufacturing)","score":0.37389999628067017},{"id":"https://openalex.org/keywords/payment-system","display_name":"Payment system","score":0.33489999175071716}],"concepts":[{"id":"https://openalex.org/C145097563","wikidata":"https://www.wikidata.org/wiki/Q1148747","display_name":"Payment","level":2,"score":0.6456999778747559},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6391000151634216},{"id":"https://openalex.org/C191172861","wikidata":"https://www.wikidata.org/wiki/Q7899321","display_name":"Upstream (networking)","level":2,"score":0.5264999866485596},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5145999789237976},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.3864000141620636},{"id":"https://openalex.org/C2776207758","wikidata":"https://www.wikidata.org/wiki/Q5303302","display_name":"Downstream (manufacturing)","level":2,"score":0.37389999628067017},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.35569998621940613},{"id":"https://openalex.org/C2776983043","wikidata":"https://www.wikidata.org/wiki/Q986008","display_name":"Payment system","level":3,"score":0.33489999175071716},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.3345000147819519},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.3147999942302704},{"id":"https://openalex.org/C52970973","wikidata":"https://www.wikidata.org/wiki/Q2497134","display_name":"Adaptive system","level":2,"score":0.28200000524520874},{"id":"https://openalex.org/C2986226071","wikidata":"https://www.wikidata.org/wiki/Q22687","display_name":"Banking industry","level":2,"score":0.2766000032424927},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.2727000117301941},{"id":"https://openalex.org/C2775973920","wikidata":"https://www.wikidata.org/wiki/Q3252726","display_name":"Selection algorithm","level":3,"score":0.2535000145435333}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3383455.3422563","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3383455.3422563","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3383455.3422563","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the First ACM International Conference on AI in Finance","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2010.11062","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2010.11062","pdf_url":"https://arxiv.org/pdf/2010.11062","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"doi:10.1145/3383455.3422563","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3383455.3422563","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3383455.3422563","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the First ACM International Conference on AI in Finance","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W145450961","https://openalex.org/W2022253721","https://openalex.org/W2074500080","https://openalex.org/W2145339207","https://openalex.org/W2786146442"],"related_works":[],"abstract_inverted_index":{"Machine":[0],"learning":[1],"models":[2],"have":[3,18,37,134],"widely":[4],"been":[5,19],"used":[6,52,128],"in":[7,57,65,122],"fraud":[8,27,33,68,72,104,110,148,186],"detection":[9,69,73,105],"systems.":[10,150],"Most":[11],"of":[12,25,80,116,195],"the":[13,23,26,31,66,90,99,103,108,113,117,155,179,185,192,196],"research":[14],"and":[15,43,60,112,164],"development":[16],"efforts":[17],"concentrated":[20],"on":[21,45],"improving":[22,191],"performance":[24],"scoring":[28],"models.":[29],"Yet,":[30],"downstream":[32],"alert":[34,91,95,118,149,197],"systems":[35,49,74],"still":[36],"limited":[38],"to":[39,84,87,101],"no":[40],"model":[41],"adoption":[42],"rely":[44],"manual":[46],"steps.":[47],"Alert":[48],"are":[50,127],"pervasively":[51],"across":[53],"all":[54],"payment":[55],"channels":[56],"retail":[58],"banking":[59],"play":[61],"an":[62,142],"important":[63],"role":[64],"overall":[67],"process.":[70],"Current":[71],"end":[75],"up":[76],"with":[77],"large":[78],"numbers":[79],"dropped":[81],"alerts":[82],"due":[83],"their":[85,130],"inability":[86],"account":[88],"for":[89,129,147],"processing":[92,119],"capacity.":[93],"Ideally,":[94],"threshold":[96,144,156],"selection":[97,145,157],"enables":[98],"system":[100],"maximize":[102],"while":[106],"balancing":[107],"upstream":[109],"scores":[111],"available":[114],"bandwidth":[115],"teams.":[120],"However,":[121],"practice,":[123],"fixed":[124],"thresholds":[125],"that":[126,174],"simplicity":[131],"do":[132],"not":[133],"this":[135,138,175],"ability.":[136],"In":[137],"paper,":[139],"we":[140],"propose":[141],"enhanced":[143],"policy":[146],"The":[151],"proposed":[152],"approach":[153,177],"formulates":[154],"as":[158,188,190],"a":[159],"sequential":[160],"decision":[161],"making":[162],"problem":[163],"uses":[165],"Deep":[166],"Q-Network":[167],"based":[168],"reinforcement":[169],"learning.":[170],"Experimental":[171],"results":[172],"show":[173],"adaptive":[176],"outperforms":[178],"current":[180],"static":[181],"solutions":[182],"by":[183],"reducing":[184],"losses":[187],"well":[189],"operational":[193],"efficiency":[194],"system.":[198]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2026-07-03T08:13:44.112507","created_date":"2020-10-29T00:00:00"}
