Rodyti trumpą aprašą

dc.rights.licenseKūrybinių bendrijų licencija / Creative Commons licenceen_US
dc.contributor.authorLevon, Fabiana
dc.contributor.authorMaknickienė, Nijolė
dc.date.accessioned2024-04-18T06:01:44Z
dc.date.available2024-04-18T06:01:44Z
dc.date.issued2023
dc.date.submitted2023-02-26
dc.identifier.isbn9786094763335en_US
dc.identifier.issn2029-4441en_US
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/154012
dc.description.abstractThis article focuses on fraudulent behaviour and patterns as well as ways of detecting such patterns by using Big Data. The study analyses scientific articles to examine types of financial fraud and their detection techniques as well as develops a model that is based on factors characterizing fraudulent credit card transactions made across USA. Regression analysis, correlation and descriptive statistics analysis is applied. Statistically significant results are found indicating a causal relationship between fraudulent transactions and transactions made in Alaska, during the month of October and on a Thursday. Although, the impact of these relationships is relatively small. Expanding the dataset with more numerical variables that could be used for identifying fraudulent transactions is advised for future research as to better the overall fit of the model.en_US
dc.format.extent9 p.en_US
dc.format.mediumTekstas / Texten_US
dc.language.isoenen_US
dc.relation.isreferencedbyScopusen_US
dc.relation.urihttps://etalpykla.vilniustech.lt/handle/123456789/153869en_US
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.source.urihttps://bm.vgtu.lt/index.php/verslas/2023/schedConf/presentationsen_US
dc.subjectfinancial frauden_US
dc.subjectfraud detectionen_US
dc.subjectBig Data analyticsen_US
dc.subjectcredit card transaction frauden_US
dc.subjectfraud detection methodsen_US
dc.titleFactors influencing fraudulent transactions from Big Data perspectiveen_US
dc.typeKonferencijos publikacija / Conference paperen_US
dcterms.accessRightsLaisvai prieinamas / Openly availableen_US
dcterms.accrualMethodRankinis pateikimas / Manual submissionen_US
dcterms.alternativeFinance and investment: new challenges and opportunitiesen_US
dcterms.dateAccepted2023-04-05
dcterms.issued2023
dcterms.licenseCC BYen_US
dcterms.references27en_US
dc.description.versionTaip / Yesen_US
dc.type.pubtypeP1d - Straipsnis recenzuotame konferencijos darbų leidinyje / Paper published in peer-reviewed conference publicationen_US
dc.contributor.orcidhttps://orcid.org/0000-0003-2785-5183, Maknickienė Nijolė
dc.contributor.institutionVilnius Gediminas Technical Universityen_US
dc.contributor.facultyVerslo vadybos fakultetas / Faculty of Business Managementen_US
dc.contributor.departmentFinansų inžinerijos katedra / Department of Financial Engineeringen_US
dcterms.sourcetitle13th International Scientific Conference “Business and Management 2023”en_US
dc.description.volumeIen_US
dc.identifier.eisbn9786094763342en_US
dc.identifier.eissn2029-929Xen_US
dc.publisher.nameVilnius Gediminas Technical Universityen_US
dc.publisher.nameVilniaus Gedimino technikos universitetasen_US
dc.publisher.countryLithuaniaen_US
dc.publisher.countryLietuvaen_US
dc.publisher.cityVilniusen_US
dc.date.firstonline2023-06-07
dc.identifier.doihttps://doi.org/10.3846/bm.2023.999en_US


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Rodyti trumpą aprašą

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