Risk Management in E-Commerce-A Fraud Study Case Using Acoustic Analysis through Its Complexity

Autor(es)

Nascimento, Diego C. ^[1] ; Barbosa, Bruno ^[1] ; Perez, Andre M. ^[1] ; Caires, Daniel O. ^[1] ; Hirama, Edgar ^[1] ; Ramos, Pedro L. ^[1] ; Louzada, Francisco ^[1]

Afiliação do(s) autor(es)

^[1] Univ Sao Paulo, Inst Math Sci & Comp, BR-13566590 Sao Carlos, SP - Brazil

• Tipo de documento: Artigo Científico
• Fonte: Entropy; v. 21, n. 11 NOV 2019.
• Citações Web of Science: 0

Resumo

This work aimed to develop business intelligence towards fraud detection using buyer-placed information combined with the sound analysis from a confirmation purchase call. We used a dataset of 789 orders in 2018, provided by different e-commerce websites and calls fulfilled from every Brazilian state. Nine acoustic index features were used, through entropy in sound and vibration, summarizing the audio plus 6 extra features related, added by 12 customer features to compose two different classifiers (Logistic Regression and Random Forest). The acoustic indexes were, in fact, capable of providing better accuracy of the models, showing a probability associated with the voice characteristics, helping decision-making in credit card fraud. (AU)

• Processo FAPESP: 17/25971-0 - Inferência estatística de sistemas complexos
• Beneficiário: Pedro Luiz Ramos
• Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado