TY - GEN
T1 - On the Application of SDC Stream Methods to Card Payments Analytics
AU - Nuñez-Del-Prado, Miguel
AU - Nin, Jordi
N1 - Publisher Copyright:
© Springer Nature Switzerland AG 2018.
PY - 2018
Y1 - 2018
N2 - Banks and financial services have to constantly innovate their online payment services to avoid large digital companies take the control of online card transactions, relegating traditional banks to simple payments carriers. Apart from creating new payment methods (e.g. contact-less cards, mobile wallets, etc.), banks offers new services based on historical payments data to endow traditional payments methods with new services and functionalities. In this latter case, it is where privacy preserving techniques play a fundamental role ensuring personal data is managed full-filling all the applicable laws and regulations. In this paper, we introduce some ideas about how SDC stream anonymization methods could be used to mask payments data streams. Besides, we also provide some experimental results over a real card payments database.
AB - Banks and financial services have to constantly innovate their online payment services to avoid large digital companies take the control of online card transactions, relegating traditional banks to simple payments carriers. Apart from creating new payment methods (e.g. contact-less cards, mobile wallets, etc.), banks offers new services based on historical payments data to endow traditional payments methods with new services and functionalities. In this latter case, it is where privacy preserving techniques play a fundamental role ensuring personal data is managed full-filling all the applicable laws and regulations. In this paper, we introduce some ideas about how SDC stream anonymization methods could be used to mask payments data streams. Besides, we also provide some experimental results over a real card payments database.
KW - General Data Protection Regulation (GDPR)
KW - Payment Service Directive (PSD2)
KW - Statistical Disclosure Control
KW - Stream mining
UR - http://www.scopus.com/inward/record.url?scp=85055678503&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-00202-2_25
DO - 10.1007/978-3-030-00202-2_25
M3 - Conference contribution
AN - SCOPUS:85055678503
SN - 9783030002015
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 306
EP - 318
BT - Modeling Decisions for Artificial Intelligence - 15th International Conference, MDAI 2018, Proceedings
A2 - Torra, Vicenc
A2 - Torra, Vicenc
A2 - Narukawa, Yasuo
A2 - González-Hidalgo, Manuel
A2 - Aguilo, Isabel
PB - Springer Verlag
T2 - 15th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2018
Y2 - 15 October 2018 through 18 October 2018
ER -