TY  - GEN
AB  - This book offers an introduction to the topic of anti-fraud in digital finance based on the behavioral modeling paradigm. It deals with the insufficiency and low-quality of behavior data and presents a unified perspective to combine technology, scenarios, and data for better anti-fraud performance. The goal of this book is to provide a non-intrusive second security line, rather than replaced with existing solutions, for anti-fraud in digital finance. By studying common weaknesses in typical fields, it can support the behavioral modeling paradigm across a wide array of applications. It covers the latest theoretical and experimental progress and offers important information that is just as relevant for researchers as for professionals.
AU  - Wang, Cheng.
CN  - HG176.7
CY  - Singapore :
DA  - 2023.
DO  - 10.1007/978-981-99-5257-1
DO  - doi
ID  - 1484678
KW  - Ingénierie financière.
KW  - Financial engineering.
KW  - Fraud
LK  - https://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-99-5257-1
N2  - This book offers an introduction to the topic of anti-fraud in digital finance based on the behavioral modeling paradigm. It deals with the insufficiency and low-quality of behavior data and presents a unified perspective to combine technology, scenarios, and data for better anti-fraud performance. The goal of this book is to provide a non-intrusive second security line, rather than replaced with existing solutions, for anti-fraud in digital finance. By studying common weaknesses in typical fields, it can support the behavioral modeling paradigm across a wide array of applications. It covers the latest theoretical and experimental progress and offers important information that is just as relevant for researchers as for professionals.
PB  - Springer,
PP  - Singapore :
PY  - 2023.
SN  - 9789819952571
SN  - 9819952573
T1  - Anti-fraud engineering for digital finance :behavioral modeling paradigm /
TI  - Anti-fraud engineering for digital finance :behavioral modeling paradigm /
UR  - https://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-99-5257-1
ER  -