Interpretable and resilient AI for financial services /

"Financial services are increasingly deploying AI models and services for a wide range of applications in the credit lifecycle, such as credit onboarding and identifying transaction fraud and identity fraud. These models must be interpretable, explainable, and resilient to adversarial attacks....

Descripción completa

Detalles Bibliográficos
Clasificación:Libro Electrónico
Formato: Electrónico Video
Idioma:Inglés
Publicado: [Place of publication not identified] : O'Reilly Media, 2019.
Temas:
Strata Conference > (2019 : > San Francisco, Calif.)
Artificial intelligence.
Machine learning.
Finance > Data processing.
Artificial Intelligence
Intelligence artificielle.
Apprentissage automatique.
Finances > Informatique.
artificial intelligence.
Electronic videos.
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)
Descripción
Sumario:"Financial services are increasingly deploying AI models and services for a wide range of applications in the credit lifecycle, such as credit onboarding and identifying transaction fraud and identity fraud. These models must be interpretable, explainable, and resilient to adversarial attacks. In some situations, regulatory requirements apply that prohibit black-box machine learning models. Jari Koister (FICO) shares forward-looking tools and infrastructure has developed to support these needs. This session was recorded at the 2019 O'Reilly Strata Data Conference in San Francisco."--Resource description page
Notas:Title from title screen (viewed January 10, 2020).
Descripción Física:1 online resource (1 streaming video file (47 min., 32 sec.))

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