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....
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| Format: | eBook |
| Language: | English |
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[Place of publication not identified]
O'Reilly Media
2019
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| Collection: | O'Reilly - Collection details see MPG.ReNa |
| Summary: | "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 |
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| Item Description: | Title from title screen (viewed January 10, 2020) |
| Physical Description: | 1 streaming video file (47 min., 32 sec.) |