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 shares forward-looking tools and infrastructure has developed to support these needs.
Jari Koister is vice president of product and technology at FICO. He also teaches in the Data Science Program at UC Berkeley. Previously, he has, among other things, led the development of Chatter, Salesforce’s social enterprise application and platform; founded and served as CTO at Groupswim.com, an early social enterprise collaboration company (acquired by Salesforce); founded and served as CSO and CTO at Qrodo.com, an elastic platform for broadcasting sports events live on the internet; led the development of CommerceOne’s flagship product MarketSite; and led research in computer languages and distributed computing at Ericsson Labs and Hewlett-Packard Laboratories. Jari holds a PhD in computer science from the Royal Institute of Technology, Stockholm, Sweden.
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