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Jari Koister

Jari Koister

Vice President for the FICO Decision Management Suite at FICO

As VP for the FICO Decision Management Suite; a software platform widely used for Intelligent Decision and AI application in Financial Technology and beyond. Jari is leading product strategy, planning and execution. Mr. Koister also oversees research into Machine Learning, Optimization and AI and incorporation of these into DMS. The objective is to provide powerful capabilities that makes FICO’s and FICO Customer’s solutions successful and increasingly competitive.In addition, he is professor at the Data Science program at UC Berkley, California.

As programmer and software architect in his early career, Jari worked on distributed applications, compiler technology, and computer language design. As software manager and executive Jari has been leading product and engineering team at great companies such as Salesforce.com, Twitter, Oracle. Jari was the founder and CTO of groupswim.com, a company that was subsequently acquired by salesforce.com in 2009. In addition, Koister has been leading software research focused teams at Ericsson and Hewlett-Packard Laboratories. Dr. Koister holds a Ph.D. in Distributed Systems from the Royal Institute of Technology, Sweden.

Track: Emerging Analytics

Tuesday, April 16, 11:30am–12:20pm

Explainable AI

Financial Services are increasingly deploying AI models and services for a wide range of application. These applications include credit life cycles such as credit onboarding, transaction fraud, and identity fraud. In order to confidently deploy such models, these organizations require models to be interpretable and explainable. They also need to be resilient to adversarial attacks. In some situations, regulatory requirements apply and prohibits application of black-box machine learning models.

This talk describes tools and infrastructure that FICO has developed as part of the platform to support these needs. The support is uniquely forward-looking and one of the first platforms to support these aspects of applying AI and ML for any customer.

What we will cover: (1) Examples of Financial Services applications of AI/ML; (2) Specific needs for Explainability and resiliency; (3) Approaches for solving explainability and resiliency.; (4) Regulatory requirements, and how to meet them.; (5) A platform that provide support for xAI and Mission Critical AI.; (6) Further research and product development directions.