Terisa Roberts is a director and Global Solution lead for Risk Modeling and Decisioning at SAS. She has extensive experience in quantitative risk management, regulatory compliance, and model governance and validation. She has worked in financial services, telecommunications, government, energy, and retail sectors. She advises banks and regulators around the world on best practices in risk modeling and decisioning and the responsible use of artificial intelligence and machine learning. She regularly speaks at international conferences on the application of innovative models in risk management. She holds a PhD in Operations Research and Informatics and lives in Sydney, Australia, with her family.
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Risk Modeling: Practical Applications of Artificial Intelligence, Machine Learning, and Deep Learning
A wide-ranging overview of the use of machine learning and AI techniques in financial risk management, including practical advice for implementation
Risk Modeling: Practical Applications of Artificial Intelligence, Machine Learning, and Deep Learning introduces readers to the use of innovative AI technologies for forecasting and evaluating financial risks. Providing up-to-date coverage of the practical application of current modeling techniques in risk management, this real-world guide also explores new opportunities and challenges associated with implementing machine learning and artificial intelligence (AI) into the risk management process.