Put open source to work
July 16–17, 2018: Training & Tutorials
July 18–19, 2018: Conference
Portland, OR
Ryan Roser

Ryan Roser
Director, Data Science and Text Analytics, Refinitiv


Ryan Roser is the director of data science and text analytics within the San Francisco Innovation Lab at Refinitiv, where he develops quantitative models and predictive analytics for investors and works with unstructured text to identify new trends and insights. Previously, Ryan was a principal quantitative research analyst at StarMine, where he developed a first-of-its-kind text-based corporate credit risk model. Ryan lives in Portland, Oregon. He enjoys gardening and raising chickens.


11:50am12:30pm Thursday, July 19, 2018
Artificial intelligence
Location: D137/138
Level: Intermediate
Ryan Roser (Refinitiv)
Average rating: *****
(5.00, 1 rating)
In the wake of the financial crisis, Thomson Reuters released a novel text-mining-based credit risk model to assess the default risk of publicly traded companies by quantitatively analyzing text. Six years later, the company is updating it to use deep learning. Ryan Roser discusses the benefits and trade-offs involved in transitioning existing analytics to use deep learning. Read more.