Data Science Club Speaker Series - Moody's Analytics

by Haas Data Science Club


Wed, 27 Sep 2017

12:30 PM – 2:00 PM

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C125 @ Cheit Hall

2220 Piedmont Avenue, Berkeley, CA 94720, United States

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Irina Korablev ( Sr. Director), and Rama Sankisa( Associate Director and UC Berkeley Alumni) from Moody's Analytics, Data Science and Analytics will give us insights on how data science is applied to measuring and managing risk through credit analysis, economic research, and financial risk strategy.


File Attachments: Machine Learning_ Challenges and Opportunities in Credit Risk Modeling.pdf

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C125 @ Cheit Hall

2220 Piedmont Avenue, Berkeley, CA 94720, United States


Irina Korablev

Senior Director

Moody's Analytics

Irina Korablev leads the Data Science and Analytics team within Data Intelligence group at Moody’s Enterprise Risk Solutions (ERS) division. Her team provides data driven insights, products and innovations based on the ERS data assets and delivers validation studies for Moody’s Analytics default probability models.

Prior to her current role Irina led operations for Moody’s Analytics’ Credit Research Database, one of the world’s largest private firm credit risk data repositories that enabled the Moody’s RiskCalc™ product line, which now covers 28 countries and 80% of the world’s GDP. As a member of the ERS Research Team Irina developed the Loss Given Default model for LossCalc™ and private firm default probability model for RiskCalc™ Russia. A veteran of Moody’s Analytics, Irina was one of the early employees at KMV, taking over management of the data assets from one of the founders.

Irina holds an MS in Applied Math from Moscow State University and MA in Economics from Central European University, completing her studies in Essex, UK and Budapest, Hungary. When not at work, you can find Irina and her family on ski slopes or in the wilderness, exploring the far away and exotic places.

Rama Sankisa

Associate Director

Moody's Analytics

Rama Sankisa is an Associate Director in Data Intelligence Group at Moody’s Analytics. He develops quantitative models focused on text analytics to discover insights that will be turned into new metrics and data products. He is also responsible for improving data acquisition and collection to help Moody’s build robust data collection infrastructure.

Prior to his current role, Rama worked as a Quantitative Researcher in Moody’s Analytics portfolio and balance sheet solutions Group where he built stochastic macro-economic and exchange rate models for insurance clients. He also contributed in developing solutions for stress-testing money market funds.

Prior to joining Moody’s Analytics, Rama has worked for Goldman Sachs where he supported exotic derivative structuring and trading desks on their new product issuances.
Rama holds Masters in Financial Engineering degree from University of California, Berkeley.

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Haas Data Science Club

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