Model Risk Management for Machine Learning Models

Model Risk Management for Machine Learning Models
Thought Leadership Webinar:  Complimentary to PRMIA Network!  In this webinar, we discuss adapting your MRM practices when working with Machine Learning models;  bring clarity to some of the model risk management challenges when adopting data science, AI and ML methods in the enterprise; and discuss key drivers of model risk in today’s environment and how the scope of model governance is changing. Thank you to for providing this webinar to the PRMIA network!

Presented By:
Sri Krishnamurthy, CFA, CAP

May 27, 2020

10:00 a.m. - 11:00 a.m.

Session Length:
60 minutes


About This Webinar

With innovations in hardware, algorithms, and large datasets, the use of Data Science and Machine Learning in finance is increasing. As more and more open-source technologies penetrate enterprises, quants and data scientists have a plethora of choices for building, testing, and scaling models. Alternative datasets including text analytics, cloud computing, algorithmic trading are game changers for many firms exploring novel modeling methods to augment their traditional investment and decision workflows. While there is significant enthusiasm, model risk professionals and risk managers are concerned about the onslaught of new technologies, programming languages and data sets that are entering the enterprise. With very little guidance from regulators on how to govern the tools and the processes, organizations are developing their own home-cooked methods to address model risk management challenges.

In this webinar, we aim to bring clarity to some of the model risk management challenges when adopting data science, AI and Machine Learning methods in the enterprise. We will discuss key drivers of model risk in today’s environment and how the scope of model governance is changing. We will introduce key concepts and discuss key aspects to be considered when developing a model risk management framework when incorporating data science techniques and AI methodologies.

Interested in learning more? Check out our newest course in partnership with QuantUniversity, Model Risk Management for Machine Learning Models.

About Our Experts  

  Sri Krishnamurthy, CFA, CAP is the founder of, a data and Quantitative Analysis Company, and the creator of the Analytics Certificate program and Fintech Certificate program. Sri has more than 15 years of experience in analytics, quantitative analysis, statistical modeling and designing large-scale applications. Prior to starting QuantUniversity, Sri worked at Citigroup, Endeca,  MathWorks, and with more than 25 customers in the financial services and energy industries. He has trained more than 1000 students in quantitative methods, analytics, and big data in the industry and at Babson College, Northeastern University, and Hult International Business School.

Sri earned an MS in Computer Systems Engineering and another MS in Computer Science, both from Northeastern University and an MBA with a focus on Investments from Babson College.


Continued Risk Learning Credits: 1

PRMIA Continued Risk Learning (CRL) programs provide you with the opportunity to formally recognize your professional development, documenting your evolution as a risk professional. Employers can see that you are not static, making you a highly valued, dynamic, and desirable employee. The CRL program is open to all Contributing, Sustaining, and Risk Leader members, providing a convenient and easily accessible way to submit, manage, track and document your activities online through the PRMIA CRL Center. To request CRL credits, please email

  Membership Type Price  
  Members (Sustaining, Corporate, RIM & Contributing)

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5/27/2020 10:00 AM - 11:00 AM

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