Manasi Vartak

Founder and CEO at Verta

Manasi Vartak is a PhD Student in the Database Group at MIT CSAIL, advised by Samuel Madden. Her research focuses on novel systems to support fast and interactive data analysis. She is currently working on systems to manage machine learning models and enable easy debugging of models. She has previously worked on visualization recommendation systems. Manasi is a recipient of the Facebook Graduate Fellowship and the Google Anita Borg Scholarship.

WATCH LIVE: December 9 @ 3:00PM – 3:20PM ET

Reducing operational risk via model monitoring

ML models are being used across the board in financial institutions ranging from marketing, credit risk models, fraud detection, investment recommendations and so on. As the number of applications of AI and ML in finance increases, so does the risk associated with poorly performing models. Often, model performance can degrade in non-obvious ways including a change in the assumptions underlying the model, a systematic change in the data powering the model, or changes in the logic interpreting model results. Robust model monitoring and management can help identify problems with models before they have massive operational or reputation consequences. In this talk, I will cover the different aspects and sub-areas of model monitoring, tools that can support monitoring and how to get started with managing operational risk associated with your models.