Model Validation and Machine Learning (With a Focus on Neural Networks)
Dr. Agus Sudjianto from Wells Fargo
QuantUniversity partnered with PRMIA to do the first QuantUniversity summer school in Machine Learning and AI in Finance. We had more than 1000 participants from more than 20 countries including India, China, Australia, UK, Turkey, South Africa etc. attend the summer school series.
This year, we offered 3 courses in Data Science, Machine Learning, and Model Risk Management:
- Just Enough Python for Data Science
- Machine Learning and AI for Financial Professionals
- Model Risk Management for Machine Learning Models
In addition, we had 10 lectures from eminent quants, innovators, and thinkers on various topics in AI/ML and Fintech related topics.
Lecture 3
In Week 3, we had Dr.Agus Sudjianto from Wells Fargo discuss his work on Model Validation and Machine Learning. Here is a summary of the workshop.
Summary:
All models are wrong and when they are wrong they create financial or non-financial risks. Understanding, testing, and managing model failures are the key focus of model risk management particularly model validation.
For machine learning models, particular attention is made on how to manage model fairness, explainability, robustness, and change control. In this presentation, I will focus the discussion on machine learning explainability and robustness. Explainability is critical to evaluate conceptual soundness of models particularly for the applications in highly regulated institutions such as banks. There are many explainability tools available and my focus in this talk is how to develop fundamentally interpretable models.
Neural networks (including Deep Learning), with proper architectural choice, can be made to be highly interpretable models. Since models in production will be subjected to dynamically changing environments, testing, and choosing robust models against changes are critical, an aspect that has been neglected in AutoML.
Slides, Demos, and videos at https://academy.qusandbox.com/#/market/5f217d6399aa4a24691da52b
If you want to try out the demos yourselves on the QuAcademy:
https://academy.qusandbox.com
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