GRI’s Podcast Series

 

 

Easy Access to Expert Information.

 

The Risk Dialogues Podcast Series is an exciting way for the Global Risk Institute to provide relevant information on emerging risk themes affecting the financial sector.  Each episode will feature subject matter experts to share their knowledge on specific topics with you.


 

Now available:

 

Machine Learning Podcast Series:

“Machine learning, or data science, can be portrayed as the new world of statistics. We are now able to learn from large sets of data in ways not possible several years ago.

  • We can deliver non-linear models for forecasting and improved decision-making.
  • We can search for patterns in data to improve a company’s understanding of its customers and the environment in which it operates.
  • We can develop decision rules where we are interacting with a changing environment.”

Machine Learning in Business - An Introduction to the World of Data Science - J. Hull

Tune into this podcast series in which Alexey Rubtsov  machine learning.

 


 

Adversarial Learning
Is it possible to confuse machines in a way similar to how optical illusions confuse people? What are the dangers of employing Machine Learning tools in financial services? Can Adversarial Machine Learning be used for good? Listen to our today’s podcast to find out answers to these questions.

Challenges in Building Ethical Artificial Intelligence
How challenging is to build Artificial Intelligence that is ethical? Is it always possible to determine what is ethical and what is not? What feature of AI could make it difficult to predict whether AI could become unethical? To find out, listen to our today’s podcast on challenges in building ethical AI.

 

Self-Supervised Learning
How can you build common sense in Artificial Intelligence? What tool will Meta use in building the Metaverse? What are financial applications of Self-Supervised Learning? Our today’s podcast will provide answers to these questions.
 

The Regulation of Artificial Intelligence in Finance
with Romana Mizdrak

How do we avoid negative effects from the use of AI in finance? How do we prevent a scenario when AI outsmarts existing financial regulations? This and much more in today’s podcast with our guest speaker Romana Mizdrak, Managing Director of Risk Quantification Division at Office of the Superintendent of Financial Institutions.


 

Unsupervised Learning
What is Unsupervised Learning, where is it applied, and how dangerous can it be?  How did Unsupervised Learning help Alibaba to better target its financial products?  To find out, listen to this two-minute podcast.

 

 

Supervised Learning
What does Supervised Learning mean? What problems in finance can it solve and when does it become useless?  How did Google apply Supervised Learning to revolutionize Machine Translation in 2016?  Our three-minute podcast on Supervised Learning will help you find answers to these questions.

 

Semi-Supervised Learning
How can you successfully target financial products when you don’t have much information about customers’ preferences?  What is Semi-Supervised Learning, what applications does it already have, and is it easy to apply?  To get answers to these questions, listen to our three-minute podcast on Semi-Supervised Learning.

 

Reinforcement Learning

How did DeepMind use Reinforcement Learning to teach a machine to play chess and other complex games better than humans?  What is Reinforcement Learning, where was it already applied in finance and when can it fail?  Our three-minute podcast on Reinforcement Learning will help you find out answers to these questions.

 


 

The Role of Artificial Intelligence in Finance with John Hull

 

Professor John Hull enlightens us on the financial aspects of artificial intelligence and machine learning: applications, regulatory issues, and risks. He shares insights profiled in his recently published book, Machine Learning in Business - An Introduction to the World of Data Science (third edition) - and draws on concepts explored in his three best-selling books in the derivative and risk management area.