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Online seminar – Artificial Intelligence and Systemic Risk

When:
October 24, 2019 @ 1:00 pm – 2:00 pm Europe/Rome Timezone
2019-10-24T13:00:00+02:00
2019-10-24T14:00:00+02:00
Where:
FBF Online Platform
Cost:
Free
Contact:
Jan Trevisan
+39 055 4685 802

Download the presentation

 

Artificial intelligence (AI) is rapidly changing how the financial system is operated, taking over core functions because of cost savings and operational efficiencies. AI will assist both risk managers and microprudential authorities. By the same token AI has also the potential to destabilise the financial system, creating new tail risks and amplifying existing ones due to procyclicality, endogenous complexity, optimisation against the system and the need to trust the AI engine.

In this online seminar, Professor Jón Daníelsson, Director of the Systemic Risk Centre at the London School of Economics, will discuss this topic on the basis of the most recent results of his research, published in a paper in June 2019. The presentation will be followed by the intervention of a discussant and a Q&A session with the public.

 

Speaker

Jón Daníelsson
Jón Daníelsson is director of the ESRC funded Systemic Risk Centre at the London School of Economics. He received his PhD in economics, where his dissertation focussed on stochastic volatility. His research interests include systemic risk, financial risk forecasting and financial regulations. Jón has written two books, Financial Risk Forecasting and Global Financial Systems: Stability and Risk and published a number of articles in leading academic journals.

 

 


 

Technical disclaimer

The online seminar will take place on the Adobe Connect platform. You can access the seminars from personal computers, laptops, tablets and smartphones. You are strongly encouraged to read the technical requirements before registering for the online seminar. To ensure an optimal experience in terms of connection speed and video quality, we suggest to attend the seminar via a device connected to a stable network connection, avoiding if possible shared wi-fi or mobile connections.