The half day workshop on Wednesday 24th September is complimentary to all delegates: 13.30 – 17.00
Like humans, AI produces results that vary from one attempt to the next and sometimes make mistakes. This does not stop us from relying on humans, and it should not stop us from relying on AI.
The key to successful AI-based workflows is setting them up in a way that would help a human succeed at the same task. During this workshop, we will leverage this insight to build reliable AI-based workflows for several important use cases in trading and risk management.
Session 1 – Theory
- Types and underlying causes of model hallucinations and other errors
- Natural limits to AI-based workflow reliability and techniques to push past these limits
- Avoiding harmful cognitive biases in prompt and workflow design
- Confirmation bias
- Distinction bias
- Anchoring bias
- Availability bias
- Dunning-Kruger effect
- Using helpful cognitive biases in prompt and workflow design
- Framing bias
- Distinction bias
- Recognizing and overcoming the limitations to precise input recall
Session 2 – Practical use cases with Python
- Trading use case: AI-guided real-time parsing of trader chats for trades and quotes
- Securities use case: AI-based analysis of securities regulation compliance
- OpRisk use case: AI-based incident categorization
Session 1: 13.30 – 15.00
Coffee Break: 15.00 – 15.15
Session 2: 15.15 – 16.45
Q&A: 16.45 – 17.00
Alexander Sokol:
Executive Chairman and Head of Quant Research, CompatibL
Alexander Sokol:
Alexander Sokol: Executive Chairman and Head of Quant Research, CompatibL
Alexander Sokol is the founder, Executive Chairman, and Head of Quant Research at CompatibL, a trading and risk technology company. He is also the co-founder of Numerix, where he served as CTO from 1996 to 2003, and the co-founder of Duality Group, where he served as CTO from 2017 to 2020.
Alexander won the Quant of the Year Award in 2018 together with Leif Andersen and Michael Pykhtin, for their joint work revealing the true scale of the settlement gap risk that remains even in the presence of initial margin. Alexander’s other notable research contributions include systemic wrong-way risk (with Michael Pykhtin, Risk Magazine), joint measure models, and the local price of risk (with John Hull and Alan White, Risk Magazine), and mean reversion skew (Risk Books, 2014).
Alexander earned his BA from the Moscow Institute of Physics and Technology at the age of 18, and a PhD from the L. D. Landau Institute for Theoretical Physics at the age of 22. He was the winner of the USSR Academy of Sciences Medal for Best Student Research of the Year in 1988.
Abstract to be confirmed…
Session 1: 13.30 – 15.00
Coffee Break: 15.00 – 15.15
Session 2: 15.15 – 16.45
Q&A: 16.45 – 17.00
Ioana Boier:
Ioana Boier:
Ioana Boier: Senior Principal Solutions Architect, NVIDIA
I have a Ph.D. in Computer Science from Purdue University. In addition, I have completed graduate coursework in Financial Mathematics at NYU and Big Data at Harvard University. Prior to joining Citadel, I was a Director in the Global Markets Division at BNP Paribas where I managed the Interest Rate Options & Inflation quantitative research team. Before transitioning into Finance, I was a research staff member at the IBM T. J. Watson Research Center.
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