Agenda

Agenda

Agenda: AI Innovation in Risk Management, online course

This course will be delivered live remotely via an online platform

Agenda timing is in GMT
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Session one - 2pm GMT / 9am EST
Session two - 3.15pm GMT / 10.15am EST
End - 4.15pm GMT / 11.15am EST
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Day one: Monday, June 15, 2020

14:0015:00

Identifying use cases for AI

14:00 - 15:00

  • In what areas is AI most effective 

  • Stress testing, early warning capability 

  • Assessing the availability and types of data 

  • Regulatory incidence associated with a particular area 

  • Is the data usable? 

Sebastian Ptasznik

Principal

Parker Fitzgerald

Sebastian leads the Credit Risk Methodology team within firm’s Quantitative Advisory Services. He specialises in quantitative analytics, credit risk modelling, macroeconomic forecasting, machine learning and data analytics.​  He has 11 years’ of quantitative analytics experience working for top tier UK and global banks, aerospace and defence, telecommunication and technology companies.​ Sebastian worked in credit risk modelling, model validation, and stress testing across retail and wholesale banking, as well as delivered a large scale data mining and machine learning projects.

15:0015:15

Break

15:00 - 15:15

15:1516:15

AI implementation roadmap

15:15 - 16:15

  • Identify the use case 

  • Match to process 

  • Implementation project 

  • Scaling across 

  • Identifying any skill shortages 

  • Creating a holistic AI strategy 

Ksenia Ponomareva

Global head of analytics

Riskcare

16:1516:15

End of day one

16:15 - 16:16

Day two: Tuesday, June 16, 2020

14:0015:00

Preparing your data for AI and ML

14:00 - 15:00

  • Mitigating bias and error 

  • Developing an appropriate data foundation for AI 

  • Continual maintenance of data quality 

  • Ethical considerations 

  • Finding the right sources of data 

15:0015:15

Break

15:00 - 15:15

15:1516:15

Group discussion: creating a culture that supports AI innovation

15:15 - 16:15

  • In a period of increased cost how can you still encourage innovation 

  • Structures and working groups that encourage innovation 

  • Common mistakes 

16:1516:15

End of day two

16:15 - 16:16

Day three: Wednesday, June 17, 2020

14:0015:00

AI and operational risk

14:00 - 15:00

  • Current operational risk challenges 

  • NLP in incident categorisation 

  • Building risk taxonomies for risk libraries 

  • Digitisation 

  • Potential operational risks associated with AI tools 

15:0015:15

Break

15:00 - 15:15

15:1516:15

AI - innovating with confidence

14:00 - 15:00

  • AI target operating models
  • AI model validation
  • Risk & control frameworks
  • Ethical AI
Alexander Denev

Head of AI - financial services, risk advisory

Deloitte LLP

Alexander Denev has more than 15 years of experience in finance, financial modelling and machine learning and he is the former lead of the Advanced Analytics & Quantitative Research at IHS Markit. He has written several papers and two books on topics ranging from stress testing and scenario analysis to asset allocation. He is currently writing his third book on Alternative Data in Trading&Investing. Alexander Denev attained his Master of Science degree in Physics with a focus on Artificial Intelligence from the University of Rome, and he holds a degree in Mathematical Finance from the University of Oxford, where he continues as a visiting lecturer.

16:1516:15

End of day three

16:15 - 16:16

Day four: Thursday, June 18, 2020

14:0015:00

AI and regulation

14:00 - 15:00

  • Opacity of the black box 

  • Use of AI in areas of high regulation 

  • Is this uncertainty inhibiting innovation? 

  • Council of Europe guideline for AI and data protection 

  • Leveraging historical data 

Fabrizio Russo

Head Of Data Science

4most

15:0015:15

Break

15:00 - 15:15

15:1516:15

Case study: portfolio optimisation tools

15:15 - 16:15

  • Standard portfolio optimisation analytic techniques 

  • Automated and semi-automated advisory activity 

  • AI across the rest of the AI value chain 

16:1516:15

End of course

16:15 - 16:16