Agenda

Agenda

AI Innovation in Risk Management: Agenda


Live virtual course | Agenda timing is in GMT/EST

Start: 2pm GMT / 9am EST
End: 4.15pm GMT/ 11.15am EST

14:0015:00

AI - innovating with confidence

14:00 - 15:00

  • Challenges of algorithmic and AI fairness in financial services
  • Complex sources of bias throughout model development lifecycle
  • Key ethics indicators and calculating trade-offs between objectives
  • Case study: credit risk evaluation in mortgage lending and peer-to-peer lending

15:0015:15

Break

15:00 - 15:15

15:1516:15

AI and operational risk

15:15 - 16:15

  • Current operational risk challenges 
  • NLP in incident categorisation 

  • Building risk taxonomies for risk libraries 

  • Digitisation 

  • Potential operational risks associated with AI tools 

16:1516:15

End of day one

16:15 - 16:16

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

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 day two

16:15 - 16:16

14:0015:00

AI implementation roadmap

14:00 - 15:00

  • Identify the use case 

  • Match to process 

  • Implementation project 

  • Scaling across 

  • Identifying any skill shortages 

  • Creating a holistic AI strategy 

15:0015:15

Break

15:00 - 15:15

15:1516:15

Identifying cases using 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?

 

16:1516:15

End of day three

16:15 - 16:16

14:0015:00

AI and regulation

14:00 - 15:00

  • Opacity of the black box 

  • Guidelines of AI in financial services

  • Current applications of AI in financial services 

  • Making AI safe and robust to use

15:0015:15

Break

15:00 - 15:15

15:1516:15

Towards an optimal AI adoption

15:15 - 16:15

  • Current state of enterprise-wide AI adoption

  • Key differentiators and transformers

  • Common challenges and lessons learned

  • Final takeaways

16:1516:15

End of course

16:15 - 16:16