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Speaking Topics 

Business and governace implications of artificial intelligence in financial services


  1. Boards and AI strategy: modern governace 

  2. Cybersecurity and AI : fighting fire with fire 

  3. Artificial intelligence in plain English 

  4. Trust with Algorithms - what is it and how to build it

  5. Trust by design - how to start right

  6. What is good, robust high quality AI ?

  7. AI Ethics: a business case in financial services 

  8. The meaning of Trust with Technology

  9. Redefining Trust with AI in financial services 

  10. AI in finance function - use cases and areas for improvement 

  11. AI and Data Ethics in financial services 

  12. Thinking strategically about automation

  13. Linear vs Exponential automation

  14. Use cases of applied artificial intelligence in financial services  

  15. Future uses of AI/ML and business strategy impact 

  16. Global trends in AI adoption 

  17. Leading AI companies, cloud and the AI stack delivery

  18. How to pick the winners when selecting AI vendors - criteria for selection 

  19. Alternative data and AI: value and timing 

  20. Trends in natural language processing, data strategy and deep learning 

  21. Asset management: Distribution solutions and Customer engagement with AI

  22. Wealth management & private banking and AI solutions

  23. Back office automation with AI and where RPA sits in all of this

  24. Behavioural finance and AI

  25. Why is important to understand Intelligence: human and artificial 

  26. The need of Trust in financial services and how technology addresses it

  27. Cybersecurity and a safer world wit

  28. Importance of AI Ethics and responsible design

  29. Personalisation at scale: AI use cases in private banking 

  30. Philosophy of technology

  31. Data ethics and integrity 

  32. The macroeconomics of AI : key considerations

  33. Data privacy and AI

  34. Data commercialisation: use and abuse

  35. AI in asset management: how to benefit of AI adoption 

  36. Government AI strategy for financial services 

  37. Regulators and AI sandboxes: staying ahead 

  38. What's an AI and what’s not - implications for your operational model

  39. What AI can and cannot do for asset management 

  40. Fixed Income and AI: operations, default and scenario analysis

  41. AI Ethics in financial services: what do we need to know ?

  42. What is AI, why now and what’s in it for financial services ?

  43. AI and workforce impact: same people with new skills 

  44. Where to start with AI ?

  45. Central Banks and Deep Learning applications

  46. Labour markets and AI: will wages still be relevant ?

  47. AI and operational resilience in financial services

  48. Retraining your workforce: where to start

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