Clara Durodié

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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