This talk covers:
- Problems with ML – what got us here won’t get us there
- Regulatory convergence and the way forward
- Measures of Explainability, Trust, Fairness and Bias
- Causal AI as a 10X accelerator in Financial Services
- Examples of Causal AI in Fraud Detection, Credit Risk and Stress Testing
Time stamps:
0:33 - What do we do?
3:33 - Challenges with current ML approaches
6:55 - Intro to Causal AI
10:42 - Example: Causal AI for Fraud/Crime Prevention
20:32 - Example: Causal AI for Credit Risk
26:06 - Example: Causal AI for Stress Testing
33:54 - Summary and closing remarks