A.I. might be one of the newest hypes but it’s really helping you with the oldest problem: making a decision. Learning from our past projects we developed an introduction to machine learning that enables the audience to shift their focus from technology to their own decisions. By the end, listeners can point out where in their own realm A.I. is an option and where it is just buzz.
Key takeaways:
1. Be able to better identify the false promises in today's overwhelming A.I landscape.
2. Get an overview of A.I. projects/use cases from the financial industry that have an important business impact.
3. First steps to take ad a business leader to implement A.I technology in your department or company
A highly relevant use case of AI in finance is to provision new risk-related insights from data that enable improved decision making by man or machine. A recent example of how to use advanced analytics to foster insight is the creation of the first picture of a black hole from radio signal based on Bayesian updating. Similar approaches help financial market participants with managing the risk of low-probability / high-cost events, colloquially known as black swans. This will be highlighted by using recent examples concerning the quantitative effect of sustainability risk.
