- “Priyank Patwa, Head of AI & Machine Learning, M&G Prudential – My role is about creating an AI/Machine Learning community. The idea is moving from a central function that does everything, to a bottom up, where our businesses are empowered to adopt AI.
- Abhijit Akerkar, Head of Applied Sciences, Business Integration, Lloyds Banking Group. This is not new for finance – we are a data driven firm. We couldn’t make any decisions if we didn’t have data. But what’s different is the new techniques, which is what is very relevant for us. The ‘how’ is the most interesting bit for finance.”
Prioritising those use cases is important and dependent on a number of factors.
- Number 1, what is the size of the prize for this use case?
- The second is, what’s the feasibility? That has different dimensions – do we actually have the right data? Is this use case proven or are we trying to solve for the first time? Do we actually have the API pipelines running through?
- Also, how excited is the business sponsor about the opportunity?
- Will this be approved through a risk and compliance committee?
- The final criteria is, will this create impact this year?
If you look at data to value as a value chain, the first mile is data. We already have that in place to a certain extent. Although we might have a lot of data, getting that data ready through the data pipelines is moving a mountain for the first time.”