Insights: How A.I. Continues to Impact Financial Services
Executives from some of the world's biggest financial institutions explain.
[MUSIC PLAYING] LISA MARCHESE: AI is a much used term and I think everybody has a bit of a different definition of what it is. AMBER BALDET: A lot of the applications that we see today are really machine learning or even something that's a bit of a precursor to a robust machine learning program, but still very insightful. They offer new kinds of business analysis. SALLIE KRAWCHECK: AI can be a very exciting future for financial services. You think about its use in investing versus what the human brain is able to do. Through the use of technology, we can have more customized investment portfolios better suited to individuals needs, that don't panic in downturns, that I think can do potentially a better job than so many active managers have done for investors today. ADAM WHITE: So using AI well to me is just like any tool. It has to have the right application for the right purpose. And you have to do it in an endeavor to have a better outcome for the customer. Things like machine learning are going to be core to how we develop a product that suits our customer's needs. SIGAL ZARMI: AI has been proven to be a powerful tool. And the way we think about artificial intelligence and machine learning is really across all of our businesses. Not just in our sales and trading operation, but also in our wealth management and investment management operation. MARIE WIECK: I think the whole notion of machine learning accelerating and augmenting human intelligence and learning from patterns quickly is something that we're seeing help in multiple industries. So that you can really add nuance, but with a body of fact. AMBER BALDET: We need to remember, though, that those systems are created by people and inherit the biases thereof. And so we can't simply trust what comes out of a so-called AI system as though it's inherently smarter than us. And we need to constantly be checking that with our view of reality and the world we'd like to create. SALLIE KRAWCHECK: The challenge where AI and one of the things we're addressing, challenge with all technology, and one of the things we're addressing at Ellevest is the inherent bias. GREG BECKER: Machine learning and AI basically looks at historical data. And if historically speaking, industries have been discriminatory, you could end up perpetuating that discriminatory behavior if that's what it's learning from. SIGAL ZARMI: We need to be really careful with what we are asking the machine to do and how we are thinking and evaluating what the machines are doing. HIKMET ERSEK: I think AI information has to be also regulated. I mean, I'm not talking about overregulation. I mean, don't understand me wrong. But it's really misuse of the information has to be regulated in sake of the people. [MUSIC PLAYING]