J.P. Morgan hired Apoorv Saxena in August 2018 as its global head of AI and machine-learning services based in San Mateo, Calif, where he also oversees asset and wealth management artificial intelligence tech. Saxena previously headed product management for cloud-based artificial intelligence at Google.
Knowledge@Wharton: How is AI being deployed in different sectors in financial services?
Saxena: The maturity of deployment of AI varies significantly. Let’s take investment banking and trading. Here, it is used to gain insights from various data points and make actionable and executable [decisions]. In many ways, this is where you will see applications of AI using alternative data sets to extract information. (Alternative data refers to unstructured information from non-traditional sources, for example.)
In some areas that traditionally are heavily regulated, you see less application of AI. That is not because regulation prohibits it, but because the regulatory environment that tech infrastructure requires has not matured to a point that allows you to do AI at scale.
One area where we have seen significant and interesting opportunities is insurance. The ability to insure a product ultimately requires the ability to price risk more effectively. The pricing of risk has traditionally been done using limited data sets. [The effort here is to] apply new data sets and come up with a unique way of pricing risk. Another area where you will see significant application of AI is customer service. For example, could you file your auto claim using just a photo of your car damage, rather than calling 10 people and having somebody come to your place and make an estimate of your damage?
Knowledge@Wharton: You talked about how AI makes a difference in insurance, in the pricing of risk. The jobs of employees who are now involved in underwriting risk may be in jeopardy as AI programs perform those functions faster and more accurately. How will AI deployment affect employment in financial services? What should be done about that?
Saxena: This is not specific to financial services. AI is going to displace and automate big pieces of the service industries. There will be migration, where humans will be involved in providing higher value-added services. The same thing happened when ATMs were introduced. The initial fear was that ATMs would destroy the livelihood of tellers. Today, there are more tellers worldwide than we had when ATMs were introduced. The teller now delivers highly differentiated, value-added client services. The same thing will happen with AI. Going back to insurance since we talked about it earlier, somebody who comes to your place to have claims adjusted and assess the damage to your car can now talk to you about [improving your overall experience] and how they could help. Jobs in financial services will evolve towards providing more value-added features and away from the routine stuff.
Knowledge@Wharton: Why is JPMorgan Chase making such a massive bet on AI?
Saxena: It is driven as much by our leadership, in terms of how financial services should look in the future, as much as the financial reality of the marketplace. We fundamentally believe that AI will be transformative for the financial services industry but it will not be organic. It must be based on the capabilities that we have to build. This is not a short-term play, but a long-term, multi-year game.
JPMorgan Chase is investing in building the talent and the infrastructure that will allow us to do AI at scale. My joining this organization, and the team I’m building here in Silicon Valley, is one indication. We have hired Manuela Veloso, who is a top-notch AI researcher from Carnegie Mellon University to lead research.
We are also investing significantly and will continue to invest in our key initiatives to ensure we’re a leader in the AI space. We see this as a game-changer. Done right, this could be a long-term differentiator for us.
Knowledge@Wharton: Are there any lessons that the US can learn from China?
Saxena: Yes. The good thing that China definitely has going for it is scale. Clearly, firms in the US and elsewhere can understand [from China] how to build services at scale. That’s number one. Number two, China has been working actively to redefine financial regulation. I think there are lessons to be learned from seeing what others are doing around you.