AI in the Financial Sector

Artificial Intelligence (AI) is a very popular topic, but how does it impact financial services? Are there pros and cons to this? What type of drivers are causing the surge of AI implementation within this sector? In this episode we explore all of that and more!  Mobeen Tahir, Director, Macroeconomics and Thematic Research at WisdomTree UK joins Cassidy Clement to discuss.

Summary – Cents of Security Podcasts Ep. 77

The following is a summary of a live audio recording and may contain errors in spelling or grammar. Although IBKR has edited for clarity no material changes have been made.

Cassidy Clement:

Welcome back to the Cents of Security Podcast. I’m Cassidy Clement, Senior Manager of SEO and Content at Interactive Brokers and today I’m your host for our podcast. Our guest is Mobeen Tahir, Director of Macroeconomics and Thematic Research at Wisdom Tree UK. Artificial intelligence or AI is a very popular topic these days, but how exactly does it impact financial services and are there actually pros and cons to this advancement? Also, what were the drivers in causing such a surge of this implementation in the financial sector? We’re going to explore all that more in today’s episode. Welcome to the program.

Mobeen Tahir:

Thank you very much for having me.

Cassidy Clement:

Sure. So just to jump right in, this is your first episode. Why don’t you tell the listeners a little bit about your background in the industry, how you got started, how you came all the way into the thematic area with AI and such?

Mobeen Tahir:

For sure. So I started my career as an investment consultant at Towers Watson, which became Willis Towers Watson and eventually WTW. And while I was there, I switched from the consulting side to the research side, which ultimately brought me to WisdomTree, provider of exchange traded products. Here, my role is that of a Market and Product Strategist. I try to weave narratives about what’s happening in the world of financial markets, economies, and most importantly, technological megatrends, which is an area of growth for the firm, but also an area of interest for me and indeed very relevant to our conversation today about AI. The goal ultimately is to help investors make informed decisions.

 There is no shortage of information out there, but we aim to add value by giving our own perspective that is ideally, timely and insightful.

Cassidy Clement:

There’s a big surge in terms of AI being applied or being talked about, written about. You know, there’s different drivers causing this for different sectors, but when it comes to the financial sector specifically, what are some of the drivers that you see causing this trend of AI usage being incorporated into operations.

Most people initially think, okay, customer service can be helped out with some automation, maybe some risk management areas, but what are some drivers that you see and that you found in your different pieces?

Mobeen Tahir:

I really liked, what, the CEO of Alphabet, said last year, Sundar Pichai. He said, when you go through a curve like this, the risk of under investing is dramatically greater than the risk of over-investing. And businesses across all industries and sectors are echoing what Sundar Pichai has stated here. The risk is that when. a disruptive technology like AI comes along, it can catch existing players off guard. You know, we saw this, with so many, businesses, you know, Uber appended the existing, taxi business model and, and the financial sector is exactly the same. You know, take investing as an example.

If someone wants to invest in say, the AI theme or any other theme, the menu of options is much broader today than it was a few years ago. And the menu just keeps expanding. So the main driver, why anyone would want to adopt AI and to innovate and to keep making sure that they are offering their customer the best experience possible is that the competition is just getting, fierce. And of course, anyone can adopt AI and really give their customer a better experience. So, we think that that is really the biggest driver and the risk any business faces is, the risk of under investing at this promising time when you just don’t know what the upside potential might be, but you don’t want to miss out.

Cassidy Clement:

Yeah. And I know you mentioned something about, I think you said Sundar Pichai had that, that quote, or that piece that you mentioned was a year ago and everything’s coming at lightning speed. I don’t think anybody five years ago would have been like, oh yes, you could have so many pieces be completely automated in the next five years. Most people didn’t think that, you know, you could have a computer in your pocket, but here we are. So when you’re looking at the financial services sector currently, how exactly is AI being used and are there certain businesses that are utilizing the technology more than others within the sector? Maybe it’s applications or brokers or banks, you know, is there one area that’s a little more concentrated than another?

Mobeen Tahir:

You could think about it in terms of two paradigms. There’s the individual level that people are adopting AI into their workflow and then you can think about what organizations are doing at the organizational level. So if we look at a few examples of what people might be doing at an individual level, I speak for myself as a researcher who writes a lot, I’m using large language models, you know, the likes of, ChatGPT and so forth to help proofread some of my writing, to summarize things that I want to summarize and shorten. To even brainstorm ideas of things that I want to write about and so forth. Similarly, I see other departments in the organization using other AI tools, like the marketing department may use AI tools for designing better graphics for editing videos, and so forth. The IT department might use AI tools for coding or for identifying issues with various applications and so forth. So there’s productivity enhancement happening at the individual level, but then at the organizational level in the world of asset management, where I come from, there is a lot of data and wherever there is a lot of data, AI lends itself very well because we deal with economic data, we deal with corporate data, we deal with customer data, competition and so forth.

And ideally, what you want to do is automate that process of analyzing, and interpreting all of that data so that people like me and my colleagues, they spend most of their time drawing insights rather than collecting and organizing that data. And that’s where AI really comes in, streamlining and automating the processing of that data, to really free up the people to do more value added things going forward. So that’s, I think, where organizations are looking at ways to implement AI at that layer. But I think we are only just getting started. I think there’s a lot more that we will see companies in the financial services do in the months and years to come.

Cassidy Clement:

You mentioned a good point there which is the viewpoint of the company to the individual and then we’ll talk about the customer perspective, but from the individual and the company perspective of how AI is utilized, whether we’re talking about task execution or different types of risk management, automation, et cetera, you know, it’s centralized on the idea of increasing productivity, increasing efficiency, increasing service level. But when we look at the actual customer, who’s then getting an end product after, there’s a lot of automation now going into the creation of this end product. How exactly does AI help the customers of financial services or in the financial sector?

Mobeen Tahir:

Yeah. So customers, when they engage with financial services, they want a speedy response and they want a personalized response. And now even more so than before, because people have got a taste of tools like ChatGPT, which can give them personalized responses and very speedy responses. So they expect the same from their service providers, even in the financial services. So, you know, it’s funny because sometimes when I tell people I work in finance, they ask me for investing advice. And my instinct is, especially coming from a consulting background at the start of my career, my instinct is first to say that I’m not a financial advisor. And the second instinct is to ask them dozens of questions.

I want to know lots of things about you before I even attempt to give you any suggestion about what might be a good route for you to go down but this is where AI can help. Now, if you think about people trying to brainstorm ideas about how and where to invest. We in the world of asset management, use terminologies like model portfolios. You know, what sort of an, a portfolio works for you given your own unique circumstances? You know, do you want to be investing in equities? You want to be investing in bonds? Do you want to be in looking at other asset classes? How will you build an equity portfolio and so forth? Given your age, your income, your goals, your constraints, your special circumstances, I mean, these are the sorts of variables which will determine where you put your money in. And this is where tools like AI can really help because it can gather all of that information. It can take the menu of options that is out there and it can maybe match the two things together so that you at least have a good starting point. It may not be a perfect solution, but it may be a good starting point to kickstart a conversation.

And that’s where people like us come in, that we can facilitate that conversation, but AI can certainly get that conversation going. So, wherever there is an opportunity for a customer to have a speedy experience and a personalized experience, we think AI will certainly play a larger role going forward.

Cassidy Clement:

I think the personalization area is probably where customers will start to see, I guess, the power of incorporating something that has the ability to retain, I guess, a history or an understanding and a little bit more depth than sometimes just a service representative or a notes file that gets passed around within you know, a service center. But with all of this, I can’t help but ask, there are so many amazing things that can happen and it seems like an optimization of operations efforts, but is there, downsides or any potential downsides to using this, especially within the financial sector, or to using this, I guess, in some sense, prematurely, where there’s not as much understanding as, we’re kind of at you know, the beginning of the birth of AI in the workplace.

Mobeen Tahir:

Yeah, I recall when I started my career in financial services, which wasn’t that long ago, but, just consider that we used to have physical files in the office. Like we used to print stuff and file it physically. And of course, if someone wanted to hack that system, they would have to physically enter the office and maybe steal the file. We’ve, of course, moved on since then. Most workplaces now have digital records. And of course, hacking a digital record is a different enterprise altogether. But with AI, what is happening is we are creating more data and we are storing more data and we are creating a bigger risk of that data going into the wrong hand.

So cybersecurity is that potential downside risk, which is very important to consider, especially for the financial sector, because This is a sector where trust is a very big deal. Now, of course, trust is a very big deal in any sector, but the financial sector is holding people’s money. It’s, very important for people to have enough trust in the system that their finances are secure. And at a time when cyber attacks are becoming more sophisticated because AI is a tool. If you give it to the wrong people, they will do it. They will use it to do more sophisticated bad things. And that is what we are seeing in terms of more sophisticated cyber attacks.

And that is what we are seeing is where the defense side becomes even more important. The defense has to adopt AI as well, whether it’s individuals, businesses, countries, anyone that is, storing data somewhere. They will need to employ better cyber security tools because the downside would be an erosion of trust if you don’t have your guardrails in place.

Cassidy Clement:

It’s super important to be able to validate some of these, what we’ll just say, very large investments into AI optimizations within especially financial systems. It’s a lot more than just necessarily optimizing a supply chain to get sneakers from a warehouse to someone’s closet. It’s, you know, people’s life savings. When we look at the current utilization of artificial intelligence in finance, usually people will throw around the ideas of, okay, the risk assessment. Use case, the activity with the user in terms of fraud detection or maybe customer service or advisory services. But if you will humor me, in the future, what ways do you think that AI could be utilized in the financial sector if a lot of these models and use cases get extrapolated?

Mobeen Tahir:

You know when generative AI came along, it got people like me very excited. I say people like me because I’m not one of those who are proficient at coding in many computer languages. And that, of course, is something that I can overcome with the use of generative AI tools because until now we’ve had to learn the language of the computer and many of my colleagues are extremely proficient at doing that. But now there’s a situation where the computer has learned our language as well and that is very interesting for people like me who didn’t have the ability to speak in the computer’s language, that now I can communicate with the computer in English and do more sophisticated things. Like if I wanted to plot a chart using lots of different data, if I could just give the application an instruction in plain English, that this is what I want to achieve.

This is the data set, now create something meaningful for me. This is the sort of trend that we are seeing. So people working inside the sector will probably make use of AI tools like that. From a customer’s perspective, because we’ve spoken about the customer earlier as well, I see financial education has a very exciting opportunity where AI can play a role. Like, just simple things like the power of long term investing, like the notion of compounding over long periods of time. Just, if you hold a simple investment that gives you a steady return over a very long period of time, that can compound to an astounding number.

 Even people working in financial services sometimes get absolutely bamboozled by some of these reports that you see about long term return outcomes and compounding and so forth. Even though we understand the principle, it’s just mind boggling to the mind. And that’s where AI can play a great role, to educate more people about basic financial concepts that can help them make more informed decisions about their finances knowing your biases is another one. You know, people are susceptible to making biases when it comes to making investment decisions. We always say past performance is no indication of future results, but even institutional investors can fall into the trap of gauging the merits of an investment opportunity on the basis of past performance.

That’s human susceptibility there. We know that ideally you want to buy low and sell high, but people fall into the trap of selling when things are down and buying when everyone else is buying. So you’re buying at higher prices. So these are the sorts of biases where a better understanding of our own biases and understanding of financial principles can help us make more informed decisions. And I think that’s where AI will play a larger role in the years to come. Because again, going back to personalization, it can give you a tailored response. And if you were speaking to Warren Buffett, you would explain a financial concept very differently, compared to if you were speaking to a five year old child.

They both might be very smart and might bring very intelligent perspectives to the conversation, but the way you will explain a concept will be very different. And that’s where AI comes in because it can do that. It can give you a personalized experience. It can give you a tailored response. And that is very promising in educating the generations to come.

Cassidy Clement:

Yeah, I think we are a lot closer, I guess you could say, to the starting line than the finish line when it comes to AI. I mean, it’s not like it launched last night, but we are kind of just at the beginning of what can be accomplished with this type of technology and this style of machine learning and modeling. But you had brought up a lot of really great points today. Thanks so much for joining us on the podcast.

Mobeen Tahir:

Thank you so much.

Cassidy Clement:

Sure. As always, listeners can learn more about an array of financial topics for free at interactivebrokers.com/campus. Feel free to leave us a rating or review on your favorite podcast network. Thanks for listening, everyone.