Transcription:
Penny Crosman (00:03):
Welcome to the American Banker Podcast on Penny Crosman, which fintechs are likely to attract investment in the coming year and perform well, and which you're likely to struggle. Our guest today is Arvind Purushotham, head of Citi Ventures, and former managing director at Menlo Ventures. Welcome Arvind.
Arvind Purushotham (00:22):
Thank you, Penny. Great to be here. Great to speak to you again.
Penny Crosman (00:25):
Thank you for coming. Can you tell us a little bit about some of the companies in the current Citi Ventures portfolio, who have you invested in the past, and are there any sort of themes among those companies?
Arvind Purushotham (00:41):
So Citi Ventures is Citi's strategic investing group, and we're generally aligned with our businesses strategy when it comes to the kinds of investments we make, there are two broad categories of investments that we make within Citi Ventures. One is in FinTech as it relates to our frontline products and services. An example of a company in the FinTech space that we been investors in is a company like Plaid that many people in the FinTech world are aware of. It enables fintechs to connect with bank accounts, aggregates account information, and provides all kinds of other underlying infrastructure services. Another example in the enterprise space is a company like Netskope in the cloud security area. Cloud obviously has been a growing area over the last several years, and securing what's in the cloud is one of utmost importance to all enterprises, not least in the financial services area. And so Netskope has been a leader in that cloud security space. So these are examples, one on the FinTech side and one on the enterprise price side. But over the last 14 plus years, we've been investors in over 150 companies across both FinTech and enterprise categories.
Penny Crosman (02:03):
That's a broad portfolio. So in a recent blog, you said you were thinking about three main investing themes for the coming year. The first one was generative AI is on the rise. From your perspective, where do you see generative AI the most useful, especially in financial services firms?
Arvind Purushotham (02:27):
Yeah, generative AI has obviously been sort of seen that meteoric shift in how people think about AI as it applies to the world in general, but certainly a very important in financial services. And so for the last nearly two years, our team and city has been thinking about generative AI as it applies to cities, businesses, cities functions, and again, how we interact and serve our customers and clients. And one of the areas and the thing that we have done is essentially evolved with the industry. One, it's an extremely dynamic space, so we've been keeping tabs on what's happening in terms of just the technology developing and maturing. And we've seen that technology developed at a rapid, rapid pace, and so we've been keeping tabs of it. Secondly, we're collaborating with our internal technology teams, the teams that are responsible for bringing in generative AI technology components in capabilities in how and making it available to our employees and to our businesses.
(03:39):
So we've been collaborating with them internally. And then thirdly, really focusing on the real world use cases of gen AI in financial services, how to do it in a safe and sound manner, how to do it in a compliant manner with privacy in mind, with security and soundness in mind. So we've been quite intensely focused on this generative AI as a space. I would say Citi recently actually released two internal tools. One is called Citi Stylus and the other is called Citi Assist. These help colleagues at city summarize reports and navigate internal policy and processes documents. These are the first two broadly applicable AI tools that Citi released internally. But more generally when it comes to, for example, software development, that's an area where Citi has been leaning forward. They rolled out a copilot across several thousand software development professionals at Citi last year already. And we're starting to see the productivity gains at scale in terms of what the copilot and copilot technologies can bring. And then we're also looking at how we can apply gen AI to the compliance space and RegTech space and all other aspects of working in a financial services institution. If you just think about AI and gen AI specifically, I think there's extremely broad applicability for that technology within financial services. So we're very deliberately thinking about what that intersection looks like and how to do it in a way that is safe, sound and compliant.
Penny Crosman (05:29):
Yes. And I know we spoke with Citi earlier when you rolled out the copilot to software developers. Are you starting to see results from these efforts and pilots so far in terms of hours saved or any kind of efficiency metrics that might be improving with these assistive technologies?
Arvind Purushotham (05:53):
I don't think we have released any results and numbers yet as a company regarding our own internal efforts and any productivity gains we're seeing within Citi. But I can speak more generally about what we hear externally when we speak to industry professionals that are at tech companies, for example. And when you think about software development, which is one of those primary areas for gene ai, we hear about productivity gains that they are seeing, and these are industry professionals saying people who were skeptical before who then started to use gene AI and copilot technologies and then are starting to see the productivity gains. So we're starting to see that happen just as an industry externally. But from within city standpoint, I don't think we have released any of the results yet. In many ways, these are early days. I think there is no doubt that there will be benefits to be had from AI and gen AI technologies, but I think that those results have not been discussed yet.
Penny Crosman (07:07):
When you are looking at generative AI companies, whether to partner with them for internal city purposes or to possibly invest in them at Citi Ventures, what are some of the things that you look for there? Are you looking for, there's obviously some risks in terms of hallucination and error and data privacy because this is still a relatively new area and the regular rules of engagement have to be implied here as they are everywhere else. What are some of the things you look at when you are vetting these companies?
Arvind Purushotham (07:53):
I think the first aspect of what we look for is whether the company is serving large enterprise is able to serve large enterprises and specifically financial services. I think financial services is more complicated given the regulatory and compliance requirements, the data privacy requirements, what can live in the cloud versus what has to live on-prem, things of that nature. And so we look at whether the company is targeting its products and services to large financial institutions. Many in fact do because it can turn out to be a large industry vertical for many of these technology companies. And so when we look at startups, there are obviously companies that are targeted mainly to, let's say creative individuals, creative professionals, or to consumers. And we look for more to the, and specifically within enterprise, the financial services focused companies. And so one example of a company that we've invested in the gen AI space, Penny is a company called LA Cara.
(09:09):
It's in the safety and security space. It provides prompt security as you, I think alluded to before, there are hallucinations and other kinds of issues you can have. And so we invested in this company called LoRa, that's one of the earlier companies looking at prompt, security, safety and soundness. The other part of the type of companies we invest in are companies like Norm ai. Norm is an AI powered regulatory compliance platform for legal and compliance use cases. And so we're looking at whether Norm can help our compliance teams with more rapid review, with more scaled ability from a technology perspective to review our documents, our marketing documents, et cetera, by comparing that to the requirements from our policies, from regulatory compliance requirements, et cetera. And we're looking at that and saying, okay, well Norm is able to do that. They already have some customers in the financial services area and maybe they can serve some of the larger banks as well. So that's an example of a company that's specifically targeted towards financial services companies. And so I think there are companies like Norm specifically targeted towards financial services, other companies that are more broadly enterprise oriented that already have shown some interest in asli or actually landed customers in financial services companies. So we've invested in some of those and then we're investing in some safety and soundness type of companies like a Looker.
Penny Crosman (10:50):
That's interesting. And when you're vetting these companies, are you bringing some of your internal folks in to look as well, like the people who are familiar with the regulatory and compliance software, you already have to make sure it's going to be a fit and make sure it makes sense in an environment like yours?
Arvind Purushotham (11:12):
Yeah, we absolutely do. I mean, as a strategic investment unit, we want to make sure that the companies that we invest in are a fit for us, both not just from an investment standpoint, but also from a commercial usage standpoint. And in many of the colleagues within our technology business or whether it's inside the technology group or within our business units are the experts. They're the practitioners on the ground. And so we certainly leverage their expertise a to just as a part of our due diligence. We want to get the opinions of experts as a part of our investment due diligence, and B, we need to explore the fit with Citi even without doing a pilot or without actually implementing a proof of concept or something like that. In many ways, by talking to a company, you can figure out what is the architecture and does this architecture and solution, is it actually usable at Citi?
(12:17):
And so that high level take on whether a solution can be a fit is something that we get right upfront. If there is a company that can just cannot be a fit because it's completely in a different way, maybe the customer segments that they're going after are very different, then it's not a fit. And so we end up not pursuing those types of opportunities. And we do that by bringing in the internal technology experts, whether it's on AI or from our business units in early to evaluate that fit with us, explore what a potential partnership could look like.
Penny Crosman (12:54):
Sure. So your second theme is that embedded lending will shift into overdrive in the coming year. Can you give an example or two of where you think this will be really popular? Are these buy now pay later kinds of loans that might be at a retailer site or car loans or other? What types of loans do you think these might be?
Arvind Purushotham (13:20):
One of the things about embedded lending is we're starting to see embedded lending happen across the board, whether it's for small businesses for, you mentioned auto loans. So we've recently seen companies in the auto loan space. We have started to see embedded lending types of opportunities for not just consumers, but also the small businesses that are auto dealers, certainly the NPL type companies. And so if you look at the entire lending spectrum, other than some of the largest types of credit and debt, which are sort of more enterprise and big financial institutions and big private credit and so on and so forth. If you leave out the largest ends of the spectrum, if you think about both consumers and small businesses, we're starting to see the proliferation of embedded lending. I think embedded finance and FinTech as a theme, that's something that we've been exploring for many, many years.
(14:25):
We've made investments in that space. And the whole idea is people don't want to go to a bank website or any other financial services website to sort of do that financial transaction. They want to achieve some other goal in their life. They want to get credit or purchase something or enable a shipment in logistics world, for example. And so by partnering with those kinds of companies that, whether these are e-commerce companies or small business logistics companies or freight companies or whatever the case may be, if you can provide payments, if you can provide lending, if you can provide other types of financial services in the flow, I think that that's what really makes it easy for customers and clients to operate and work with a bank, work with any financial services institution for that matter. And so this embedded FinTech has been a theme, and obviously that is driven by the availability of mature APIs, about knowledge of utilizing data, how to secure these transactions, et cetera.
(15:44):
Like all of those underlying technologies have come a long way. So now that is starting to see real world impact, whether it's in the consumer space, whether it's in small businesses, whether it's in various different industries. We're starting to see embedded FinTech happen. And so I think many of our companies are in the embedded FinTech space. Some of them are more payments companies that would like to get into lending, and so we can be a partner for these companies in the lending space. And so we think that it's an area whose time has come. I think we're going to see some very scaled companies in 2025 in the embedded lending area.
Penny Crosman (16:28):
Do you think that AI is going to have an impact here as well? I know some small business banks or some banks that serve small businesses are starting to use AI in their lending decisions. Do you think that as you look into this area, you're going to be probably looking at some AI or gen AI companies here as well?
Arvind Purushotham (16:53):
I think the usage of AI for underwriting is still something that we're not seeing happening at scale. Now. We're starting to see startups that are trying to use AI for underwriting, but that is an area exactly where compliance and regulations come into play for a large financial institution like Citi. So I think among the, we're starting to see some sort of lower scale usage of ai, smaller startups starting to use it, but not so much the larger companies yet Penny, because of many of these compliance and regulations and requirements around lending. So given that, I think we do believe that AI can play a very important part when it comes to underwriting, but it's not something that we have seen yet. It's not something that we have invested in yet. But AI can play a very important part in lots of other parts of lending.
(17:59):
For example, when you think about identity, when you think about onboarding, when you think about an area that we've looked at and invested in is in anti-money laundering and how do you bring AI to that space? We're investors in a company called Quant that it brings in AI to do a better job of anti-money laundering and being compliant with anti-money laundering requirements, KYC. So there are many of those areas where you can bring in ai. And even though that's not underwriting per se, I think that even those provide significant impact and benefits for a financial institution and frankly even for consumers. Does that make sense? I mean, I think it's underwriting at scale large, especially for consumers, that's a harder area and it's not something that we have seen startups do yet.
Penny Crosman (18:57):
Sure. And you can't invest in everybody, so perfectly legitimate reason not to go there. So your third theme is E-commerce gets hyper personalized. And to me, that's interesting. I've been in this space a long time, and it seems to me that personalization has always been a holy grail. And it used to be that big data was going to give you personalization, and then it was AI was going to give you personalization. Now it's generative. AI is going to give personalization. And it always seems like it's tricky because if one piece of data is wrong or missing, then the resulting recommendation can be totally off. And if it's a book recommendation from Amazon, who cares? But if it's your bank telling you to do something or your financial advisor is telling you to do something that's a little bit more serious seeming, I think. And then on the other hand, there's the concern that a bank doesn't want to be using too much consumer data for a purpose other than the purpose for which the data was gathered and violating some kind of data privacy rule or even seeming too big brotherish or creepy. How do you envision e-commerce getting hyper-personalized and walking that middle ground of having the insight into the individual person without overstepping anything?
Arvind Purushotham (20:35):
Yep. It's very fair question. I think I'll sort of talk about two aspects of this, right? The first aspect of it is e-commerce getting hyper-personalized because of what's happening with data and what's happening in online networks and so on and so forth. And then secondly, the role that we think Citi could play or any large financial institution can play in terms of and how it relates to our business, right? On the first part, what we're noticing Penny, is I think you can see this on a personal basis, that when people are on various social sites, Instagram or other social sites, the kinds of ads that you're being shown are extremely personalized. What you see may not be the same ads, or definitely not the same ads as your children may see or your partner see, or whatever the case may be. And the algorithms that these social networks and other large scale platforms and big tech companies use, they've become very smart about identifying and learning about the needs and interests of different consumers.
(21:55):
And so I think the combination of the amount of data that's out there, the power of the algorithms that power these sites and search engines and whatnot, and these social networks, all of that is leading to learning a lot about the consumer. And I'm talking about the e-commerce sites, learning a lot about consumers, e-commerce sites, the purchasing data about consumers and being able to target consumers very effectively. So that's happening in the e-commerce world, and we are seeing that get better and better in terms of targeting and personalization and so on and so forth. I think the role that we think of playing in this world is, as you know, Citi has a large credit cards business. There's a branded and co-branded cards business as well as a retail services business where we partner with companies such as Home Depot and across these, and we have a lending business related to the cards business as well.
(23:01):
When we talk to the business unit leaders, I think for us, being top of wallet is important. How do we make sure that we can help our credit cards and lending businesses stay top of wallet with consumers? How do we make sure that our credit card and lending businesses are staying abreast of what's happening in e-commerce and sort of the cutting edge of e-commerce and how people are being targeted, and how do we make sure that we connect the two worlds, right? So enable perhaps some partnerships that allows for Citi's customers to benefit from being associated with Citi and shopping at a particular site. And that comes back to loyalty. I mean, loyalty is a big aspect of our consumer business. As you know, we have some big loyalty programs, whether it's with Costco or American Airlines and others. And we also have been thinking a lot about loyalty last year and in 2025 and beyond.
(24:07):
And so when we connect that world up, the loyalty world with e-commerce, I think there can be some powerful synergies there where Citi will partner with e-commerce websites or other such vendors and providers to make sure that customers are getting a great experience while obviously benefiting our business from a top of wallet perspective. And I think the approach is not that Citi would use our data to do more targeting. I think it's essentially partnering with a retailer, partnering with other such platforms to make sure that we're able to get to consumers at the right time, in the right way with the right product.
Penny Crosman (24:57):
Okay, that makes sense. So when you are looking at a startup meeting with the team, considering investing in a startup, what are some of the things that you are looking for? What are the qualities and characteristics that you care about the most?
Arvind Purushotham (25:16):
Investing is such a learned skill that's learned over many years, over many investments, understanding what works, what doesn't work, and a lot of pattern recognition around it. My simple way to think about any investment is sort of looking at the controllables versus the non controllables. When you think about what startups are successful and what startups end up not being successful, there are certain uncontrollables like market conditions for example, or the pandemic event that obviously was quite disruptive to many companies and many industries. There are uncontrollables that we all have to face out there in business, and those things we can only make some best guesses about. But otherwise, the team, there's little the team can do about it among the controllables. I mean, that's where you really look and really focus on the team. And there's this sort of a thought process out there that you really look at the team for the very early stages, and then once you get to the later stages, the evaluation of the team becomes less important because the company has already proven that they can put a product out there that the customers are buying the product, it's already scaled to, let's say tens of millions of revenue or whatever the case may be.
(26:48):
But I would posit that the team is important even then because then you're looking at a company at a later stage, but then you're looking at that team to see if the team will now scale to take it to hundreds of millions of revenue. And so at every stage of a company's growth, needless to say, the team is extremely important. And what is it about the team that we look for? One is we look for the resilience of the team to be able to handle many of the things that change in the environment. Can they react to it? Can they pivot if required? Can they be agile and flexible to make sure that they achieve that product market fit? That's number one thing that we look for. Secondly, we look for excellence. So startups can only succeed if they have an excellent product or a service out there to beat the incumbents to create a new market, whatever the case may be.
(27:51):
And so the team needs to know what does good look like? What does excellent look like? How do we deliver excellence? And then continues to drive for excellence in serving their customers and clients. And so that's the second thing that we look for. Third, and is the tech aspect of it. And this I say more from the point of view of FinTech. In FinTech, many times we're looking at businesses and we're asking ourselves, what is the technology element in this FinTech business? Is it mainly fin and not a lot of tech? Or is there a pretty deep interplay interlinked between the fin and the tech so that it actually creates a moat? And so that last piece of it turns out to be important for many of our FinTech investments where we're asking ourselves and asking the company the question of how the technology that they've built, maybe the platform that they've built, et cetera, connects to the financial services that they're providing, how they handle data, how they deal with APIs, how do they deal with security, all of those kinds of things to make sure that there is a reasonable or a good moat for those things.
(29:06):
And all of that is driven by the team. And so I think whether it's an early stage company, the company is just getting a product out in the market, or it's a much later stage company, and the company needs to get to a few hundred millions worth of revenue in the next 2, 3, 4 years. I think you ask yourself the question, can this team get that company to the next stage? And that's what we focus on quite heavily. The last thing I'd say is in financial services, you also need the team that understands what it takes to operate in financial services. What do the regulatory needs dictate? What are some of the compliance requirements? Many entrepreneurs in financial services come from, maybe tech, maybe financial services, not the place that they come from, but do then in that case, do they understand what it takes? Are they surrounding themselves with people with domain expertise so that they can then sort of complete those requirements or understand the requirements around compliance and regulations and then deliver it in a proper manner, deal with regulators? Any scale financial services company will need to interact with regulators and have that relationship and manage that relationship. So we're looking for maturity in that area. Even if it's an early stage company, we want to make sure that people are thinking about it even though regulatory scrutiny may be further down the line for them.
Penny Crosman (30:37):
Yeah, that makes sense. We've certainly seen fintechs crash and burn for lack of expertise and attention to bank regulations. So that's a very important point. So thank you so much for sharing these insights and to all of you, thank you for listening to the American Banker Podcast. I produced this episode with audio production by Adnan Khan. Special thanks this week to Arvind Purushotham at Citi Ventures. Rate us, review us and subscribe to our content at www.americanbanker.com/subscribe. For American Banker, I'm Penny Crosman and thanks for listening.