Riskified Ltd. (RSKD) Earnings Call Transcript & Summary

All right. Kicking it off today, so I'm Will Nance, I cover payments and fintech here at Goldman. Excited to have Eido Gal from Riskified here. First time joining the conference. So really excited to have you guys. Eido is co-founded the business less than a decade ago and has overseen the company's growth and partnerships with top eCommerce merchants in the industry. So Eido, thanks for joining us.

Great to be here, Will.

So I believe it's the first time having you out here. I wanted to maybe level set a bit, the company has been public for about 3 years now. Where is Riskified and its journey as a public company? And what is your vision for where it can go over time?

So look, I think, hopefully, if you talk to our customers or kind of investors do references with our customers, they would say, hey, -- we've tested them. We tested them against our internal team, against other solutions, and we think they're the most accurate at identifying eCommerce fraud. So I think that's the situation today. I would say that over the next 18 months, I hope and believe we'll be able to expand into solving more significant use cases or just more use cases, I should say, around policy and dispute management and be a more integral part of our merchants' workflow. And probably slightly longer horizon, let's call it, 36 months. I think we would be doing more and more things like the enhanced -- bank authorization that we talked about the previous earnings where we're leveraging some of the unique data that we have and leveraging that within the payments ecosystem to increase autorite or performance for our enterprise eCommerce merchants. So I think that's kind of the trajectory product side that we're heading.

Got it. That makes sense. So maybe could we unpack a little bit just how you think about the growth algorithm for the company? You have -- this kind of land and expand sales motion with customers. You've also added new products and verticals, new geographies. So how do you kind of think about what the growth should be for this business longer term?

I'm going to move a bit like this. Right. So I think, look, by the way, related to the IPO, we incrementally started investing more in the go-to-market to go over kind of a global opportunity. And I think we're seeing thinking about the growth algorithm, obviously, there's adding new merchants to the core chargeback guarantee platform. And I think that's been going really well for us. The contribution from that segment this year is going to be higher than prior years. It's going to be higher than the previous year. So that's going well. And a lot of that is the expansion, some of the other things we talked about. Another part of the growth algorithm is around the newer products that we discussed, right, the Policy Protect, the Dispute Resolve. And I would say that's growing exponentially, that's great. The 3x growth year-over-year. Unfortunately, that's still a small base, right? So about 0.5% contribution to the gross margin is what we've shared. I do feel great about kind of the pipeline, the traction if we can continue to see some of this percentage growth, it should be meaningful relatively quickly. The net dollar retention, the other piece of the growth algorithm, which historically even pre-COVID has been the 115 to the 120 range has been lower over the past 2 years, around the 105 range. This year, we think it might dip below slightly below 100 as well. And a lot of that or predominantly, that's because of the macro pressure that our merchants are seeing in a lot of the discretionary categories, whether it's travel, luxury, the home category. So that's been a headwind recently. And I think retention metrics have been kind of somewhat consistent in the 98% range over the past few years. This year, they might dip slightly below that to the 97% range. So I think that's how we kind of imagine the growth algorithm.

Got it. That makes sense. As you kind of pointed out, the macro environment has been really choppy. The consumer has been dealing with high inflation for a while, there's been a lot of sort of reallocated spend under the surface of what looks like kind of more stable spending pattern. So what have you seen in the business? And is there anything to call out more recently?

I think we've seen -- let me highlight a few verticals, and I think it's consistent with what these verticals have been saying publicly, and it's kind of full understood, but maybe how that impacts us -- is what I should explain a bit more, right? You have the home goods category related to furnishing, people are remodeling, high interest rates, those people are moving with. Houses are being bought. So that's been trending downwards. Fashion, especially kind of the high end, the aspirational shopper, but also the highest end luxury has, especially on the e-com side, has been trending downwards relative to kind of expectations at the beginning of the year. I would say that travel, while it's still strong, we're not seeing the type of explosiveness that we were seeing in previous quarters. Where there has been an increase is kind of low end, shopping, whether that could be fashion and otherwise electronics, some verticals around kind of groceries, food deliveries, those have been seeing a more marked increase.

Got it. That makes sense. And then I guess, a different way of asking the macro question, I think, specific to your business, I mean, oftentimes, we ask about trends in consumer spending. But I guess there's also the question of trends in fraud. I think most payments companies, over the long time are focused on reducing that. What has been the kind of the broad trend over the last couple of years in just the prevalence or the number of attack factors in the fraud space?

Okay. I think fraud is adaptive and it shifts and it never really goes away. And for us, that's great because it's this type of game of cat and mouse. It's not something that's ever going to "solvable." And there are always new vectors now with the rise of like ChatGPT. There's a marked increase in chatbot fraud, where in the fraudsters are leveraging some of these tech's capabilities and forcing or kind of canning agents into giving them credentials to log into accounts, right? So that's a new attack. And every few weeks and months, we see these new patterns of attacks. For us because of our kind of focused dedication, network effect, engineering capabilities, it's easier to detect and to stop that to merchants and not continue to try and manage this complexity internally, it continues to be an increasing challenge. So we think that the increased sophistication of fraud and Fraud as a Service are overall positive for us long term.

Yes. That makes sense. So I wanted to talk through distribution. The eCommerce marketplace has been -- become increasingly concentrated over time into larger platforms. How has that impacted your go-to-market? And then how do you think about partnerships more broadly in the e-com ecosystem?

I think we've done a good job of really focusing on enterprise eCommerce companies, even the marketplaces there, and kind of enjoying their growth as we scale with them, one of the food delivery companies we work with. They're expanding into a lot of categories, offering this as a white label service for some other merchants who don't want to build this capability in-house. So in that sense, I think we're well positioned to grow with these larger platforms. Specifically around the SMB market, which is probably kind of 20% of -- as we define SMB, I'm sure everyone defines it slightly differently, the eCommerce marketplace. I think that's where we want to have much more of a partner-first approach versus kind of a direct sales motion. And that's probably something that I would say, in the next 18 months or so.

Yes. Makes sense. So on -- maybe you can talk through just pipelines and customer acquisition. What have been the recent trends there? How pipeline is trended? And when we think about sort of the catalyst for a merchant to look for an outsourced fraud solution, what are kind of the top 2 or 3 swing factors there?

So look, let me start from the end, right? I think we kind of shared, hey, this year, it's going to be the best performing contribution-wise of new logo. So pipeline has been healthy to support that and feel good about that. And the reason it's been, I think, so healthy is the combination of more global reach, right? We talked about the newer regions, maybe we'll mention Japan, Brazil, APAC, Lat Am that have been ramping nicely. And we've also been able to land some of the product platform as new sales from day 1, which has also been helpful in kind of contributing to that growth there.

Yes. And then when you think about -- once you have a customer that land and expand motion, what does that conversation with the customer look like to get a greater share of their volumes?

I think it's about building a trusted relationship and being able to showcase, hey, we promised you a 97% approval rate and 20 basis point fee. And look, you're actually receiving a 1% higher approval rate than we promised you and fraud and chargebacks are under control. You know what, we noticed that you have these other segments and your cost profile is 25 bps there. We think we can manage it for 20 bps and incrementally increase your sales as well, right? So once you've proven performance and show that, it becomes an easier process to gain more and more...

Yes. That makes sense. And then pipeline this year, you mentioned this being one of the biggest years in terms of contribution of new logos. Just how do you see -- what is sort of the visibility you have into kind of pipelines and deployments as we start thinking into next year?

I think we always have this rolling cadence -- and I'm sure this is similar to almost all companies, especially enterprise eCommerce for the next 1 to 2 quarters. You already have kind of the people integrating definitely for the next quarter, probably mid- to large-size companies can always happen in a 2-quarter cadence. 3 to 4 quarters out is probably the pipeline that we're building right now. So I think that's the overall trajectory.

Got it. Makes sense. You've had some kind of one-off fraud events over time. And I'm sure there are also a bunch of events that we never hear about that you catch quickly and nip in the buds. What are the conversations like with your customers in real time as those events happen?

That's true. By the way, one of the fun things about running risk of it is on top of all the regular public company metrics, we also have fraud events in CTB and everything else to manage internally. So it keeps us on our toes. Look, I think that what we try to do is to provide the merchant a sense of control, okay? The merchant from our perspective needs to feel that they're managing the business and are making these decisions. You don't want them to imagine that there's this black box that is saying that, hey, something is happening and now approval rates are going down. So it's a lot around communication, showcasing it through the tools and visualizations, working with the merchant, their leadership and security teams to understand the fraud of what is happening, mapping out the options in order to stop this fraud event. And kind of collaborating on a solution, right, where there's broad alignment around the room, what needs to be done right now in order to stop this.

Yes. I guess how do you balance -- in an event like that, how do you balance kind of the need to act quickly versus the need to also communicate, stay in front of the customer and kind of make sure that they're involved in the decision-making?

They're aligned. Again, if there's a massive fraud event, it's in everyone's best interest to make sure that the fraud is stopped, so it doesn't propagate and become an even bigger issue. And if there's an issue with kind of leak credentials or accounts being taken over. It's in the customer's best interest as well to understand this and stop it. And they're seeing it from a lot of different vectors. So we always feel that there's a lot of great collaboration with the clients at that point, right? They understand the problem. They want to solve it. So we haven't had -- have too many hard discussions around what levers to push.

Yes. I mean do these end up being kind of catalyst for better conversations, productive conversations on the back end around doing more, expanding the relationship?

That's a great point. It's probably a bit -- those are usually the best conversations to expanding the scope and saying, "Hey, this is where the fraud vector happened. This is why it was unprotected." Because of account security issues, because of data issues, because of integrity issues, because of a segment that we're not looking at right now that potentially enable the front to come in. So yes, it's a good point.

Got it. So how about competitive dynamics. And you've -- so you have stand-alone players like Riskified. You've got merchant acquirers, there's some risk scoring models that are less on the guarantee side. So -- where do you most often run into competitors? And when you don't win a competitive deal, what's the most common reason for why that is?

Look, let me answer this way. We've shared that over the past few quarters, competitive win rates have been in the range of kind of 80% to above 60%, right, depending on the quarter. So when we sit around the room as a management team or as a board, obviously, every competitive deal, we want to make sure that we win and get it up to 100%, but we feel that the biggest focus we need to have is how do we make sure that we generate more deals and more pipeline, right, in a way that also diversifies the client base that we have right now so that we're less impacted by macro in kind of -- in future cycles and don't have that type of headwind. And that's really the focus for us, right? Having said that, when we do lose, it could be related to, hey, I'm not sold on this guarantee model. I want to continue managing my own kind of [indiscernible] in team. And I'm afraid of letting go of some of the decisioning capabilities that's probably the #1 reason.

Got it. That makes sense. And then just -- how do you think about the dynamics between sort of acquire led models versus the stand-alone models? And are there multiple types of models out there?

I think that what we've seen so far is that in our segment of the enterprise, people are not looking for, hey, let me take a simple package solution from one provider. They tend to run multiple gateways, so they need something that's usually gateway agnostic and they tend to choose deep best-of-breed solutions and test them out, right? And that's what the category we put ourselves in.

Got it. So switching gears to international. I think in '22, you added a lot of go-to-market resources. I think you referenced this earlier to establish some beachheads in new markets. How are you feeling about the international growth runway today?

And look, some of the fastest growth that we've had over the past few quarters has come from those regions, whether it's kind of that 30%, 40% in APAC and Lat Am prior few quarters. So we definitely are seeing kind of positive contribution there. I think we highlighted a very meaningful to us win in Japan to open up that market. And we think it's a market that really references are probably more important than others there. So we're very excited about that. I think we're seeing good progress there.

I mean one thing that we talk about a lot in payments is just sort of the increasing kind of commoditization of the U.S. payments market relative to international, which remains super complex. I'm wondering if that kind of benefits your business internationally. Like do you see bigger problems to solve for customers in international markets just because of the inherent complexity?

It's an interesting question. I haven't thought about it like that. I think from our perspective, our platform and decisioning, we're already actually operating in a lot of these regions from a [ RIC's ] perspective, right? So we work with very large merchants and even if they're headquartered in the U.S. or in Europe, they have business in Japan, they have business in China, they have business in Brazil. So our decisioning science is already set up to -- for the nuances of some of these local markets. It's true that everyone has a slightly different competitive makeup -- or kind of go-to-market strategy maybe is the way to phrase it.

Got it. Okay. And then on new verticals, I think ticketing and live events, I think, has been particularly notable. I think this has been one of the newer verticals that's been added since the IPO. It was a big success story, and I think is now roughly 1/3 of the business today. So can you kind of talk about how you got into that space? And then a story of how it became so large in such a short period of time?

Sure. So I think success helps drive future success for us in some of these categories, right? I think kind of a standard story would be we added a mid-tier merchant in that space, had an opportunity to prove the value with one of the largest merchants in that space. And as we added that merchant, we focused in and said, "Hey, how do we make sure that we're the best breed best-in-class solution for kind of the ticketing industry?" And for us, that means slightly customized modeling with slightly customized features. So for example, we developed an algorithm, these marketplaces, they're selling a lot of different tickets. They're selling NFL tickets, NBA, Broadway shows. So we developed something fairly complex that could take the text of the ticket. Based on that, do an analysis of what type of event it is? Is it a Broadway show? Is it an NFL ticket? Is it a preseason game? Is it the Super Bowl? And based on the category, assess a risk score, that's something that's like hard to do, okay? It means that you have better models for everyone in this category and industry. And potentially, we can use kind of a similar solution in like the fashion industry and kind of distinguish between Gucci and Uniqlo -- if anyone is selling both of those products. But I think that was the approach, right? So you have some initial traction. You make sure the product is able to provide a superior performance for that industry. With that, it's easier to go to all the other merchants in that category and have more success there. So I think that's what we saw in the ticketing industry and hopefully, that's something we're -- and that's obviously something we're trying to replicate in some of the newer categories that we're trying to expand our presence in, whether it's organic groceries or food delivery or also from an international perspective.

Yes. That makes sense. And so I guess, how does that work from the boots on the ground perspective? Is Salesforce verticalized? And how do you think about opportunities for new vertical expansion, such as the grocery and food delivery space?

Salesforce is really built based on tiers we have kind of our strategic sellers that are selling to clients with over $3 billion in GMV sales and then it kind of works down from there, right? So really based on [indiscernible] You do have some global practices. Airlines is a great example. They're just so unique in how they operate it and how the payments and fraud systems are set up that it makes sense to have it on a globalized nature. And we through the compensation plans is where we try to drive kind of the strategic behavior of, hey, we want to make sure that we're getting more new products sold because we have a better margin profile, and we think it's going to help the platform longer term. We want to make sure that we get those first few deals in some of these newer categories that might be a bit more challenging because you don't have that kind of massive testimonial background, but that's going to lead for the future successes there. So that's how we approach it from a go-to-market perspective.

And I guess I'm always surprised at just the number of different variations that sort of the -- like the risk profile of your customer relationships can take. And so whether that's risky versus less risky volume. I'm curious how that differs across verticals and just how do you see kind of risk profiles and financial profiles of the different verticals?

I think one of the most important things we do is we have risk-adjusted pricing, right? So to your point, we can work with a -- we mentioned the home category in the U.S., someone selling furniture domestically, not super high risk, okay? And at the same breadth, we can work with someone selling digital gift cards globally, okay? This is like cash on a credit card, extremely high risk. The commonality between them is we can outperform the internal team and system, right? So one merchant might have a 98% approval rate with a 15 basis point chargeback rate, but we can do that for 10 basis points with 0.5% higher. The gift card merchant would have a 70 basis point chargeback rate with a 85% approval rate. So you have these very large variances. But for us, really, what's important is to be able to outperform the internal kind of metrics and KPIs in those cases.

Yes. That makes sense. You referenced new products several times today. You've been expanding into new and adjacent products. And I think chargeback guarantee, I think as you mentioned, it's still the bulk of the business today. How would you frame the opportunity and kind of additional services? And what's the trend been in kind of attaching these to kind of existing and new deals?

So policy product, our Policy Protect product, which helps merchants both manage their -- it helps them reduce abuse from non-fraud chargeback. So for example, I can call a merchant and say, "Hey, I never received my package and I want a refund." And they would provide me a refund. But I actually did, right? I mean I just figured out that I don't need to steal a credit card, I can just do that. So that's a form of abuse that our Policy product solves, which is not credit card fraud, but is using similar technology. Our Policy product also helps merchants provide different experiences to some of their end consumers. So one way that our client uses it is they configure our system to set it up so that the top 10% of international shoppers receive free shipping and free returns, but the others don't, right? So this isn't really abuse. It's more leveraging our kind of network and technology and understanding lifetime value to set up a different experience for their consumers to optimize their internal kind of margins. Another use case for policy is, for example, they might want to create a first-time customer, 10% discount code. But then you have these returning customers abusing that code, creating fake e-mails. So that policy product has been going well, and I'm a big believer in that. And I think we're seeing in the zone of 10% to 20% of the revenue of the chargeback deal when you're talking about kind of same merchant, and that's incrementally higher on the gross margin because that doesn't have a chargeback component to it. So that's the policy product. And I think that's applicable to -- I don't want to say all, but most of our merchants, different forms of policy abuse, whether it's a digital merchant, a physical goods merchant, the dispute management, which is us helping take the chargebacks in and work with the banks to resolve them in favor of our merchants in an automated way with high win rates, that's probably sub-10% incremental revenue increase. It's a lot around automation and workflow, but also seeing good traction there. Overall, they've been growing around 3x year-over-year. But like we mentioned, still kind of on the smaller side, about 0.5% incremental uplift to kind of our gross margin. And feel good about kind of the pipeline and what's ahead from them, both from a product and traction perspective. And I think if we can able to maintain some of these growth rates, they'll become meaningful pretty soon.

And I guess, have you seen these be the tipping point and sort of competitive deals where this is kind of one main point of differentiation versus your competitors?

I think Policy has some wow factor for merchants. It's really a complex system that combines a lot of our machine learning and network and the ability for the merchant to configure their own policies and manage it on an ongoing basis. So we definitely see excitement around that. And when we kind of referenced how we feel our kind of a relatively high win rate, I'm sure that's a component of it.

Yes. That makes sense. All right. So I'm not the guy to ask a bunch of questions on AI, but I think you're perhaps the most AI-focused name in my coverage. And it's interesting as the investor conversation around AI has shifted to be more focused on return on AI as opposed to just how much you spend on it. I think you have some of the most quantifiable returns on investment when talking to customers. So can you just talk about just the AI that powers your model? How the customer conversations have been impacted by this explosion in the use of AI?

So you're right. We're an AI company. We're an AI company. When we started in 2013, we said like the original pitch deck of Riskified and it was machine learning back then is like we believe that we can leverage machine learning to do smarter fraud detection for e-commerce merchants. The type of machine learning or AI that we did is called the supervised machine learning. We've actually spent the first few years of the Riskified looking at high-risk transactions that other systems were declining, and merchants would submit them to us and say, "Hey, you know what, Riskified, if you can guarantee this transaction, that's great, i.e., my existing team and system thinks it's a fraudulent transaction." We would look at a lot of data and features and say, "Oh, you know what, I found a way to explain why is it super risky. It's actually an okay transaction and approve it." We've actually had an incredibly powerful feedback loop in the form of chargeback, right? If a chargeback comes in, you've made a mistake, so you can tag that to the system, we're wrong. If it doesn't come in, you know that you are right. So that's really important over time. It's created a very, very powerful effect for us. And that type of supervised learning where we own the taggings is what we train our models on, right? So that's very proprietary. And when we talk about the models that we train, I think I gave you the example in the ticketing space, it's stuff that we engineer, we build, right? We look at a transaction and we say, how do we as human, as people, as analysts understand that this is a good or bad transaction. And someone says, "Well, I know it's a Super Bowl ticket or I know that it's higher risk than a Broadway show." And we say, "Okay." So how do we help the machine understand that? And that's when we build that feature that encapsulates that information that's fed into the machine learning model and we have hundreds of those, right, that we've built and engineered and we deploy different features on different models. So that's all been incredibly meaningful and significant part of our stack. And we've invested in 10 years ago and we continue to invest in it today. And the value that we get is in the superior performance for our merchants, right? The better performance for our merchants, the more sticky we are, the more challenging it is to move away from us or go to a competitor. And also what we see is that the better we get, we also take some of that increased value and gain to improve our margins. So we released kind of this annual chart. That shows even if CTB starts slightly higher at different cohort levels, over time, it improves, right? And we see improvements in existing cohorts sometimes offset by going into newer geographies or newer categories where we have slightly less experience.

Yes. Makes sense. And I guess from a customer conversation perspective, have there been instances where customers say, "I need to have a AI strategy that makes sense." Have you -- has there been kind of an easier sales cycle or just increase kind of intent when you're talking to customers about kind of pulling the trigger?

Maybe people are just more aware of AI. So I don't know, maybe relative to 3 years ago when you were talking about it, and they would close over and now it's like a bit more interest and hype and going internally and trying to sell solutions saying, no, we don't have a real AI solution. Now this is an AI solution. It's probably gaining a bit more. It's helping in that sense, I would say.

Yes. Yes, that makes sense. I wanted to hit on just the gross margin model performance you're touching on it just a second ago. I think today, I think a little less than half of the revenue goes towards covering the cost of the fraud guarantee and chargeback. You've seen some improvement since the IPO even in the form of higher gross margins. But how do you think about the potential for further enhancements and kind of where gross margins can go over time?

I think we'll see an incremental step-up in gross margins like we have been over the past few quarters, and I think that's going to be fueled by a combination of improvements to the core machine learning algorithm, somewhat offset by the addition of new clients and whatnot. But also as we continue to grow some of the newer products that have a better gross margin profile inherently, that's going to help improve things as well.

Yes. That makes sense. I think you had some pretty significant step-ups in margin over the past year or so. Can you talk about kind of what drove that maybe as a case study and how you were able to kind of identify these improvements?

I mean, broadly, it's the exact same categories that we said, right? The combination of the newer products, which we sized that kind of 0.5% from that overall improvement and the other from the core machine learning. When you're saying from that core machine learning, it's a lot of things, right? It's like we have -- we do dozens of activities throughout a year that would help -- incrementally help. And one example I gave you is around feature engineering and that feature that helps the ticketing industry. That also helps approval rates, but also helps our margins in that industry. We've done a lot of work on automating the build and deployment of kind of customized machine learning models. One of the unique things about Riskified, we don't work with hundreds of thousands of SMBs and then we just need to have a generalized model for an industry. We actually really can tailor a model for our enterprise clients. So that's something that's hard to do at a scale. We work with over 50 publicly traded companies. And you want to have a model deployment every few months to quarters to take into account new data changes in the population, things like that to run in a continuously optimized way. So we've actually built a very complex and great platform to automate a lot of that process. And if it used to take 2 to 3 data scientists would take them 1 to 2 weeks to train and deploy this new model, it's now -- someone is supervising the process, but it's basically with the click of a button. So I think all those different things and again, a lot of things that we do across our tech stack, we focus a lot on. Data science is probably one of the largest teams that we have in Riskified, always has been. So those are the type of things that we do in order to help facilitate both better performance for our clients and a better margin profile for us.

Got it. Yes. So I think you mentioned after the IPO, you made a big investment in go-to-market. Since then, I think costs have actually been sort of flat to down over time. There's been a big focus on expanding margins. You've put out some targets for 2026. The company became free cash flow positive and you're kind of trending in the right direction on margins. So can you talk about how it's been kind of maintaining that flat cost structure internally? And just how do you think about the sustainability? And how you kind of continue on that path over the next couple of years?

Look, it hasn't been as easy, but we're disciplined, okay? I think that we're saying in various macro environments, we're going to drive to meaningful EBITDA improvements. That's been our story for the past 18 months, and I'm really proud of the progress that we've made. I think in '22, I think it was above 1,000 basis points improvement on kind of the bottom line. I think last year, slightly over 900 basis points or so, so really meaningful improvements there. And it's a combination of that cost discipline, together with better margins, to have obviously some good top line growth or kind of mid-teens top line growth over the previous 2 years. So that is a focus for us looking at it holistically and making sure that we're improving bottom line. I think that's slightly broader. We're trying to learn what's happening over in this current macro cycle and saying, hey, how do we position ourselves as a better company as we come out of this cycle, right? Whether it's with a more diversified and broader customer base across more geographies with a more diversified product platform that has more touch points and kind of more revenue from different features than that. And I'm just really proud of what we've done there, and I think we've created a lot of leverage in the business to be able to be able to continue to scale and grow. And hopefully, and I believe that at some point, the things that are now a headwind would also become a tailwind and the growth will become also more meaningful, but the bottom line improvements will continue to outpace that significantly.

Yes. That makes sense. So we've got about a minute left. Just maybe we can end on capital return. So the business is now generating positive free cash flow. How much cash do you kind of need to run and invest in that -- in the business? And then how do you think about capital allocation going forward?

I mean, look, we're a profitable company that's generating cash flow. There's no -- we have so and so capital requirements. Obviously, we would want to feel comfortable with some amount in the bank. But looking at kind of our current enterprise value, which I think for the past few weeks has been somewhere between 2 to 3x kind of gross profit. We think that the best use of proceeds is to continue to buy back our shares and decrease the overall amount outstanding and available as probably the largest shareholder. That's definitely something I believe in. We are interested in looking for interesting technologies that we can kind of further cross-sell to our great blue-chip brains that have a great relationship with us. And I think that's the overall strategy.

Got it. Makes sense. I think we're just about out of time. So thanks for joining me today. Really great to have you here. Hope we have back next year.