Good morning. Thank you for joining EXL's Q1 2024 Financial Results Conference Call. On the call with me today are Rohit Kapoor, Chairman and Chief Executive Officer, and Maurizio Nicolelli, Chief Financial Officer. We hope you've had an opportunity to review the Q1 earnings release we issued this morning. We have also posted an earnings release slide deck and investor fact sheet in the investor relations section of our website. As a reminder, some of the matters we'll discuss this morning are forward-looking. Please keep in mind that these forward-looking statements are subject to known and unknown risks and uncertainties that could cause actual results to differ materially from those expressed or implied by such statements. Such risks and uncertainties include, but are not limited to, general economic conditions, those factors set forth in today's press release, discussed in the company's periodic reports, and other documents filed with the SEC from time to time. EXL assumes no obligation to update the information presented on this conference call today. During our call, we may reference certain non-GAAP financial measures, which we believe provide useful information for investors. Reconciliation of these measures to GAAP can be found in our press release, slide deck, and investor fact sheet. With that, I'll turn the call over to Rohit. Thanks, John. Good morning, everyone. Welcome to EXL's Q1 2024 Earnings Call. I'm pleased to be with you this morning, sharing our strong financial results as we've had a solid start to the year. In the Q1, we generated revenue of $436 million, an increase of 9% year-over-year, and we grew Q1 adjusted EPS by 9% to $0.38 per share. Our data and AI-led strategy has generated a sustainable competitive advantage for EXL. The sound execution of this strategy has enabled us to continue our growth momentum. In analytics, we delivered revenue of $191 million for the quarter, up 5% sequentially and year-over-year. I am encouraged by the Q1 performance in our analytics segment, which has been relatively flat for the past three quarters. This is the result of continued strong double-digit growth in healthcare payment services and data management. Our banking analytics business stabilized during the quarter, while marketing analytics remains challenged, as discussed previously. In our digital operations and solutions business during the Q1, we generated revenue of $246 million, with growth of 6% sequentially and 12% year-over-year. This was driven by continued strong double-digit growth in our insurance and emerging business segments. Looking at the overall demand environment, our new and existing clients remain focused on lowering costs, improving efficiencies, and enhancing customer experience and growth. Our data and AI-led strategy, combined with our deep domain expertise, is helping them achieve these goals. We have been able to significantly increase our total addressable market by offering innovative new solutions and expanding into new buying centers. This is reflected in the continued strength of our sales pipeline. As clients increasingly turn to us for end-to-end solutions, we have also grown our average deal size, which is fueling our above-industry revenue growth. Based on our strong performance in the Q1, we have raised the lower end of our full year guidance range for both revenue and EPS. Maurizio will review the details in a few minutes. We recently held our AI in Action virtual customer symposium, where attendees heard from EXL and industry leaders on the future of business models and how they are scaling the use of enterprise data to bridge the gap between strategy and operations to make AI real. The event included live demonstrations of practical applications and use cases of embedding AI across all our business segments. The event was attended by over 2,300 clients, prospects, analysts, advisors, and partners, and feedback has been very positive. A replay of the event is available on our website. Let me share a couple of recent examples of how we are bringing to life all our capabilities at the intersection of data, AI, and domain expertise for our clients to deliver meaningful value. First, we developed a Gen AI-based conversational business intelligence solution for a leading life and annuity insurer. The solution is designed to help them better understand their captive and independent advisors, interests, behaviors, and demographics. This helps them optimize targeting and message development to improve their experience and increase sales and return on marketing investment.... Effectively developing the solution for the client required bringing together our talented team of GenAI experts, data engineers, business subject matter experts, and AI deployment specialists to work as an integrated team. We harnessed large volumes of both external and internal client data assets to build a 360-degree profile of each advisor. We fine-tuned LLMs to generate personalized insights for distinct advisor groups with unique traits. Finally, we developed a conversational interface for an easy and intuitive user experience. This solution is highly scalable and delivers on-demand, real-time, natural language insights across all our clients' sales and marketing functions. By leveraging additional data sets and embedding digital into our clients' marketing and sales processes, we have created significant value by enabling them to double their new business volume. In another example, EXL has become the preferred AI and data partner for a UK-based leading retailer. We accomplished this through the successful implementation of multiple AI-based solutions to transform their online sales operations. For example, we deployed our proprietary GenAI-based Smart Agent Assist solution at scale, which is currently running live across 1,100 customer agents, handling 6 million calls annually in the client's captive operations, as well as those outsourced to EXL. Our solution provides real-time speech-to-text, AI nudges for next best action, customer sentiment and vulnerability detection, and call summary. Early results include a greater than 90% reduction in customer repeat calls, a double-digit agent productivity gain, and vulnerability detection accuracy rates of over 95%. In addition, we have helped our clients reduce returns, streamline orders and refunds, and improve overall customer experience. We also deployed EXL's Buyer Assist solution, which utilizes GenAI and natural language processing to generate insights from disjointed and unstructured data from 40 different sources across the web, social media, online reviews, and catalogs. Our solution is adept in handling data in any form, be it text, images, or videos, and feeds it into our Buyer Assist recommendation engine. By presenting our clients' buyers with customized recommendations, we help them better predict which items to procure based on potential future demand. This has resulted in a 2%-3% increase in sales, a 30%-40% improvement in buyer productivity, and enhanced customer satisfaction. Due to our success with this client, EXL is now their strategic business transformation partner in deploying AI across their enterprise, thereby expanding our TAM and enabling us to continue our growth momentum. These are just a few examples of the proprietary AI-based solutions we have developed and deployed that combine data and AI with our deep industry experience to deliver meaningful business benefits to our clients and their end customers. I am pleased to highlight two key appointments we made recently within our senior leadership team. Vikas Bhalla and Vivek Jetley have each been promoted to President of EXL, in addition to their current roles of Head of Insurance and Head of Analytics, respectively. In their expanded roles, they will take on broader company-wide responsibilities, including being more involved in driving overall corporate performance and executing on our data and AI-led strategy. As we implement our data and AI-led strategy, it is important that we continually optimize our leadership structure to execute on our strategic objectives. Vikas and Vivek are highly talented and strategic leaders who have built strong, sustainable growth businesses and have created tremendous impact for EXL over the past two decades. In their expanded roles, I look forward to their continued leadership as we transform EXL to the data and AI partner of choice for our clients. We will be holding an investor strategy update event next Tuesday, May seventh, to provide an in-depth overview of our strategy, our pivot to being a data and AI-led company, and our growth opportunities. Registration for the event is available on the investor relations page of our website, and we look forward to seeing you there. In summary, we delivered strong results in the Q1, and we are encouraged by the continued momentum in our digital operations business, as well as the growth in our analytics business. Our winning data and AI-led strategy, combined with consistent execution by our exceptionally talented and dedicated team, position us well to deliver industry-leading performance for the remainder of 2024 and beyond. With that, I'll turn the call over to Maurizio to cover our financial performance in detail. Thank you, Rohit, and thanks everyone for joining us this morning. I will provide insights into our financial performance for the Q1, followed by our revised outlook for 2024. We delivered a solid Q1 with revenue of $436.5 million, up 9% year-over-year on a reported basis, 8.8% in constant currency, and 5.4% sequentially. Adjusted EPS was $0.38, a year-over-year increase of 8.9%. All revenue growth percentages, percentages mentioned hereafter are on a constant currency basis. Revenue from our digital operations and solutions businesses, as defined by three reportable segments, excluding analytics, was $245.8 million, representing year-over-year growth of 12.3%. Sequentially, we grew revenue 5.9%. In the insurance segment, we generated revenue of $145.1 million, an increase of 15.6% year-over-year and 4.4% sequentially. This growth was driven by the expansion of existing client relationships and new client wins. The insurance vertical, consisting of both our digital operations and solutions and analytics businesses, grew 12.1% year-over-year, with revenue of $183.1 million. In the emerging segment, we reported revenue of $74.4 million, growing 11.9% year-over-year and 10.7% sequentially. This growth was driven by new client wins and expansion of existing client relationships. The emerging vertical, consisting of both our digital operations and solutions and analytics businesses, grew 0.4% year-over-year, with revenue of $155.6 million. The healthcare segment reported revenue of $26.3 million, down 1.7% year-over-year, and an increase of 1.1% sequentially. The year-over-year decrease was primarily due to one-time revenue in the Q1 of 2023. The healthcare vertical, consisting of our digital operations and solutions and analytics businesses, grew 18.1% year-over-year, with revenue of $97.8 million. In the analytics segment, we generated revenue of $190.7 million, up 4.6% year-over-year and 4.7% sequentially. Growth in analytics was driven by higher volumes in healthcare payment services and growth in our data management business. This was partially offset by a decline in marketing analytics, reflecting an ongoing trend we have highlighted in previous quarters. SG&A expenses as a percentage of revenue were up 140 basis points year-over-year to 20.4%, driven by investments in generative AI, digital solutions, and front-end sales, partially offset by operating leverage. Our adjusted operating margin for the quarter was 18.9%, down 50 basis points year-over-year, driven by increased SG&A investments. Our effective tax rate for the quarter was 23.2%, down 80 basis points from 24% in the Q1 of 2023. This was driven by higher profits in the lower tax jurisdictions. Our adjusted EPS for the quarter was $0.38, up 8.9% year-over-year on a reported basis. Our balance sheet remains strong. Our cash, including short- and long-term investments, as of March 31, was $246 million, and our revolver debt was $345 million, for a net debt position of $99 million. Our Q1 cash flow from operations was an outflow of $21.9 million, compared to an inflow of $16 million in the Q1 of 2023. This is due to higher working capital requirements and one-time earn-out payments related to a prior acquisition. During the quarter, we spent $11.3 million on capital expenditures and repurchased approximately 4 million shares at an average share price of $30, for a total of $119.4 million. This includes 3.35 million shares received upfront as part of our previously announced $125 million accelerated share repurchase plan. We expect to receive the remaining shares in the Q3. Now, moving on to our outlook for 2024. ... Although the macroeconomic environment remains unpredictable, we are raising the bottom end of our guidance ranges for both revenue and EPS based on our strong Q1 results. We now anticipate revenue to be in the range of $1.79 billion-$1.82 billion, representing year-over-year growth of 10%-12% on a reported and constant currency basis. This represents an increase of $5 million at the midpoint and $10 million at the low end of our previous guidance of $1.78 billion-$1.82 billion. We expect a foreign exchange gain of approximately $1 million, net interest expense of approximately $4 million-$5 million, and our full year effective tax rate to be in the range of 23%-24%. We anticipate our adjusted EPS to be in the range of $1.58-$1.62, representing year-over-year growth of 10%-13%. We expect capital expenditures to be in the range of $50 million-$55 million. In summary, we started the year strong and are encouraged by the continued double-digit growth momentum in our digital operations business and the growth in our analytics business. By effectively executing our data and AI-led strategy, including the significant investments we are making to further grow our competitive advantage, we are confident in our ability to maintain our double-digit growth trajectory. With that, Rohit and I will now be happy to take your questions. Thank you. As a reminder to ask a question, please press star one one on your telephone and wait for your name to be announced. To withdraw your question, please press star one one again. Please stand by while we compile the Q&A roster. One moment for our first question. Our first question comes from Bryan Bergin from TD Cowen. Your line is now open. Hi, good morning. Thank you, and congrats to Vivek and Vikas. I want to start on analytics that performed a bit better than expected here sequentially. Can you comment on how you now see analytics growth progressing over the balance of the year? I heard the comment on banking stabilization, which is good. Can you just dig in a little bit more there on what you're seeing? And then customer marketing analytics, just to be clear, is it bouncing along the bottom, or are clients kind of still trimming? Sure, Brian. So first of all, we're very pleased with the progression of our analytics business, and this is the Q1 where we are seeing sequential growth take place quarter on quarter after three years of flattish revenue for the analytics segment. Three quarters. Two quarters? 3 quarters. You said 3 quarters, yeah. Yeah, three quarters. The analytics business, as you know, for us, is made up of different buckets. We've got analytics services, we've got a data management capability, and we've got marketing analytics as part of the portfolio. The data management part of our portfolio is very strong and continues to grow very nicely, and we feel we are well positioned to take advantage of the secular trends that are taking place out there, and particularly with the adoption of Gen AI, the demand for data management has only increased, and we feel that we are well positioned to participate in this growth. We are very happy that the analytics services part of our portfolio has now stabilized and recovered nicely. This was being impacted by banking analytics services, where discretionary spend was being cut back and spend on analytics services was being cut back. That seems to have now stabilized, and we would expect this to continue to move up as we go forward. Marketing analytics for us continues to remain challenged, and it continues to decline in revenue, and it is actually a headwind for us at this point of time. We do expect that this will stabilize and that this will be something that will bottom out, but at this point of time, it continues to decline, and it continues to be a drag for our business. If you take a look at the overall analytics business, our expectation is in calendar year 2024, we would expect to see sequential growth take place in the absolute dollar value of our analytics revenue quarter on quarter. What that would also imply is that our growth rate year-on-year is likely to continue to improve from Q1, which was at 5%, and we would expect this to continue to improve sequentially, quarter-on-quarter, as well as year-on-year for 2024. I hope that's helpful for your question. Yes, very good. Okay, and follow up here on near-term workforce resourcing plans. Obviously, a recent media report drove some share price volatility, so just wanted to give you a chance to clarify anything around that. Understanding your net headcount was up in the quarter here, but do you still have bench to optimize any areas of talent you're de-emphasizing versus areas you're leaning in? Sure. So, you know, the workforce rationalization and optimization for us, firstly, is a very, very small piece of our overall employee headcount, and it represents less than 2% of our overall headcount. As you've rightly pointed out, we've been growing our headcount quarter-over-quarter as well as year-over-year. If you just compare where we ended up at the end of Q1 in 2024 versus end of Q1 in 2023, there's been a net addition of 7,000 employees at EXL, and that's consistent with the growth that we are experiencing and our ability to continue to add on talent. We would expect in 2024 we would continue to add employees on a net basis to the company as we continue to build and grow our revenues by 10%-12% in calendar year 2024 over 2023. So this, workforce rationalization that was done, was predominantly done because of a skill set mismatch, and this is something which we had to undertake, as a one-time action. This is obviously something which we are very careful about, but with the volatility of, how the demand is, shaping up and what kind of skill sets are needed, we needed to optimize it, and this is part of our prudent management, of our business. And I think, this is, something which, you know, we'll take it in our stride, and we'll continue to build up, what we've got. The important thing is, the revenue for us continues to scale up, and as our revenue scales up, we're gonna need more and more people to do that work, and so we'll be adding staff as we go along. Very clear. Thank you. Thank you. One moment for our next question. Our next question comes from Ryan Potter from Citi. Your line is now open. Hey, thanks for taking my question, and congrats on the good quarter. It was nice to see the strong start to the year on a sequential basis across both segments. And I know last quarter you called out sequential growth rates improving through the year, but with the unchanged top end of the outlook, it appears to assume some sequential growth rates stepping down from Q1 levels. So first, I wanted to be clear, was there anything one-time or, or timing-related that drove some of the Q1 outperformance? And then is there anything to call out on why sequential performance may decelerate going forward, or is it just being cautious around macro-related assumptions? Hi, Ryan. It's Maurizio, and thanks for the question. It's when you look at the quarter, we did outperform during the quarter based on the street consensus, and we did take a look at our guidance. Now, in looking at our guidance, we did increase the bottom end of our guidance because we think that where we were was a very low probability of that occurring this year. And also implied in doing that, the midpoint of our guidance also comes up in overall. Given that it's still early in the year, we've only completed one quarter of the year, and we have the rest of the year still to perform, and there's still a bit of uncertainty in the overall marketplace, even though we are very confident on 10%-12% growth going forward, we thought it was prudent right now to remain our high end at where it is. So our bottom end comes up from where we were. Our midpoint of the range also comes up from where we were. But right now, given we're only one quarter into the year, we felt it was prudent to keep our top end of the range where it was when we gave guidance in February. So Ryan, let me add a couple of things to this. Number one, there is nothing as one-time revenue in the Q1. This is part of our normal progression of our business, and we're very happy to see both digital operations and analytics start to grow and kind of perform well. Number two, on a quarterly basis, we would expect year-on-year growth rate to continue to improve as we go forward in 2024. Obviously, quarter-on-quarter growth rate in Q1 was exceptionally high over Q4 of 2023, but we still expect to see quarter-on-quarter growth in absolute dollar terms in 2024, though the percentage growth rate quarter-on-quarter is gonna be lower than the 5% that we experienced in Q1. So I hope that's helpful to you to understand how we're seeing our business. Yeah, that's helpful. I guess kind of shifting to the digital ops business, where our performance there has been very impressive, and you've consistently outperformed peers and even seemed to outperform some of your expectations. So I guess, what would you attribute some of the largest drivers of this outperformance to be? Do you think it's more reflective of the more cost-focused demand environment, or do you believe you're gaining momentum and taking share in the marketplace here? Sure. I think it's because of a couple of different fundamental factors that are driving the growth, and we are very pleased with our digital operations and solutions business growing at 12% in this quarter, year-over-year. And you know, for the past several quarters, continuing to grow at these you know elevated levels. First and foremost is our ability to integrate in digital with operations and analytics with operations. That creates ability for us to win much more you know in terms of the pipeline and drive the growth rate of this business a lot faster. The second part of this is we are winning larger deals-... And the average deal size has increased for us, because clients now expect us to create business impact across a larger part of their portfolio and to handle the business for them end-to-end. And the third part of this is, because we come at it from a lens of applying domain, data, and AI, our ability to go into new buying centers within the same clients and with new prospective clients is a lot better. So frankly, the integration of digital and analytics with operations, where we believe we are very strongly positioned and uniquely positioned, the larger deal size, and the ability to go into new buying centers, is allowing us to grow the digital operations and solutions business at a faster rate. And this is basically our business model resonating very strongly with our clients and for us to stand out in the marketplace. Great. Understood. Thanks again. Thank you. One moment for our next question. Our next question comes from Maggie Nolan, from William Blair. Your line is now open. Thanks. Maybe just, piggybacking off of that conversation around digital ops, can you talk about recent volume and pricing trends in the digital ops business? And any kind of recent or updated thoughts on the health of key client accounts in that business? Sure, Maggie. So first of all, we are very fortunate that the portfolio that we have in our business in digital operations is in very steady and stable industry sectors. So for us, our insurance, our emerging, and our healthcare, you know, business verticals, these are stable and growth-oriented verticals, and so we're not really seeing any change in volume in these verticals. We're seeing continued traction take place in terms of the growth and the volume, you know, in these verticals. As far as pricing is concerned, that is something that we are seeing some of our competitors work on trying to use price as a lever. But our focus with our clients is always been about how can we deliver exceptional value to them, and then be able to charge them appropriately for that. So our existing clients know the execution and the value delivery that we have demonstrated to them, so they continue to give us more volume of business. But there are times with new customers where we do get challenged on pricing because some of our competitors are resorting to a lower pricing, given their lower growth rates. And that's something where we have to stand out and differentiate and be able to demonstrate our capabilities on digital, on analytics, and the ability to create overall better value for the client. Got it. Thank you. And then on the full year guidance, you know, I heard the commentary that you expect the sequential growth, and that's great to hear. I'm wondering what part of the business would provide the upside to get you to the high end of the guidance? Is it a recovery in the marketing analytics? Is it, you know, additional wins in digital ops, a combination? How do you get there, and what are some of the assumptions baked into the higher end of that guidance range? Sure. As you know, you know, digital operations for us represents 55% of our business, and it's a very stable and a very steady growth-oriented business for us. And any new wins that we have out there tend to have a revenue impact in outer quarters and outer years. So there isn't very much that we would expect, you know, in our digital operations business momentum to change. The big change could happen in our analytics business and certainly with some of the engagements that we've started to undertake with our clients around Gen AI. I think those are the two opportunity areas for us to be able to try and get to the top end of the range, you know, for the guidance that we've provided. Thank you very much. Thank you. One moment for our next question. Our next question comes from Surinder Thind from Jefferies LLC. Your line is now open. Thank you. In terms of just, looking at some of the Gen AI implementations or, or the potential types of projects that you're working on, obviously there were some good demonstrations on the AI webinar day. Can you talk about, for example, like in the customer service area or others where I think there's been some concerns around headcount reductions, how is that model evolving from like... What kind of productivity are you guys able to provide at this point? Or do you have any benchmarking or data, how we should think about the value that a client is receiving at this point? Sure, Surinder. So, look, I think, Gen AI and the application of digital is certainly, you know, allowing our clients to be able to have greater cost efficiency, but at the same time, have a much better end customer experience, and to be able to target this towards generating growth. What we are finding is because our penetration and our share of wallet within each of the, our clients is still relatively low, it's, you know, less than 15%-20%. Anytime we are able to deploy GenAI for our clients' benefit, we actually gain overall volume, and we gain in terms of revenue with that same client, even though we are providing them with greater efficiency, and we are providing them with a greater ability to create impact. In the example that I shared in my prepared remarks, that's a classic example where we've had an amazing experience with our clients, and we've been able to deploy a proprietary GenAI-based solution across the enterprise, and impact 1,100, you know, customer service agents and 6 million calls a year. But what's happened is that the customer has given us more work because they want us to deploy this in other areas, in other business lines, and across other providers that they work with, as well as on their own captive operations. So the net impact of that is that our business relationship with our clients becomes a lot more strategic, and it increases in size and value. That's helpful. And then in just, as related to that, as you think about implementing these solutions or more, from the perspective of clients, what are-- how are they getting across or thinking about things like what's an acceptable error rate for an implementation? It seems like, you know, the solutions operate to various extents in terms of the, the quality of the end result here. Obviously, there are some low-risk cases, there are some higher-risk cases. But how do we think about the timeline on some of these types of projects, of going from these proof of concepts to actually the, the live and what they actually mean from a revenue perspective? That's a great question, Surinder. And then that's, you know, I think at the crux of how clients and prospects are thinking about using GenAI. So first and foremost, accuracy of the results is critically important, and second, the adoption of that solution is critically important. And the adoption only takes place if the accuracy levels are high enough that they're providing you with a distinct competitive advantage. Our role is to make sure that we can deliver high-quality service and high accuracy, and at the same time, enable change management so that the adoption of using these tools is a lot better and a lot more sustainable. Now, there is a fair amount of risk sharing that we undertake with our clients and align ourselves to the end outcomes. So there are, there is a fair amount of investment that we are making in terms of having prebuilt, accelerators and prebuilt solutions that we can bring to bear to our clients, and they don't need to invest in that early adoption capability. And then there is a lot of fine-tuning and a model change that we need to do to get to those levels of accuracy. So when we start with a new solution, the accuracy levels are very low. They are like 65%-70%, but we have to drive that up to 90%-95%, and that is driven by a strong understanding of the domain and understanding of how and what the data is telling us, and therefore the fine-tuning of our algorithms and our ability to embed this into the workflow so that it is actually useful for every single person that is adopting these solutions. And that's where we are unique, and that's where we stand out, and you know, that's how we're deploying this. But at the end of the day, our clients are partnering with us to be able to get to those levels of high accuracy and high adoption. Thank you. Thank you. One moment for our next question. Our next question comes from Puneet Jain from JP Morgan. Your line is now open. Hi, thanks for taking my question, and thanks for doing the webinar last week. It was very helpful. Quick question on that, like, are you seeing... Like, it's clear, like, that AI and GenAI is helping drive some of the new conversations, new use cases for EXL, and you are well positioned. But could it also be driving clients to take longer in deciding project awards? Like, because it's new, like, the use cases might be new, like you mentioned, Rohit, just now. The accuracy levels required are also high, so could they be taking longer in deciding those project awards when it's about AI implementation in their processes? Yes, Puneet. I think there is a longer lead time in terms of decision-making by clients because they are looking at a number of proof of concepts, and they are looking at experimenting as to where these technologies are gonna be impactful and where actually the return on investment is not very high. So there is a fair amount of experimentation and doing pilots and proof of concepts that is there. And the decision-making on enterprise-wide, scaled-up deployments of these solutions is definitely taking time. We are in a fortunate position because when we do these proof of concepts for our clients, we're able to very quickly demonstrate our ability to create impact. As soon as our clients see that, and that's very visible and transparent to them, then the deployment of that across the enterprise becomes a much easier decision for them and a much quicker decision for them. So we are, you know, I think, benefiting from an ability to kind of take some of these initial proof of concepts and deploy them across the enterprise. So I would expect in 2024, this is gonna be something that is going to result in active decision-making by our clients and our ability to be able to implement and deploy this for them. Got it. No, that's very helpful. And the prior guidance assumed, I think, that macro will remain unpredictable in the H1 and potential normalization in H2, particularly in analytics. Is that still your assumption? And do you expect marketing analytics to stabilize? When you say that, does that mean it will stabilize on sequential basis from here on? So, there are two parts to your question. One, from a macroeconomic standpoint, our viewpoint is that while the macroeconomic environment seems to be somewhat stabilizing, it continues to remain challenged. And therefore, our assumption is that, the macroeconomic environment and our clients will remain cautious, in terms of how they think about making investments and how they think about, investing in new areas. As far as marketing analytics is concerned, that business for us, is declined and, but it has a seasonality to it. And the seasonality is that, marketing analytics is typically, stronger in the Q1 and in the Q4, and in the second and Q3, it's actually much lower. So we're gonna see that play out, you know, for 2024 as well. But calendar year 2024 over calendar year 2023, it would still be a decline. Got you. Thank you. Thank you. One moment for our next question. Our next question comes from Moshe Katri from Wedbush. Your line is now open. Hey, thanks for taking my call. Good numbers. In your opening remarks, you spoke about sales pipeline strength with the expanding average deal sizes. In that context, can you talk a bit about maybe TCV, ACV, how is that kind of moving? Is there any way to kind of quantify those movements? And then have there been any changes in the pace of sales cycles or pipeline conversion rates? Thanks. Sure. So Maurizio, our sales pipeline continues to remain strong, both across our digital operations and our data analytics business. I think, from a TCV standpoint, we are seeing larger deals come in, so the TCVs are certainly higher. The way we would characterize this is, 70% of our pipeline is made up of large deals. We also, the conversion between a TCV and an ACV, that remains pretty much constant. Typically, our digital operations deals are between 3-5 years in term, and the analytics deals are typically 1-2 years, you know, in term. So that ratio remains, pretty much the same. As far as the win rates are concerned, we've been fortunate that we've been winning, you know, at a healthy rate over the last few quarters, and that's what is giving us an elevated rate of growth in our digital operations business. Clearly, we need to have a lot more in our analytics business because the discretionary spend out there is somewhat curtailed, and that decision-making on discretionary projects is still, you know, suppressed and being held back. So as soon as that kind of comes back to normalcy, we would, you know, see that go up. I think what we are seeing is that the banking and financial services sector seems to have stabilized. So that's a good sign for us because that's a large part of our business, and we would expect that, as that stabilizes and returns back to growth, we would be able to benefit from that. And then just to follow up on the marketing analytics piece, obviously, we're looking for a decline year-over-year this year. Is there a way to kind of quantify that decline in terms of expectations? And then maybe in general, what drives this segment? Maybe talk a bit about, you know, what funds it, how do you, how do clients fund it, and what are kind of the, the reasons to kind of, you know, to contract EXL for these kind of services? Thanks. Sure. So Moshe, we don't quantify, you know, this, you know, service line for us because it's a small service line. But, I think the way to think about this is, our marketing analytics business is largely focused in with insurance carriers trying to acquire new customers and by banks and financial institutions trying to acquire new borrowers. Clearly, with the interest rates going up, the acquisition spend by banks and financial institutions in terms of acquiring new borrowers, that propensity has declined. And with the insurance carriers, given some of the inflationary pressures that were there, their outreach to acquire new customers has also declined, and that's the reason why the marketing analytics business for us has declined sequentially. Now, what we are doing with our marketing analytics business is two fundamental changes. Number one, we are diversifying our customer base. So actually we are broadening out our customer base, and now we have clients from healthcare, we have clients from our emerging business unit, and other clients that are taking advantage of the proprietary data assets that we have in marketing analytics and being able to benefit from that in terms of the next best thing to sell to their customers and their ability to cross-sell. So that diversification is helping. And we are expanding the work that we do in marketing analytics from just customer acquisition to much more of an end-to-end, you know, customer engagement profile. So that's being helpful as well. You know, obviously, it's gonna take us, you know, some time to do this, but the diversification of marketing analytics across industry verticals and customers, as well as the broadening out of that service line in marketing analytics, is gonna help us manage the volatility of this business. Understood. Thanks. And, thank you. One moment for our next question. Our next question comes from Dave Koning from Baird. Your line is now open. Yeah. Hey, guys, thanks. Yeah, great, great results. On health analytics, like if we just take total health, less your health operations, that business line has been remarkably strong and stable. I think I look back for like 8 quarters or so, it's been growing kind of 25%-36% each quarter. What's so consistent about that? I mean, it seems like it's not having any impact from kind of the macro slowdown. Yeah, Dave, thanks for that. As you know, the healthcare industry vertical is actually a huge, vertical. And number two, it's got huge challenges with data. And as you know, payers and providers and participants in the healthcare services business start to embrace a lot more of data and start to embrace a lot more of AI, we are certainly benefiting with that. Our healthcare payment services have been growing very, very nicely, but the reason it is growing very nicely is because our ability to leverage data, to leverage AI, and to leverage digital, alongside with our strong understanding of the payment services process, allows us to be able to deliver superior impact for our clients, and our clients love that, and they're embracing more and more of that. We're also seeing a lot of growth take place in healthcare analytics, and this is a huge opportunity for us to continue to build upon, because leveraging data in healthcare analytics can be very, very impactful for all of the major, you know, participants in this industry space. So we are very pleased with what we have built out here, the kind of impact we are creating, and the kind of traction that we're getting. But I can tell you, our penetration in this vertical is still very small because the healthcare business by itself is a $4 trillion business, you know, vertical. Gotcha. Yeah, no, that's helpful. Then if I might ask just a super nerdy question on the cash flow statement. You mentioned in the prepared remarks about the contingent consideration payment. It was split both between the operations and the financing. I've never seen it in operations before. Maybe I think $11 million was in operations and $4 million of the payment was in financing. Why was that? So we're following acquisition accounting, Dave. That's the recommendation that we have from our auditors that we've worked very closely with. You know, that's where we ended up on. Look, you know, we had an outflow because of that during the quarter, but you know, when you look at free cash flow for the year, we still you know, expect it to be comparable to net income for the year. You know, we had this one blip in the Q1, but we do see the full year free cash flow being comparable to net income. No, that's, that's helpful. We always look at that as a positive. When you're paying out, it usually means the results have been pretty good from those. So nice job. Thank you. And, thank you. One moment for our next question. Our next question comes from David Grossman from Stifel. Your line is now open. Thank you. Good morning. I'm wondering if we could just, you know, go back to some of the more, you know, fundamental things around your commentary on Gen AI. I think I understand what you've been saying about how it's impacting, you know, the demands from your customer base and some of the use cases. Perhaps you can spend just a few minutes on what you see as being the secular impact it may have on your business model. You know, I'm thinking contracting, risk, margins, and just how the business is operated overall and how that flows through the P&L and the balance sheet? And maybe there's no change. Maybe this is just another, you know, technology wave that'll impact the business model in a similar way. Just curious whether or not this may be different, and if so, how? Sure, David. So you're absolutely right. Look, there are two fundamental changes taking place. One is the macroeconomic environment, and the second is the adoption of GenAI. On GenAI, I think our business model is certainly going to evolve and change. Certainly, there'll be a lot more investment that's gonna be required to be able to create some of these adapters and solutions that clients will expect to be prebuilt and that they will not be funding themselves. And at the same time, there will be a lot more risk-sharing that will be there. So it's gonna be a lot more contingent on us being able to deliver the outcome and the business benefit to our clients. I do think the shift in the commercial models will take place gradually, but perhaps the first change is gonna be to shift from a time and material type of contract towards more fixed price kind of contracts, or even initial upfront investment by us on repeatable adapters and accelerators that we'll need to invest in. From a margin standpoint, I think initially, because of the investment and because of our ability to demonstrate impact for our clients, the margins would be initially low. But over a period of time, because the value that we can deliver with GenAI is significantly higher, we would expect the margins to actually go above our corporate average. So as we scale up the business, I think this becomes a much more attractive business for us to be kind of going into. It's much higher value added, it's much more defensible, and it's gonna have a much better margin characteristics. Of course, it's dependent upon our ability to execute and our ability to demonstrate the results. It's also a business that's gonna involve a lot of continuous change, because with GenAI, you know, as you know, the LLM models keep changing every couple of weeks. And so we're gonna see more, you know, models kind of come in. We're gonna see more and different ways in which these are gonna get adopted. So the obsolescence is also gonna increase, you know, in this space, and therefore, the ability to remain nimble and modular, I think is gonna be critical for the long-term success, you know, in this space. So it's certainly got very different characteristics, and I think, as GenAI continues to evolve over the next one, two, three, five years, the business is gonna look and feel quite different, as we go along. Have you experienced the margin dynamic yet through a full cycle, meaning that you had to, you know, kind of go through the process of building or pre-building a solution or an adapter and seeing the deployment and then seeing the margins lift above the corporate average? Or is this still on a, you know, kind of your expectation based on what you're seeing in the market, but we're just not there yet? No, David, we've seen that. So one of the solutions that we built is PayMentor, which helps our clients collect their receivables, and it's entirely digital and an AI-based solution. We had very low margins on that piece of service line initially, and now that we are operating that at scale across multiple clients, our margins on that piece are higher than the corporate average. So we are seeing this on solutions that are getting adoption and which are getting to size and scale. But obviously, you know, those solutions that do not get to size and scale, those investments are things that we will have to recover, you know, through the ones that are successful. So it- Right, any- ... it's gonna be a portfolio approach for us. Any metrics that you can disclose in terms of where the portfolio is today on that journey, you know, in terms of how many deals that you have? It's still too early for us on that, David, to be able to disclose that. But you know, when we meet for our investor strategy day on May seventh, we will be actually unpacking some of this, you know, for you. Great. Thank you. Just one little quick thing, so I know we're going over here. Just on the working capital comments, in terms of the cash flows in the quarter, is that related to this dynamic of having to invest in some of these prebuilt solutions, or is that something just totally different in the quarter? No, no, David, it's more kind of one-time items that came through in the quarter and more working capital requirements. It's not really related to our investment process. Our investment process is ongoing. We obviously, we're investing more particularly into AI this year, but it's not related to that. Got it. All right, guys. Thanks very much. Thank you. One moment for our next question. Our next question comes from Mayank Tandon from Needham. Your line is now open. Thank you. Good morning. Thank you for squeezing me in here. I have just a couple of quick ones. One, Rohit, you mentioned earlier about right-sizing the workforce, given the news out there earlier in the month. I just wanted to get a sense of, as you think about upskilling and retooling your workforce in anticipation of some of these, GenAI-related engagements. Who are you looking to hire, and where are you finding the talent from? Just any sense in terms of your recruiting engine and, what some of the changes might take place over time as you position for growth from some of these GenAI platforms? Sure. So, Mayank, you know, for us to be able to successfully deploy GenAI, what we need are AI experts and what we need are engineers. The GenAI experts are things that we think we need to develop on our own because there isn't a very readily experienced, you know, skill set out there. But the engineering talent is something that we can acquire from the outside and add on to our capabilities. We're obviously investing very heavily in terms of reskilling and upskilling our existing employees, and that's being done not only through academic coursework that we're making available to our employees, but also through their direct involvement in projects and in POCs that we are developing so that they get the practical experience as well. Today, almost two-thirds of our employees have taken advantage of AI training and development tools. We have a core team of about 1,500 GenAI experts in the company, and we are gonna continue to add the engineering talent alongside with this AI expertise that we have. Got it. Very helpful. And then, just finally, from my side, Maurizio, are any thoughts around M&A pipeline? How are the opportunities in the market? Are you seeing more attractive valuations? And then just in general, capital allocation priorities as you move forward. Sure, Mayank. It's, So we're in a very good spot in terms of capital allocation. You know, when you look at our position as a company, you know, we've got right around $250 million in cash. You know, our debt now is right around $345 million. And we're generating adjusted EBITDA, you know, this year, projected will be somewhere between $375 million and $400 million. So we have plenty of capital to allocate, and we're fairly under-leveraged as a company, which puts us in a very good spot. So for us, going forward, you know, our allocation of capital really will be between share repurchase and M&A. And in the M&A pipeline, we are seeing, you know, more opportunities for us going forward, particularly in the core areas that are most important to us. It's capabilities within AI, particularly GenAI, data management. Those are really the core areas of capabilities for us in the segments we really operate in, to really build out and further develop our overall business, within those two areas. So that's... We're seeing more opportunity there. You know, in terms of valuations, we do see valuation becoming a bit more reasonable than they have been in the past, so that gives us more opportunity to really be more active in the M&A market. And you'll probably see that, you know, in the next 12-24 months as we go forward. And we have the ability to leverage our capital allocation between share repurchase and M&A, meaning if we do more M&A, we can reduce, if needed, our capital, our share repurchasing. But it's our intention to really push forward on both. That's great color. Thank you so much. Thank you. I'm showing no further questions. I would now like to turn the call back over to John Kristoff for closing remarks. Thanks, Justin. Thank you everyone for joining our call today, and I would again remind you to please register for the investor event on May 7th. Pre-registration is required, so please, if you have not done so, go ahead and do that. And as always, for any follow-up questions, feel free to reach out to me directly. Thank you. Have a good day. This concludes today's conference call. Thank you for participating. You may now disconnect.