Genpact Limited (NYSE:G) Q2 2023 Earnings Call Transcript

Genpact Limited (NYSE:G) Q2 2023 Earnings Call Transcript August 9, 2023

Genpact Limited beats earnings expectations. Reported EPS is $0.72, expectations were $0.69.

Operator: Good day, ladies and gentlemen. Welcome to the 2023 Second Quarter Genpact Limited Earnings Conference Call. My name is Chrystal, and I will be your conference moderator for today. [Operator Instructions] As a reminder, this call is being recorded for replay purposes. The replay of the call will be archived and made available on the IR section of Genpact’s website. I would now like to turn the call over to Roger Sachs, Head of Investor Relations at Genpact. Please proceed.

Roger Sachs: Thank you, Chrystal. Good afternoon, everybody, and welcome to our second quarter earnings call to discuss results for the period ended June 30, 2023. We hope you had a chance to review our earnings release, which was posted to the IR section of our website, genpact.com. Speakers on today’s call are Tiger Tyagarajan, our President and CEO; and Mike Weiner, our Chief Financial Officer. Today’s agenda will be as follows: Tiger will provide an overview of our results and an update on our strategic initiatives. Mike will then walk you through our financial performance for the quarter as well as provide our current thoughts and our outlook for the full year 2023. Tiger will then come back for some closing remarks, and then we will take your questions.

We expect the call to last about an hour. Some of the matters we will discuss in today’s call are forward-looking and involve a number of risks, uncertainties and other factors that could cause actual results to differ materially from those in such forward-looking statements. Such risks and uncertainties are set forth in our press release. In addition, during today’s call, we will refer to certain non-GAAP financial measures that we believe provide additional information to enhance the understanding of the way management views the operating performance of our business. You can find the reconciliation of these measures to GAAP in today’s earnings release posted to the IR section of our website. And with that, let me turn the call over to Tiger.

Tiger Tyagarajan: Thank you, Roger. Good afternoon, everyone and thank you for joining us today for our second quarter 2023 earnings call. Before I go into the financial performance for the quarter, I would highlight that our strong bookings momentum continued in the second quarter. We currently expect 2023 full year bookings growth of 25% to 30%, driven by the large deal and new logo wins. This positions us for strong top line growth in 2024 and beyond. Along with a great bookings quarter, our adjusted operating income margin, adjusted diluted EPS and cash flow from operations, all exceeded our expectations. While cost reduction and digital transformation continue to remain high priority for our clients, they are increasingly turning to us to help accelerate their data journeys, triggered by a desire to leverage an AI.

This will allow us to deliver more value to them through AI augmented end-to-end services. Specifically during second quarter of 2023, we delivered on a constant currency basis total revenue of $1.106 billion, up 3% year-over-year. Data-Tech-AI services revenue of $501 million, up 3% year-over-year and Digital Operation services revenue of $605 million, up 2% year-over-year. We also delivered adjusted operating income margin of 16.8%, a 10 basis points year-over-year decline and adjusted diluted earnings per share of $0.72, up 3% year-over-year. Our top line revenue during the second quarter was below our expectations. This reflects the current environment because across industry verticals continue to prioritize large transformations focusing on structural cost reduction, and replatforming operations, while at the same time seeing incremental pressure on discretionary project spending in areas related to marketing and short cycle advisory work.

We also saw some volume reductions from our high-tech clients driven by macro headwinds. As a result of these near-term challenges, Data-Tech-AI services where we design and build solutions to transform our clients business grew 3% on a constant currency basis. While digital operation services where we digitally transform and run our clients operations was up 2% on a constant currency basis. As a result of these trends, we now expect total revenue for the full year to increase 5.5% to 6.5% year-over-year on a constant currency basis, compared to our prior expectation of 6.5% to 8% growth. Mike will provide greater detail on our updated full year outlook. Despite the near-term revenue pressure, demand for our services remains strong. The incredible deal momentum we saw earlier in the year continue as we set a new second quarter and first half of the year record for bookings.

The majority of our deals remain long-term in nature, with approximately 70% being annuity based, which demonstrates the resilience of our business model. Win rates over this period were well above historic averages at more than 60%. In Q2, we signed six large deals, all of our total contract value of $50 million following the five we signed in Q1 of this year. Both are above historic levels. Our client roster also expanded nicely as we added 24 new logos during the quarter, including three large teams. Driven by robust new inflows, our pipeline reached another all-time high, including several new large deal opportunities. We are seeing an increasing trend of clients focused on getting their data consolidated, improving its quality and migrating and orchestrating that data in the cloud.

All this helps prepare them to use Gen AI, large language models and predictive AI and machine learning to deliver dramatically better business outcomes. Given our year-to-date record bookings and robust pipeline, we currently expect 2023 full year bookings growth of 25% to 30% above last year level of $3.9 billion. While we have not shared a bookings outlook in the past, given the consistent strength we are seeing, we thought it’s important to do so now as it shows the way our clients are thinking about setting themselves up to leverage Gen AI in the future. Let me add some color on the six large deals we signed in the quarter. For a large global insurance company, we will be managing all of their technology including infrastructure, applications and platforms, while we transition their data to the cloud and integrate all of their disparate systems and processes from acquisitions.

For one of the largest global technology platform providers to financial institutions, we will run and transform their operations in deposits, lending, collections, fraud, chargebacks and fraud alert management. The whole contract is transaction based pricing, and will create a true win-win as over time, we will use Gen AI and other digital technologies to run their operations. Our domain depth was the winner here. We are partnering with an eCommerce company to run all of their corporate technology security operations, finance and accounting and customer care services. Our objective is to modernize the technology apps, move them to the cloud and dramatically improve customer experience. The ultimate plan is to create the capability to leverage Gen AI to run these services.

We expanded our relationship with a global food company to standardize and transform their finance operations in EMEA to replicate our execution of the highly successful North America journey. The next objective here is to leverage Gen AI and predictive analytics from all the streamline data to drive competitive advantage in their markets. And finally, for a large industrial client, we will leverage digital technologies, advanced analytics and Gen AI to provide real-time critical decision insights to grow their business, reduce costs, and improve cash flow. We also expanded our relationship with a global financial institution to help build and launch an all digital savings account option for their customers. The combination of our experienced team, our banking experts, and digital technologists designed and build the front end user interface, as well as customer service fraud detection and other back office functions, which we are now running.

During the quarter, we continue to make great progress on our five strategic initiatives. First, revenue from our priority accounts grew 2% year-over-year during the quarter and represented approximately 62% of total revenue. Our investments in these clients are paying off as approximately 70% of our first half bookings were from our priority accounts. We continue to expect this portfolio to grow faster than the company average over the long-term. Second, we continue to deepen our partnerships with the cloud technology players with whom we are co-innovating and creating joint IP solutions. For example, with o9 Solutions, we launched a supply chain as a service offering that leverages Gen AI and helps companies navigate ongoing supply chain disruption.

The solution provides real-time scenario planning to help clients reduce supply chain costs, eliminate excess inventory and drive top line growth. Our new collaboration with Microsoft enables Genpact’s global talent to access Microsoft Azure open AI service, so we can build and implement Gen AI solutions embedded in our services. We are we’re building a Gen AI practice team with Google Cloud to help accelerate the deployment of cloud based AI solutions for businesses across our chosen verticals, with a particular focus on financial services. In close collaboration with AWS, we are building and bringing to market a Gen AI-based regulatory reporting solution for a large global power company. We continue to strengthen our partnership with ServiceNow by bringing our deep domain and process capabilities that allows ServiceNow to be the workflow of choice across multiple buying centers outside of the IT function.

Third, we’re continuing to invest in new operating centers and Tier 3 cities in India, providing us with access to larger and more diverse talent pools. In July, we opened our third new center this year. Fourth, we are seeing great momentum in our journey to non-FTE based commercial models, such as transaction based pricing and outcome based pricing. These now represent 60% of our revenues. More importantly, one-third of our first half bookings were non-FTE pricing. And we now believe that we will hit our original goal of 20% of revenue penetration well before 2026. This has also been driven by the increase in our AI-based solutions. And finally, our recent investment in our large deals team are generating great results, both in bookings and pipeline.

As expected, our attrition level has stabilized and it’s now 25% for the second quarter, significantly lower than the 38% during the same time last year. Adjusting for involuntary attrition and employees with less than 3 months of service, our attrition rate was even lower at 20%. Let me now spend a few minutes on our systematic approach to leveraging Gen AI in our business. And I discussed last quarter, we started our AI journey 5 plus years back and since then, we have invested, developed and refined our AI capabilities resolutions relevant for each of our services and industries. We’ve prioritized our resources and Gen AI actions in three broad areas. First, we are using Gen AI to disrupt less penetrated areas for us that are wide open for new service models.

We are calling this off-end strategy for us. Great examples of such services include customer care, FP&A, and sales and commercial digital marketing support. This will allow us to gain market share and drive growth. Second, we are prioritizing services where we are a recognized leader, such as financial accounting, financial crimes and risk services and supply chain services where infusing Gen AI can act as a catalyst to drive step function improvement and outcomes beyond just productivity. And third, we are rapidly deploying Gen AI within our own walls in areas such as HR, training, knowledge management, and internal software coding. This will help improve our margins and create use cases for our clients. Let me now bring this to life with a few examples.

For one of the largest global consumer brands companies in the world, we have reimagined the revenue forecasting process, leveraging AI and machine learning models at an SKU level, that significantly improved forecast accuracy from a 70% range to a 90% range, while at the same time, cutting cycle time from weeks to minutes. For our global automotive manufacturer, we are using Gen AI to gather and summarize competitive product features in real time, driving agility in their market response. For a global insurance company where we run their end-to-end insurance claims process for household goods, we’re using Gen AI to collect and analyze product and pricing information to more accurately determine pricing used for claims reimbursements, leading to faster and more accurate settlements.

For a digital financial institution, we are using Gen AI to determine the true meaning of suspicious keywords and customer transaction notes, reducing false positive alerts for potential nefarious transactions in our KYC and AML services. For a global media and entertainment company, we are using Gen AI to help customer care agents quickly resolve customer disputes with ideal responses developed by analyzing online chat data that understands customer sentiment real time. For a global medical devices company, we equipped the procurement team with a Gen AI engine that provides real time answers to questions related to contract causes, and payment terms to address vendor disputes with recommended actions. For a large Japanese technology conglomerate, we are charging and translating customer emails for rapid responses improving customer satisfaction and sales.

While still these are early days, I’m so excited that we have more than 60 specific Gen AI solutions, either being tested with clients or internally. These have led to 500 plus client conversations across verticals to create a Gen AI strategic roadmap for them. We believe we are uniquely positioned to build frameworks and playbooks for our clients to fine tune large language models with client specific data and industry domain data, given our deep understanding of the domain and the data. The other advantage we have is our historical focus on understanding end-to-end processes and delivering outcomes. This allowed us to partner with our clients on deployment, change management and adoption of these new AI solutions. All of this has quickly led to many new deal and flows embedded with Gen AI, opening up new opportunities for long-term growth and margin expansion.

As I said before, every enterprise is grappling with accessing clean data and orchestrating data to the cloud to leverage AI models and large language models. We believe this will increase our total addressable market at every technology wave in the past has done. Over the next 3 years, we plan to invest approximately $600 million, both organically and inorganically to continue to build out our AI capabilities. This will include investing in our own innovation R&D teams, brand co-innovation programs, Data-Tech and AI skills training and creating deep expert groups, as well as acquisitions focused on data analytics and IP and frameworks in the use of data models. With that, let me turn the call over to Mike.

Mike Weiner: Thank you, Tiger, and good afternoon, everyone. Today I’ll review our second quarter results and then provide you with our latest thinking regarding our full year 2023 financial outlook. Total revenue was $1.106 billion, up 2% year-over-year, or 3% on a constant currency basis. Data-Tech and AI services revenue, which represents 45% of total revenue increased 2% year-over-year, but 3% on a constant currency basis, largely driven by our ongoing demand for supply chain services, as well as automating client’s core finance and accounting functions. This performance was below our expectations due to lower short cycle discretionary tech spending, primarily in our financial services vertical. Digital Operations services revenue, which represents 55% of our total revenue increased 1% year-over-year or 2% on a constant currency basis, primarily due to deal ramps from existing and recent wins partially offset by reductions in volume from our high-tech counts.

We expect Digital Operations performance to improve during the second half of the year relating to large deal ramps from large bookings that Tiger referred to in his earlier remarks. From a vertical perspective, financial services increased 4% year-over-year, largely due to insurance client deal ramps and continued strong demand for our Digital Solutions, partly offset by current clients lower discretionary project legacy tech spending. Consumer and health care declined 1% year-over-year, largely driven by the impact of lengthening large deal cycles we saw during the second half of last year, as well as recent divestiture of businesses we previously classified as held-for-sale. This was partially offset by demand for our tech enabled finance and accounting process improvement solutions.

High-tech and Manufacturing increased 2% primarily driven by supply chain engagements, ramp ups and new logo wins. This was partially offset by the impact of reduced volumes in High-tech accounts that I mentioned earlier. During the 12-month period ending June 30, 2023, we grew the number of client relationships from annual revenue greater than $5 million from 154 to 180. Client revenues greater than $25 million expanded from 34 to 38 and clients more than $100 million increased from 3 to 6. Adjusted operating income margin was 16.8%, down 10 basis points year-over-year and up 40 basis points sequentially due to higher gross margin and operational efficiencies. As a reminder, our performance for the second quarter last year included the positive impact from a classification of a non-strategic asset is held-for-sale and excluded a $39 million restructuring charge related to actions we took to reduce our runway cost basis.

Gross margin for the second quarter expanded 90 basis points year-over-year to 35.3% largely due to revenue mix, operational leverage and the absence of the restructuring charge that was in — that was partly included in last year’s cost of goods sold. SG&A as a percent of revenue improved 60 basis points year-over-year to 20.8% as the absence of the prior year restructuring charge more than offset the higher investment in sales and marketing during the second quarter of 2023. Adjusted EPS was $0.72 up 3% year-over-year from $0.70 in the second quarter last year. $0.02 of the increase was primarily driven by higher adjusted operating income as well as the positive impact of lower outstanding shares of $0.01. Our effective tax rate was 22.7%, down from 24.8% last year, largely due to a higher mix of discretionary tax benefits in the second quarter of 2023 compared to last year.

During the quarter, we generated $171 million of cash from operations, up from $102 million during the same period last year. The increase was primarily driven by sequential improvements in our DSOs in the second quarter of 2023 versus an expansion during the same period last year. On a year-over-year basis our DSOs improved 2 days to 82 days. We continue to expect our DSOs to remain in the low 80 day range for the remainder of the year. Cash and cash equivalents totaled $491 million compared to $552 million at the end of the first quarter of 2023, largely reflecting the return of $145 million to shareholders. Our net debt to EBITDA ratio for the rolling four quarters was 1.3x. With our undrawn debt capacity, existing cash balances, we continue to have ample liquidity to pursue growth opportunities and execute on our capital allocation strategy that includes reinvesting in our businesses, strategic capability acquisitions, and return of capital to shareholders.

We continue to expect our net debt to EBITDA ratio to remain in our preferred 1 to 2x range. During the quarter, we continue to execute on our share repurchase program, and bought back approximately 3.2 million shares for a total cost of $120 million at an average price per share of $37.68. We now have repurchased $150 million of our shares, which is in line with our expectations set for the full year of 2023. With this activity and our projected full year dividend, we will pay off 50% of our expected operating cash flow. Capital expenditures as a percentage of revenue was approximately 1.4%. We anticipate a higher level of investment activity during the second half of the year related to large new deal wins, as well as opening new operational centers in Tier 3 cities.

Now let me update you on our full year outlook. As Tiger discussed earlier, clients have become more cautious on growth related to discretionary spending as they focus on their cost base agendas, which impacts our short cycle advisory project. At the same time, we are prioritizing large transformational deals. This dynamic resulted in less than near-term revenue as bookings mix up skewed towards large deals with revenue that gets recognized over a multiyear period. As a result, we now expect total revenue to be between $4.59 billion and 4.64 billion representing year-over-year growth of 5% to 6% or 5.5% to 6.5% on a constant currency basis. We continue to expect our full year adjusted operating income margin to be approximately 16.8, including investments related to AI, aligned with our strategy to drive margin expansion at a faster pace than we have done historically.

Given many of our recent large field bookings having initial onshore delivery, we continue to expect our full year 2023 gross margin to be relatively flat to slightly down compared to 2022 levels. We continue to expect our full year 2023 effective tax rate to be in the higher end of our 24% to 25% range. Given this updated outlook, we now expect adjusted earnings per share for the full year 2023 to be between $2.91 and $2.94, representing a year-over-year growth of 6% to 7%. This includes the positive impact related to our year-to-date share repurchases of $0.04 per share. Let me update you on our thinking and an expected revenue adjusted operating income cadence for the second half of the year. Due to deal ramp activity related to our new large bookings, we expect to build through the year with the remainder of the year.

as well as facing easier comparisons we expect the year-over-year revenue growth for the second half of the year to be slightly higher relative to the first half of the year. Therefore, we anticipate mid single-digit quarter-over-quarter growth for the third quarter expanding to high single-digit growth in the fourth quarter. We now expect our adjusted operating income margin to expand modestly with the sequential revenue growth that we absorb higher levels of investments during the second half of the year. Lastly, we continue to expect a full year cash flow operations of approximately $500 million. As Tiger discussed earlier, given our year-to-date record bookings and robust pipeline, we expect full year bookings for 2023 to grow 25% to 30% over the last year’s $3.9 billion.

With this anticipated growth, we currently expect to return to double-digit top line organic growth in 2024. With that said, let me turn the call back over to Tiger.

Tiger Tyagarajan: Thank you, Mike. As we deal with the effects of the challenging macro environment, we remain very confident in our ability to achieve 10% plus organic revenue growth and adjusted operating income margin expansion at a faster pace and historic levels through 2026. I want to point out a couple of very exciting trends we have seen in our first half bookings. Our technology bookings are up 80% year-to-date, and our pipeline of technology services deals is robust, showing the desire for our clients to have us as a tech partner who understands and drives business results. The other exciting trend is that 51% of our deals, data analytics, tech and AI embedded in the solution, clearly showing the domain and data tech [ph] strength we have as a differentiated market position.

With clients striving for greater productivity from their tech stack, we see opportunities to leverage Gen AI to the right code, optimize resource allocation, system troubleshoot, help with network configuration as well as analyze vast amounts of information to generate unique insights to significantly enhance decision-making. This, we believe, expands the total market for us. It is clear that the opportunity to learn new skills in digital and generative AI as well as work for an organization known for fostering an innovative culture is helping us attract and retain great talent. At the heart of our Gen AI value proposition is a core group of highly skilled data scientists, domain experts and engineers that make up our AI center of excellence.

Through our Data Bridge Certification program, we trained more than 70,000 global employees over the past 3 years in contextual data literacy. This sets us up for our Gen AI journey where we recently launched a new AI training program that currently has over 20,000 enrollments and 12,000 members of our workforce have completed the program. We have also trained approximately 10,000 team members on prompt engineering. Despite experiencing some near-term pressures primarily related to discretionary spending, our future remains very ready. Our record year-to-date bookings and our growing quality pipeline sets us up nicely to be back to a minimum of low double-digit top line growth for 2024. With that, let me turn the call back to Roger.

Roger Sachs: Thank you, Tiger. We’d now like to open-up our call to your questions. Chrystal, can you please provide the instructions?

Q&A Session

Operator: [Operator Instructions] And our first question will come from Tien-Tsin Huang from JPMorgan. Your line is open.

Tien-Tsin Huang: Hi. Thanks. Good afternoon. I just wanted to ask first on the revenue revision. I hope you can hear me okay? I’m in the airport. Can you hear me?

Tiger Tyagarajan: Yes, can hear you clearly, Tien-Tsin. Yes.

Tien-Tsin Huang: Great. Thanks, Tiger. I just want to ask about the revenue revision and maybe the attribution between short cycle work being lower as well as the lower volume that you saw. And are you assuming any recovery in the second half outlook on either of those areas? Or is it really just a large deal wins [indiscernible] in the second half outlook?

Tiger Tyagarajan: Yes. So great question, Tien-Tsin. So one, we’re not assuming any recovery for short cycle because you need a crystal ball to actually get come to that conclusion. So we’re not doing that. And most of the growth that we’re going to see in the second half is driven by the large deal wraps as well as continuing with Data-Tech-AI journey and consulting technology advisory, et cetera, work that is ongoing right now. We are not expecting a recovery for the second half. And as it relates to your earlier part of the question, the volume reduction that we saw in high-tech clients probably accounted for, like, 40% of the revenue change and the other 60% would be advisory work.

Tien-Tsin Huang: Thank you for the complete answer there, Tiger. So just my quick follow-on question just on the large deal momentum, obviously, great there. Any comments on the margin profile of some of those deals, any rebatching [ph] that’s associated with some of them and the timeliness of the ramps. How do they look versus what you’re accustomed to seeing? Thanks.

Tiger Tyagarajan: Yes, so great question again, Tien-Tsin. So one, I think about 40% of the deals have rebatch, but it’s only a component of each of those deals, and the others don’t. And that’s a typical mixture we have. So it’s not dramatically different. And typical large deals, it’s always a combination of rebatch and the regular ramp. That’s one. True margin profile in these deals not any different with one clear significant difference that I called out, more than a third of the deals in the first half have transaction-based pricing and non-FTE pricing as the commercial model. And that is something that we have been pushing, as you know, pretty hard over many years. We think that the momentum that we are seeing in the marketplace around AI solutions, Gen AI solutions and our ability to begin to integrate those into our solutions allows us to create value propositions that makes it a win-win between us and our client.

So the way I would think about the margin profile is the base case margin profile is no different, but actually, the real opportunity here is that the margin profile will grow as we deliver more value for our clients.

Mike Weiner: Yes, I would just like to add on to that, Tiger. If you think about our strategic plan and increasing our margin year to year at a higher pace than we have, we see no change in that at all putting through 2024 and on beyond.

Tien-Tsin Huang: That’s great to hear. Thank you both.

Tiger Tyagarajan: Thank you, Tien-Tsin.

Operator: Thank you. Our next question will come from Keith Bachman from BMO. Your line is open.

Keith Bachman: Hi. Many thanks. I have two related questions. The first one, Tiger, I’m trying to string together the thread. You talked about double bookings growth of 25% to 30% on a base 3.9. And so 25%, 30%, let’s just use 25% for round numbers and top line growth of low double digits in 2024. I thought that was a very interesting statement, obviously expressing confidence in your durability. But what’s the difference? I assume part of it is the bookings take while to manifest in the revenues, but it would seem that implicit within that, there’s also a certain amount of assumptions surrounding that the short cycle work will be pretty weak. But I was just hoping if you could tie together say the 25% to 30% versus low double-digit rev growth? And then I have a follow-up.

Tiger Tyagarajan: Yes. So I think, you partly answered the question, Keith, yourself. When you have a longer, bigger deal and a long cycle deal, an annuity deal signed, you’re obviously making that a 5-year contract. And when that happens, while at the same time, short-term smaller advisory work and the deal momentum there is slower. And really, what you’re seeing is a rotation of the booking portfolio from those short cycle to larger annuity. Therefore, that 25% to 30% growth cannot translate automatically to an equal growth in the subsequent immediate year. So that’s part of the answer. The second is that you’ll see that come through over the years. And the first reflection of that is the fact that we are saying that we will get back to double-digit growth in 2024.

If you go back to our history, you will see many years where this has played out exactly this way, where you have a bookings year, and I could think about 2018, which was a great booking year that then proceeded very strong revenue year, but the difference between the bookings growth and revenue growth mirrors the kind of numbers we’re talking about here.

Keith Bachman: Right, right. Okay. My second question relates to that, Tiger. And I’m trying to — and I ask many of our service provider companies the same question, but how do you envision this supply disruption or efficiency gains associated with Gen AI? And specifically, I think Genpact has a large customer service representation. I don’t know what percent of revenues is, but many leading pundits are calling out significant efficiency gains and seat-based models for customer service in particular. And so there will be — and most of that work is on an FTE basis. So there will be lower seats. And just thinking about how you — a, is that a statement that you agree with? And b, how do you offset that? And I know you talked about success-based models being a greater part of your journey.

I assume that would be part of the answer. But at the same time, a CFO would want to pay fewer dollars as AI is implemented at customer service activity. So I’m just trying to string together the various — really, how do you think about Gen AI? Where is the disruption most likely? And b, how does that work that you’ll use success-based models to offset the efficiency gains with Gen AI? Thank you.

Tiger Tyagarajan: So Keith, everything that you said, we agree with except one data point, which just to correct you, customer care, customer service work for us is sub 10% of our business. If you remember, financial accounting is our largest portfolio, insurance claims, insurance underwriting, lending underwriting, risk services, I can go on and on supply chain, of course, sales and commercial support. So customer care, very small proportion of our business as compared to typical comparable very large only customer care providers, which then actually provides an opportunity for us that I called out in my script, basically saying customer care is going to be disrupted, so completely agree with you. For us, therefore, it becomes off-end strategy in Gen AI.

So what we are doing as we speak is building solutions and taking it to customers as we speak, where we do not do customer care work for them. And we are telling them, there’s a new model, and this is the way you should do it. So you’re absolutely right. It’s one of the areas that will get disrupted. We are already seeing that in pilots that we are running. The proportion of that work for us is small. By the way, even the work that we do in customer care is complex, high value customer care.

Keith Bachman: Okay.

Tiger Tyagarajan: We do not do what one would call typically commoditize easy customer care less amenable to immediate disruption of elimination from Gen AI. But we have the skills and the capability and that’s exactly what we’re doing, which is why we called it often part of our strategy. The other place that I would add to that is what I concluded my remarks with is, if you think about typical application development and simple coding, I think the narrative is very clear out in the marketplace, that is, again, something that is going to get disrupted. We ourselves have run pilots for internal coding work that we do, and we are looking at anywhere from a low 40% to 70% potential disruption. Again, not a big piece of our portfolio. Again, something we are taking to our clients as part of our offense strategy and saying, we can do this for you in a different way than the way it’s being done either by your current providers or by you yourself.

Keith Bachman: Okay. Very interesting, Tiger. Many thanks for your answer.

Tiger Tyagarajan: Thank you, Keith.

Operator: Thank you. Our next question will come from Maggie Nolan from William Blair. Your line is open.

Maggie Nolan: Thank you. Maybe on the outcome based pricing since that was part of the last topic here, can you provide a little more information on what types of engagements are seeing more of an uptick in this outcome based pricing? And then any pattern in terms of which industry relationship length or anything like that in terms of what clients are embracing outcome based pricing?

Tiger Tyagarajan: Maggie, again, great question. I will start the answer by saying the umbrella term to think about is non-FTE pricing, which is pricing that is not related to headcount because underneath that, I would start with transaction pricing and overall fixed pricing and then outcome based pricing, almost in that order. And the reason I’m saying that is because a lot of the transactional work that gets done in our kind of services lend themselves very easily to transaction based pricing. And simple example of that would be, let’s start with accounts payable and accounts receivable, they lend themselves. Then you move to financial services transaction work, whether insurance or the financial services, technology provider clients that we called out, we are managing actual customer service response is not on the phone, but actually in more elaborate fashion.

You are doing fraud learn management, you are doing underwriting responses, you are doing insurance claim responses, insurance claims management. Anything that is transactional lends themselves really well to transaction based pricing. The industry that’s most open for this is financial services because they understand transaction based pricing, they have volume, they have velocity and frequency of throughput. So we are seeing a real — and I think that’s something that’s changed in the marketplace literally in the last 6 months, but probably more in the last couple of years because we’ve been pushing this agenda for 5 years, which is a receptivity to the model and understanding that actually it creates a win-win because it allows us to invest and build solutions that embed AI and Gen AI and machine learning and all digital technologies that then deliver great value for the customer and for us, but also for the end customer because when we do this really well, the consumer of the bank or the customer of the bank is the one that’s most defied through this journey.

Maggie Nolan: That’s really helpful, Tiger. Thank you. And then there’s been continued good large deal activity. So I’m wondering how you would characterize the competitive environment right now and then the pricing environment for competitive deals?

Tiger Tyagarajan: So Maggie, the competitive environment is not that different from what it’s been actually for quite a few years. I would say two things that have always been important and probably have got elevated in importance. And I would suspect both the digital transformation journey coming out of the pandemic as well as now the Gen AI journey that people are thinking through is a big motivation for what’s changing. I think there’s a deep realization of the importance of understanding my industry, my data, my processes that we’ve always believed is one of the most important things in the journey. I think most of our clients are beginning to recognize that. And where it really comes home is when you start deploying intelligent solutions that have intelligence built into it with these AI models.

You really want to make sure that the data that has been consumed for that intelligence is fully understood. And then when you apply guardrails around responsible AI, around ethics, around InfoSec and privacy. Once again, I think the best people to actually bring all of that out and put that on the table and figured out the right road map and playbook and journey are people who understand the domain and process and the data. And we shine in those conversations. So I would say competitive environment, not that different. We are shining through, our win rates are therefore up. That’s very clear. We are shining through and winning in every deal. The first callout that we get when we win is you guys shone through in your domain and data understanding.

And I think that’s the world we are in, and we really feel excited about that world.

Maggie Nolan: Thank you.

Tiger Tyagarajan: Thank you, Maggie.

Operator: Thank you. Our next question will come from Ashwin Shirvaikar from Citi. Your line is open.

Ashwin Shirvaikar: Hi, Tiger, Mike, Roger. Hope you’re well.

Tiger Tyagarajan: Yes, Ashwin.

Mike Weiner: Ashwin, hi. thank you.

Ashwin Shirvaikar: I guess, I wanted to ask, if you could look at your two segments, Data Tech and Digital Ops to sort of break down by — break down each segment by what portion of each tends to be discretionary where clients can push stuff around in terms of timing. The reason I ask is because while you — in the prepared remarks kind of pointed out, it’s the shorter term, more discretionary work that is being pushed out. When I look at your 2Q results versus consensus expectations, it’s really the Data-Tech-AI that was in line, whereas Digital Ops was below expectation. So if you could kind of break that down and kind of give us an idea of what part of each is discretionary and which functions that would be great.

Tiger Tyagarajan: I have Mike answer which portion is discretionary on each of those segments, but a quick reaction to the revenue impact of the two things we called out. We called out advisory and that front-end type of work. Most of that — almost all of that would reside in the Data-Tech-AI and impacted Data-Tech-AI. But we also called out the volume reduction in a couple of the high-tech clients. Those are all in Digital Operations. So absent the high-tech volume reduction, we would have seen even more growth in Digital Operations with the soft was being in — versus our expectation on Data-Tech-AI driven by the advisory work. So if you parse out the impact of the high-tech 1 is on digital operations, and that is a one-off. The Data-Tech-AI is a much more pervasive advisory work where people are reorienting the discretionary expense. Mike?

Mike Weiner: Yes, if I just double click on that a bit, if you think about your [indiscernible] it’s all really coming from Data-Tech and AI, the Digital Operations, the volume that you alluded to. When you think about it, it comes to three large kind of cohorts of work that we do: one, doing some legacy technology work. Now primarily was also affected in our financial vertical. Digital marketing and our experience work, which pretty much indexes to the market as a whole. And then the last one that Tiger just alluded to, it’s the advisory work that we do, which encompasses a lot of operational advisory work that we do blueprinting, supply chain and procurement work that is just not at the level we anticipated earlier on in the year. And we are holding our outlook relatively flat for that — exactly flat for that. They were not at the remaining part of the year.

Tiger Tyagarajan: But I want to add, Ashwin, one of the interesting element. If we double click on specific clients where big transformation journeys are being — are beginning to get undertaken, whether the deals we signed or the deals we are right now working on. One of the most interesting things that we are noticing is that when one of those clients decides to undertake a big transformation journey, they actually call a stop to all kinds of little things happening in those arenas. And stop that work because I don’t want to spend that incremental dollars there because I’m now beginning to undertake a big transformation journey. So a little bit of this is a rotation. Even if our clients on where they spend the money, not on 10 little things but on one big thing because I want to get hold of my data in order to be able to then have AI models consume it in order to be able to deliver much bigger value.

And I better do it now because otherwise, I’ll be comparatively disadvantaged.

Ashwin Shirvaikar: Understood. Understood. Thank you for that. And then as I sort of think of 3Q versus 4Q, I think earlier you were set up with — and I hate using word hockey stick, but it was a bit higher in 4Q than in 3Q in terms of sort of the ramp through the year. Are we to assume that part of that — the shape of that ramp is unchanged? It’s still very back-end weighted? And then what’s the confidence that some of those implementations and ramps will stay the way that they were planned? I kind of had asked a similar question, I think, last quarter, but I just want to make sure what has changed in the interim?

Mike Weiner: So we are very comfortable with that kind of ramp up or vertical associated with the revenue growth. It’s really all tied to these large deals we’ve been talking about throughout the call. And I think we feel good about them when our revenue recognition starts when we implement those large deals, which we’ve signed. And again, as Tiger talked about, there’s a large rebatch component of them that allows us to start earning revenue on it sooner rather than later. So it’s just projected timing on that from existing signed deals. We feel really good about that.

Tiger Tyagarajan: Yes. And Ashwin, just to elaborate and add some more color to what Mike said. The shape of the curve, zero change in the shape of the curve from what we talked in our second quarter call on our first quarter earnings versus today. You asked the same question last time, which is another question. And I can tell you that compared to the call that we did versus today, not one of those deals have changed their trajectory in the ramp. There has been no slippage at all, which is why all of our revenue projection now and the change that we’ve had between what we spoke in the Q2 earnings call, earnings call [ph] we did in Q2 and earnings call today is all driven by Data-Tech-AI advisory work and high-tech volume reduction. None of that is driven by any change in the ramp schedule. And I’m saying this as we speak today. So we feel good about that ramp.

Ashwin Shirvaikar: Yes. [Indiscernible]. Thank you.

Tiger Tyagarajan: Thank you, Ashwin.

Operator: Thank you. Our next question comes from Bryan Bergin from TD Cowen. Your line is open.

Bryan Bergin: Hi. Good afternoon. Thank you. Wanted to start on bookings here first. The 25% to 30% growth expectation, are you tracking to that level through the first half? Are you above it or do you relying on material large deal wins that have yet to be signed for that?

Tiger Tyagarajan: I mean [indiscernible] Brian, we are actually above it. And the reality is that bookings are lumpy. The good news is, as I think we said in the first quarter, we had record bookings. And actually, the second quarter was even better than the first quarter. So not only is we are tracking above that in the first half, we are actually tracking second quarter better than first quarter. Having said that, we are not making that assumption for the second half. So it’s actually a good assumption, but not an exponentially curve assumption. So we feel good about our 25% to 30% growth for the year.

Bryan Bergin: Okay. Very good. And then a follow-up, just on the ’23 growth expectations, I may have missed this. Mike, can you talk about the updated segment growth outlook for Data-Tech-AI and Digital Ops and just anything worth calling out for each of those segments on exit rates within that high single-digit growth total company rate?

Mike Weiner: Yes. We didn’t really address it from that perspective. We just really looked at the cadencing or the patterning of that, right? So you’d expect mid to low single-digit expansion growth in our digital operations business sequentially in third quarter, fourth quarter and so on, right? And then returning to mid to high single digits in our Data-Tech and AI and then obviously well into the double-digit, high double-digit growth rate in the fourth quarter, and that’s how it patterns out. You then expect us to return to somewhat of a normal pattern of revenue growth of the mid to low single digits on our digital operations and mid-teens on Data-Tech and AI as we move through 2024 as we are anticipating somewhat normalization, particularly in Data-Tech and AI work that we are doing.

Bryan Bergin: Okay. Understood. Thank you.

Tiger Tyagarajan: Thank you.

Operator: Thank you. [Operator Instructions] And our next question will come from Surinder Thind from Jefferies LLC. Your line is open.

Surinder Thind: Thank you. Tiger, as you think about the large bookings that you’re experiencing, how do you view the longer term opportunity here? It seems like the growth is elevated. So should we expect at some point, the cycle to turn? Or do you feel like there may be a secular discussion that you’re having with clients at this point?

Tiger Tyagarajan: I think, Surinder, it’s actually, by the way, a great question. We’ve talked a lot about it inside, is this episodic or is this secular? I think we are beginning to come to the conclusion that there is a secular trend here. And the reason for that is authority [ph]. One, it’s pervasive across all our industry verticals. I don’t think there’s a single vertical that stands out as being different from the other in either direction. Second, it’s pervasive across geographies. All the geographic markets that they’re involved in, North America, which is the U.S. and Canada, Western Europe, including places like Germany and France, Japan and Australia. So it is across geography. And the third is coming out of the pandemic was digital transformation.

It was talent leveraged. And now it’s AI, and I get hold of data, and I don’t have time. We think that is very secular as long as we all believe that this whole AI journey has now moved into a very secular trajectory. There’s still a lot to be sorted out and has to be very clear. It’s still very early days, but it will get done. There will be disruption and an ability to provide AI-infused services and AI-augmented services that deliver really step change in outcomes of all times in some of the examples that we gave. So we think this is very secular across. One of the most interesting things that we think has happened for us that actually is going to help us in this journey is that we may start with a client with finance and accounting or we may start as a client with customer care of the more complex customer catch up or work.

Our ability to then take multiple services across the enterprise to almost all buying centers in the C-suite, I think, is dramatically different today than 5 years back, which then means that priority accounts that we have called out, once we sign an account in a particular area, as long as we execute, our ability to then go and open up new buying centers with new services and keep growing that account, it sets us up very nicely. And then the final statement I will make is all of these clients are looking for the ability to find a way to use data. Data cuts across multiple services. So that’s the other reason why we believe that our ability to take a combination of services over time where data actually is traded between these services and then you use AI to actually create great value.

All of that sets us up for a real secular trend here.

Surinder Thind: That’s helpful. And then a question more about just near-term trends. When we think about some of the volume reductions by your high-tech clients, how should we view that in terms of the big picture here? Is that a little bit of a canary in the coal mine in the sense that it was the high-tech clients that were the first to kind of start to lay off people to exhibit some caution. And so now we also are starting to see some volume reductions there? Is there a chance that if there’s a bit more macro weakness that this kind of spreads? Or is this just some conservatism that you’re seeing on the part of those clients?

Tiger Tyagarajan: So actually, the way I would think about high-tech is the canary in the coal mine actually sounded the alarm, not now, but 6, 7, 8, 9 months back. And the actions that they first took was looking at their own headcount. And we’ve all seen a bunch of announcements on that over the last 6 to 7 months. As they looked at the work that has been done, most of them, when I talk about volume reduction, it’s basically saying, I do not need to provide this [indiscernible] treatment to this customer. I do not need to check this so much. Let’s not use this policy to check this content. So it’s in the area of trust and safety. It’s in the area of digital marketing and all the work that has done between these high-tech clients.

The flow through of that into other industries, taking on the cost base has already happened. Part of the reason why we talked about big deals is also because a lot of our clients have been focused on cost reduction. For them, it’s not about — I’m going to do less work, they can’t. That work has to be done. In the case of high-tech, they’ve decided to do less work. We actually believe given that a number of these high-tech clients are actually — have reset their cost base, at least based on what we are all seeing in the public domain, that there will come a time when they will come back and start doing more work, particularly as it relates to data annotation, getting ready for Gen AI, getting ready to actually fine tune their models. There’s a lot of new work that’s going to come up from the same high-tech clubs.

Surinder Thind: Thank you.

Tiger Tyagarajan: Thank you, Surinder.

Operator: Thank you. And we do have a follow-up from Ashwin Shirvaikar from Citi. Your line is open.

Ashwin Shirvaikar: Thank you. Appreciate the chance to ask the follow-up. It’s on margins and cash flow. Normally, when one sees slower ramps or put out ramps, it tends to be positive for margins and cash flow. And conversely, when you see a lot of different actually ramping that tends to be pressure. So how should be corresponding to the double-digit growth expectation for next year that you kind of alluded to, how should we think of margins and cash flow with regards to that?

Mike Weiner: So in terms of that, let’s talk about cash flow first, and we’ll talk about margins. So our cash flow guidance for the year hasn’t changed at all, approximately $500 million and what our conversion is. I would anticipate that growing in line with the business in totality. As far as the margin growth from our huge piece of the margin expansion that we’ve identified, this year we went from, I think, last year 16.5%. So our guidance this year is 16.8%, about 30 bps. The largest component of that is going to be really driven by operating leverage of the business, right, as well as just the continued efficiencies that we drive on behalf of our clients that flow through in our business. The offsetting lever to that, and we’ve talked about is that our continuous investment, our “organic” R&D and our business we continue to invest in new capabilities for the future.

So we will continue to manage that lever accordingly to continue to hit our commitment in terms of that margin expansion on a sequential basis. So that’s really what our operating plan. It really works well from that perspective.

Tiger Tyagarajan: Yes. And just to add one final point, Ashwin. Remember that we are deliberately dialing up our investments. We’ve already done that in part of Q2. We are doing it as we speak in Q3 in both the R&D side, particularly with all the Gen AI discussions that we had, creating the center of excellence, creating the proof-of-concept and the pilots as well as in sales and marketing and having teams take those to clients. I talked about conversations around Gen AI as a topic with a range of clients. Almost every one of them converted to a second and a third conversation. And then you have a set of, okay, let’s try this pilot that then leads to an actual pilot. Whether it leads to ultimate production, we’ll have to wait and see when that happens. So we haven’t seen a big inflow of revenue directly from Gen AI, but all of that requires a lot of really clever people to be deployed and we are using our investment dollars to be able to do that.

Ashwin Shirvaikar: Understood. Thank you.

Tiger Tyagarajan: Thanks, Ashwin.

Operator: Thank you. And our next question will come from Keith Bachman of BMO. Your line is open.

Keith Bachman: Hi, guys. I thought I’d jump back in queue. Tiger, I wanted to hear if you could flush out a little bit more about your experience in non-FTA related business. And that is to say a couple of things. One, where is the adoption trends been most successful? Two is, presumably, there’s some risk associated with the non-FTE that is, particularly if they’re success based business models. What have your experience been in actually running into some challenges. And then third, as you think about it, where do you expect that to go? And why is it accretive to revenue growth if you’re going with success based or non-FTA business models? Why would it be accretive to growth rate? Thank you.

Tiger Tyagarajan: Yes, let me answer the first part, Keith. So the success — the aggregate success over now 10 years where we’ve had non-FTE pricing is that it is better than just pure FTE pricing from our ultimate margin delivery perspective for Genpact. And it is obviously hugely beneficial for our client [ph]. There’s no question. And I’m talking about the aggregate. By definition, therefore, there are some that don’t work, and we learn from that and improve it and then we ultimately deliver. So on the aggregate, hugely successful. The reason for that is actually very simple. The only places where we actually go in with those types of models is where we understand the domain, understand the industry, understand the process, understand the function.

The more we understand that, the more we know what levers to pull, what processes to change, what technology to implement, how to train the AI model and at what speed and pace can we do that? And therefore, what risk are we taking in that journey. And we’ve been successful in our journey through that over many years actually. The market’s not been refactored and actually buying that enough, we’re not beginning to see that change. So we feel really confident that, one, we will be able to deliver great value to our clients. There is an alignment of goals, there’s an alignment of innovation and an alignment of governance that actually also makes that happen. I don’t think we should underestimate that. We also should not underestimate how much change is needed in order — I mean if you take an AI implementation journey in an end-to-end service, that’s not just — just not a technology implementation.

It’s going to ask people to change the way they have done something for 20, 30 years. That change management and agenda becomes so much easier if you have a full alignment of goals, which is what these models actually ultimately give. So we are very, very happy that actually it’s undertaking this journey because I think it will be great for clients and will be accretive for us.

Keith Bachman: So Tiger, is there any difference in the upsell rate associated with once you do a success base or non-FTA model on the upsell rate over time?

Tiger Tyagarajan: I don’t know whether we can call that out as very different. Obviously, we deliver more value than the clients want to be more delighted and therefore, I’m sure there probably more upsell, but that’s right.

Mike Weiner: Yes, still two thoughts. A lot of the models, not in the new deal bookings that we have right now, these transaction or alternative commercial models that we’ve done have come at the end of a renewal of an engage, right? So it’s kind of hard to isolate that cohort. So we’ve learned the client has learned they’re comfortable with it. and now we are going to move to them on. And then just also moving on to what Tiger talked with you, want to just look at pure profitability of the roughly 16% of total revenue that we have today associated with it, the margin is substantially higher than a margin on average, right? And a lot has to do with, we are never going to get to 100%, right? But we are picking and choosing the models that will work for us and we’re underwriting those outcomes for the client.

And that’s really the win-win situation that we are in right now. And we think we are going to, as Tiger alluded to, we have a 20% revenue goal for that in 2026. We should exceed that notably.

Tiger Tyagarajan: Yes. A little bit, I would call out a little bit of DNA of process, Six Sigma Lean, that I think makes a big difference when you’re trying to drive defects down, when you’re trying to estimate exact risk that you’re taking. And therefore, on the aggregate, we end up delivering. Obviously, there’s more risk. Therefore, the margin is higher, and that risk plays out and some of those deals not work not exactly that we — the way we wanted it. But on the aggregate, it actually — the portfolio works out really well.

Keith Bachman: Understood. Many thanks.

Tiger Tyagarajan: Thank you.

Operator: Thank you. And I’m showing no further questions from our phone lines. I’d now like to turn the call back over to Roger Sachs for any closing remarks.

Roger Sachs: Thanks, everybody, for joining us today, and we look forward to speaking with you again next quarter.

Operator: This concludes today’s conference call. Thank you for your participation. You may now disconnect. Everyone, have a wonderful day.