Genpact Limited

Good day, ladies and gentlemen. Welcome to the 2023 first quarter GenPax Limited Earnings Conference Call. My name is Gigi, and I'll be your conference moderator for today. At this time, all participants are in a listen-only mode. We will conduct a question and answer session towards the end of this conference call. 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 GenPax website. I would now like to turn the call over to Roger Sachs, Head of Investor Relations at GEMPACT. Please proceed.

Thank you, Gigi, and good afternoon, everybody, and welcome to our first quarter earnings call to discuss results for the period ended March 31, 2023. We hope you had a chance to review our earnings release, which was posted to the IR section of our website, GEMPACT.com. The speakers on today's call are Tiger T. Adarajan, our president and CEO, and Mike Wiener, our chief financial officer. Today's agenda will be as follows. Tiger will provide an overview of our results and update on our strategic initiatives. Mike will then walk you through our financial performance for the quarter, as well as provide our current thoughts on our outlook for the full year 2023. Tiger will then come back with some closing remarks, and then we will take your questions. Expect our 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. can find a reconciliation of these measures to GAAP and today's earnings release posted to the IR section of our website. And with that, let me turn the call over to Tiger.

Thank you, Roger. Good afternoon, everyone, and thank you for joining us today for our first quarter of 2023 earnings call. Today, I'll talk to you about our financial results for the first quarter of 2023. and about how we believe we are uniquely positioned to partner with our clients in leveraging generative AI, large language models, or LLMs, and broad AI and machine learning technologies. So first, our results for the first quarter were solid and reinforced the powerful interlinkage between our data tech AI and digital operations services that leads to many new opportunities to continue to create value for clients and growth for us. What was most exciting was the record level of first quarter bookings we signed in the quarter, a new record pipeline we entered the second quarter with. In the first quarter of 2023, we delivered on a constant currency basis, total revenue of $1.089 billion, up 4% year over year. Data Tech AI service revenue of 485 million, up 6% year-over-year, and digital operations services revenue of 604 million, up 3% year-over-year. Additionally, we delivered adjusted operating income margin of 16.4%, expanding 140 basis points year-over-year, and adjusted diluted earnings per share of 68 cents, up 13% year-over-year. Over the last 60 days, I have had the opportunity to speak to 150-plus C-suite executives of large global enterprises, and I'm hearing a consistent set of themes. They all face the reality of having to do more with less, so they remain focused on cost takeout and cash flow improvements. At the same time, they want to allocate resources to their most critical long-term transformational programs. including starting to think about ways to leverage generative AI, LLM, and more broadly, AI in their business. It is this backdrop against which we set the new record for our first quarter bookings, including five large deals, with total contract values greater than $50 million. While almost three quarters of our bookings were from our priority accounts, we also added 17 new logos this quarter, with an average contract value of about $6 million compared to the $3 million level for the full year 2022. Let me give you some color on the five large deals because there are some consistent themes there. First, for a leading technology platform provider in the automotive industry, we are modernizing their application stack, moving it all to AWS Cloud, redesigning their finance, sourcing, procurement, and customer service operations, to improve efficiency, and more importantly, access clean data that can be orchestrated to leverage AI-based solutions. The strategic objective is cost reduction, but also improvement in end-to-end dealer and customer experience that will drive growth. For one of the largest global consumer goods companies, we will redesign, transform, and run their full order to cash and source to pay services end-to-end across 100 plus countries to dramatically reduce costs and improve working capital. Even more importantly, using our AI and cloud-based Quora AP platform, we will standardize and automate master data management and contracting, which will then allow use of AI for better decisioning on buying, supplier choices, and sustainability, as well as customer segmentation and customer credit. For a large industrial equipment manufacturer with a very fragmented technology landscape across 50-plus countries, we will redesign and run their end-to-end global finance processes and thus enable them to fully separate into two listed entities. We will combine digital partner technologies with our domain depth and process expertise, which will then allow data to be leveraged for AI and generative AI, delivering savings and commercial benefits. a leading global medtech company changed its strategy of many years, running their own global captives to now partnering with Genpak. Their motivation was to leverage the latest AI, generative AI, and LLMs for which they first need access to clean data consistently across 80-plus countries. We are taking over their global captives to not only drive costs down, but also deliver a commercially competitive advantage to drive their growth. And finally, for a global beverage company, we're taking over their European capital operations, and they too have decided to shift strategy to leverage our know-how in process and domain to be able to embed AI solutions by rapidly modernizing their processes that deliver AI-driven insights to improve cost, experience, and outcomes. Many of these deals incorporate non-FT-based commercial models, particularly transaction-based pricing, that aligns all our goals to drive rapid leverage of new technologies, including generative AI, machine learning, and LLMs. Data Tech AI services, where we design and build solutions to transform our clients' businesses, grew 6% on a constant currency basis. This was driven by ongoing momentum for our emerging services, including supply chain, sales and commercial, and risk. That collectively grew 9% partially offset by a slowdown in the discretionary portion of our shorter cycle advisory work as we had expected. Digital operations services where we digitally transform and run our client operations continue to deliver steady results in the first quarter, growing 3% on a constant currency basis. We have made great progress on all five of our initiatives to deliver our long-term goal of 10% plus organic top-line growth and expanding our AOI margin at a more meaningful pace than historical levels through 2026. First, revenue from our priority accounts grew 3% during the quarter and represented approximately 62% of total revenue. Despite seeing some near-term macro pressure, our investments in these clients are paying off. as the majority of our first quarter bookings were from our priority accounts. Second, we continue to deepen our relationships with our cloud technology partners, with whom we co-innovate and create joint IP and AI solutions. For example, with ServiceNow, we have embedded our domain and data depth to help transform and automate manual processes in areas such as procurement, accounts payable, and risk management. The strength of this partnership is evidenced by our co-sponsorship of ServiceNow's flagship event, Knowledge23, taking place next week, where we will present our procurement as a service offering. And with Canaxis, we have expanded our preferred partner status with capabilities in Europe and Asia to more effectively serve clients with critical supply chain solutions globally. Third, we're investing in new operating centers in Tier 3 cities particularly in India, giving us access to great talent pools. We have two centers fully operational and a third one getting ready for quarter three launch. Fourth, we continue to drive outcome and transaction-based commercial models that now represent 13% of total revenue on our path towards 20% by 2026. In fact, 28% of our bookings in quarter one had non-FTE pricing. And lastly, we've expanded our large deal team to take advantage of increasing number of large deal opportunities. And the results are showing in large deal bookings as well as pipeline strength in large deals. As expected, our attrition continues to drop, now at 24% during the first quarter. We saw this positive trend across the company at all levels, skill sets, and geographies. Adjusting for involuntary attrition and employees with less than three months of service our attrition was even lower at 19%. During the quarter, we hired 8,000 new team members across the globe. It is clear that the opportunity to learn new skills and solutions and work on digital generative AI and machine learning technologies in many of our client engagements is a talent attractor and is also driving attrition down. Now, let me step back and talk about the rapid evolution in the last five months of generative AI and why we believe we are one of the best positioned in our industry to take advantage of this next wave of AI. While AI has been in our DNA for years, generative AI and the recent breakthrough is an exciting next wave which will further leverage our capabilities. As we look back over the last five years, it is important to emphasize how central a role AI has played in our success with clients. Over these years, we have developed and refined our AI capabilities, enabling us to create innovative, industry-specific solutions for our clients. We believe this has positioned us as one of the leaders in the AI space in our industry, giving us a competitive advantage for long-term growth and margins. Some of the key milestones on this journey include the following. In March 2017, we made our big move into AI when we acquired Rage Frameworks that allowed us to bring natural language processing and natural language generation technologies into our services. This helped us launch our AI-driven solutions for financial services, using the technology to read financial statements that we then deployed in our loan processing operations and financial reporting services, delivering a 60% reduction in cycle time for loans and a 40% cost reduction. We then built and deployed AI-powered demand forecasting and inventory optimization solutions for the CPG sector, reducing stockouts and inventory holding costs. Three years back, we deployed AI-driven predictive maintenance solutions for a number of our large manufacturing clients where we run these operations, leading to a 30% reduction in maintenance costs and improved equipment effectiveness. We also created, at that time, our AI Center of Excellence, focused on driving innovation, talent development, and building new solutions with scaled industry partners. We then expanded our suite of AI solutions to include natural language understanding, NLU. This allowed us to have AI-powered customer service chatbot solutions for the banking, insurance, and the high-tech industries as part of our end-to-end services. This improved customer experience, drove up retention and renewal rates for our clients, as well as cross-sell and upsell for them. In every one of my 150-plus C-suite client conversations that I referenced earlier, we talked about generative AI and how all our clients are challenged with where to start, how to prioritize, what steps to take, and how to maximize value. The biggest realization for most enterprises is that their highly fragmented and distributed data sets and processes will prevent them from starting this journey. We saw the exact same thing happen when RPA and low-code workflow on the cloud became prime time seven years back. We embraced these technologies, built capabilities, and incorporated all of them into our services and operations. We now have close to 8,000 bots running in our operations and deployed by us on client sites. We also have more than 250 clients. whose operations run on Genpak's Quora platform, our AI cloud-based digital platform, that on the average handles more than 20 million transactions a month. We're now seeing the same co-innovation journeys in AI to consolidate processes and data, clean them up, standardize them, and then deliver services with these AI solutions built into them. This is clearly one of the big drivers for the surge in our inflows and bookings, The urgency all our clients have to get to the stage of being able to leverage these technologies to create value. They often need to fix their basics, their legacy technology processes and data in order to be able to leverage AI. Our differentiated value proposition as their transformation partner is built on five pillars of strength. First, domain expertise. Our deep understanding of various industries has allowed us to create industry-specific AI solutions that address unique challenges and understand all exceptions and edge cases. Second, scalable AI solutions. The AI solutions we develop can be easily adapted and scaled across different industries and functional areas. Third, continuous innovation. We believe that continuous and rapid innovation cycles are key to maintaining an AI and generating AI advantage. We invest consistently in R&D to ensure that we are constantly experimenting with AI and generating AI use cases with our clients. Fourth, talent development. Our AI center of excellence has a talented team of data scientists, engineers, and domain experts. And our three-year-old data bridge reskilling program had 70,000 people get certified last year. This provides the base talent pool to build our expertise in a talent short market. And finally, strategic partnerships. We have established strategic partnerships with leading technology providers to enhance our AI capabilities. Our domain process and data expertise make us a uniquely differentiated strategic partner for many of them. Let me share two specific examples of how these five pillars and our history have made us the partner of choice for finding ways to leverage AI. We built and deployed an AI-powered customer churn prediction model for a leading software as a service company. This model uses machine learning algorithms to analyze customer behavior data, product usage patterns, and other relevant factors to predict the likelihood of a customer churning. As a result, we identified at-risk customers and have now implemented targeted retention strategies in our operations, leading to a 30% reduction in churn and a significant increase in customer lifetime value for our clients. For another client, we went back to 10 years of customer sentiment data that was being captured to build a very powerful net promoter score prediction engine that we then used to to drive specific tailored marketing campaigns using generative AI to aid in customer service. For a global manufacturing company, we used AI-driven predictive analytics to generate more accurate revenue and expense forecasts as part of our FP&A services, considering various internal and external factors such as market trends, economic indicators, and historical financial data. This improved accuracy enables the company to make better informed strategic decisions, optimize resource allocation, and ultimately achieve a 25% reduction in forecast errors, leading to increased operational efficiency and financial performance. We are still in the early days of this current wave of use cases using generative AI and are in rapid prototype and experimentation mode with our clients. The initial wave of opportunities are concentrated in help desks, customer service, and research work, particularly in unregulated industries. As we have demonstrated with technologies such as RPA, dynamic workflows, and even earlier iterations of AI, every technology wave expands our total addressable market and allows us to do more complex work for our clients. With that, let me turn the call over to Mike for a detailed review of our first quarter results.