ExlService Holdings, Inc. Q3 FY2024 earnings call

• Revenue growth: Third quarter revenue was $472 million, up 15% year-over-year, and adjusted EPS grew 16% to $0.44 per share. - Business segment performance: Analytics and Digital Operations and Solutions both saw growth, with various vertical segments like insurance, emerging, and healthcare also experiencing growth. - Data and AI strategy: Leveraging data modernization and AI implementation services, such as the insurance LLM and partnerships with Databricks. - Talent investment: Attracting top talent like Sanjay Joshi and Sarat Varanasi, and investing in employee training with nearly 1 million hours of training completed this year.

In the third quarter, EXL generated revenue of $472 million, up 15% year-over-year. Analytics segment delivered revenue of $204 million for the quarter, up 11% year-over-year and 5% sequentially. Digital Operations and Solutions business delivered revenue of $268 million, up 18% year-over-year and 5% sequentially. Insurance segment generated revenue of $157.6 million, an increase of 15.1% year-over-year and 5.2% sequentially. Emerging segment grew revenue 21.7% year-over-year and 2.8% sequentially to $80 million. Healthcare segment reported revenue of $30.5 million, growing 16.5% year-over-year and 8.5% sequentially.

• Full-year revenue is anticipated to be in the range of $1.825 billion to $1.835 billion, representing year-over-year growth of 12% to 13% on a reported basis and approximately 12% on a constant currency basis. - Adjusted EPS is expected to be in the range of $1.61 to $1.63, representing year-over-year growth of 13% to 14%. - Anticipates increased investments in data and AI in the fourth quarter similar to the pattern last year.

• General economic conditions. - Factors set forth in the company’s periodic reports and other documents filed with the SEC from time-to-time.

Q: Can you talk about the strategy for building proprietary AI models?

A: Our strategy is twofold: build proprietary AI models where we can create differentiation and stitch together appropriate balance of large language models, agenetic AI capabilities, etc. to optimize client benefit.

Q: How is the conviction and potential sustainability of elevated growth in Digital Ops assessed?

A: Demand environment is strong, pipeline is growing, number of large deals is increasing, and broad strength across industries is seen.

Q: How are you assessing the risk of change in conversion rates of larger deals for Digital Ops?

A: Conversion rates and win rates in large deals are similar to the rest of the portfolio, with fair traction in the pipeline.

Q: How much of the Analytics segment comes from services not offered three years ago?

A: The data analytics business is evolving rapidly with shifts to AI and complex analytical services, but specific breakdown of new vs old services is not externally shared.

Q: How is data used to train industry-specific LLMs like the Insurance LLM?

A: Use client-permissioned data, like claims-related data from insurance carriers, with expressed and written permission.

Q: What are the differentiators compared to competitors?

A: High customer satisfaction scores and early investment in analytics, digital, and building market-relevant capability.

Q: Refinement of growth elements in Digital Ops?

A: Digital revenue includes stand-alone digital solutions and integrated digital operations work, with clients gravitating towards value delivery.

Q: Volatility in margins?

A: Quarter-to-quarter volatility, but annual margin trajectory is expected to incrementally build.

Q: M&A pipeline and capital allocation?

A: Selective M&A based on strategic value, and balanced capital allocation between M&A and share repurchase, with $185 million allocated for share repurchase this year.