Q3 2026 Science Applications International Corp Earnings Call Transcript
Key Points
- SAIC's acquisition of Silveredge is expected to enhance AI capabilities and contribute to revenue and EPS growth.
- The company reported strong adjusted EBITDA of $185 million with a margin of 9.9%, driven by strong program execution.
- SAIC's book-to-bill ratio was 1.2x, indicating a healthy pipeline of future business.
- The company plans to reinvest $100 million in annual savings into higher ROI areas to drive growth and improve margins.
- SAIC increased its FY26 adjusted EPS guidance by $0.40 due to strong earnings and a lower tax rate.
- Third-quarter revenue declined by 5.6% year-over-year, partly due to the government shutdown.
- The company faces challenges in converting its legacy of innovation into revenue and EBITDA growth.
- SAIC's Civil segment experienced a 7% year-over-year decline in the quarter.
- The government shutdown slowed the pace of proposal submissions, impacting business development activities.
- There is ongoing pressure on civilian agency budgets, which could impact future growth opportunities.
Good day, and thank you for standing by. Welcome to the SAIC fiscal year 2026 Q3 earnings conference call. (Operator Instructions) Please be advised that today's conference is being recorded. I would now like to hand over to your speaker today, Joseph DeNardi, Senior Vice President, Investor Relations and Treasurer. Please go ahead.
Good morning and thank you for joining SAIC's third-quarter fiscal year 2026 earnings call. My name is Joe DeNardi, Senior Vice President of Investor Relations and Treasurer. And joining me today to discuss our business and financial results are Jim Reagan, our Interim Chief Executive Officer; and Prabu Natarajan, our Chief Financial Officer.
Today, we will discuss our results for the third-quarter of fiscal year 2026 that ended October 31, 2025. Please note that we may make forward-looking statements on today's call that are subject to known and unknown risks and uncertainties that could cause actual results to differ materially
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