Service Corporation International (SCI) FY2025Q2 Earning Prediction
Service Corporation International (SCI) is set to release its earnings performance on 07/30 16:15:00 ET in After Hours trading. Consensus forecasts predict a revenue of 1.05B and an earnings per share (EPS) of 0.84 for the . With Intellectia's exclusive AI algorithms, users can predict whether the earnings will beat or miss expectations before the report drops. Leverage this powerful tool to strategize and position your trades ahead of the earnings release!
Earnings Surprise Analysis
SCI Transcript
The earnings call reflects strong financial performance, with increased cash flow guidance, revenue and margin growth, and a solid acquisition pipeline. The Q&A highlights confidence in sustaining growth trends and EPS targets. Despite some uncertainties in cremation growth and SCI Direct, the overall sentiment is positive due to strong financial metrics and strategic initiatives. The absence of negative factors such as guidance cuts or margin declines further supports a positive outlook.
SCI Slides
SCI Report
Frequently Asked Questions
What is the Service Corporation International FY2025Q2 Earnings Release Date and Time?
Service Corporation International (SCI) is scheduled to release its FY2025Q2 earnings report onJul 30, 2025, After Hours(approximately 4:00 PM ET). This timing allows investors to react during after-hours trading, with a conference call typically following shortly after.
What Are the Consensus Forecasts for Service Corporation International FY2025Q2 Revenue and EPS?
Analysts' consensus predicts 1.05B in revenue and an EPS of 0.84 for Service Corporation International's FY2025Q2.
What Does Intellectia's AI Predict for Service Corporation International FY2025Q2 Earnings?
Intellectia's exclusive AI algorithms forecast a forService Corporation International's FY2025Q2 earnings, with a prediction date of Jul 30, 2025. Service Corporation International
How Can I Use This Earnings Prediction to Trade SCI Stock?
Leverage Intellectia's AI forecast to position trades ahead of theJul 30, 2025 release—consider calls for a beat scenario or protective puts for misses. Focus on pre-market volatility, and use the scenario probabilities to build strategies around revenue and guidance updates.
How Accurate Is Intellectia's AI for Earnings Predictions Like Service Corporation International FY2025Q2?
Intellectia's predictions are backed by rigorous backtesting, showing a high hit rate for Beat and Miss calls compared to traditional analysis. While no forecast is 100% certain, we provide probability-based scenarios (e.g., 50% chance of a *Beat*) and detailed rationales to help you make informed decisions. Combine our insights with your strategy for the best results—it's like having a co-pilot for earnings season! Empowering users to strategize trades before reports drop.
How does AI Earnings Prediction generate its forecasts?
AI Earnings Prediction uses advanced Large Language Models (LLMs) to analyze a wealth of data, including past earnings transcripts, real-time market sentiment, analyst insights, and company news from the last three months. It focuses on key indicators like revenue, EPS, and margins to predict whether a company will *Beat*, *Miss*, or remain Neutral relative to market expectations. Think of it as a super-smart analyst crunching numbers and news 24/7 to give you a trading edge!
When are the predictions available, and how often are they updated?
Predictions are generated two days before a company’s earnings release (e.g., 5:00 PM ET on Feb 13 for a Feb 15 report) to capture the latest market and company data. They’re updated in real-time if significant news breaks, ensuring you get fresh insights.
Can I use AI Earnings Prediction for all types of stocks?
Currently, AI Earnings Prediction focuses on companies with market caps above $40 billion, covering major players like SPG, AAPL, MSFT, and NVDA for the 2025-2026 earnings seasons. We prioritize high-impact stocks with robust data to ensure reliable forecasts. Stay tuned as we expand coverage to more companies based on user demand!
