Verisk Analytics Inc (VRSK) FY2025Q3 Earning Prediction
Verisk Analytics Inc (VRSK) is set to release its earnings performance on 10/29 07:15:00 ET in Pre-Market trading. Consensus forecasts predict a revenue of 776.24M and an earnings per share (EPS) of 1.69 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
VRSK Transcript
The earnings call summary and Q&A indicate a positive sentiment, with strong financial performance, strategic acquisitions, and innovation initiatives. The company raised guidance for 2025, completed significant acquisitions, and is embedding AI into its products. Despite some headwinds, the focus on M&A and shareholder returns is promising. However, management's lack of clarity on guidance reduction components slightly tempers the outlook. Overall, the stock price is likely to see a positive movement over the next two weeks, reflecting the company's strategic advancements and positive client feedback.
VRSK Report
Frequently Asked Questions
What is the Verisk Analytics Inc FY2025Q3 Earnings Release Date and Time?
Verisk Analytics Inc (VRSK) is scheduled to release its FY2025Q3 earnings report onOct 29, 2025, Pre-Market(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 Verisk Analytics Inc FY2025Q3 Revenue and EPS?
Analysts' consensus predicts 776.24M in revenue and an EPS of 1.69 for Verisk Analytics Inc's FY2025Q3.
What Does Intellectia's AI Predict for Verisk Analytics Inc FY2025Q3 Earnings?
Intellectia's exclusive AI algorithms forecast a forVerisk Analytics Inc's FY2025Q3 earnings, with a prediction date of Oct 29, 2025. Verisk Analytics Inc
How Can I Use This Earnings Prediction to Trade VRSK Stock?
Leverage Intellectia's AI forecast to position trades ahead of theOct 29, 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 Verisk Analytics Inc FY2025Q3?
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!
