AI Earnings Analysis
EarningsMoat uses AI to analyze company financial statement data (balance sheet, income statement, cash flow) and delivers structured analysis across the three dimensions investors care about most: earnings quality, moat strength, and key risks.
It goes beyond telling you what happened — it helps you judge whether these earnings can stand the test of time. Covers US, China A-share, and Hong Kong markets.
AI Analyzes Financial Data
Automatically fetches financial statement data, AI computes key metrics and delivers professional analysis.
Three-Pillar Structured Output
Earnings quality, moat strength, and key risks — each with independent scoring and narrative.
Covers US / CN / HK Markets
Supports companies listed on NYSE, NASDAQ, Shanghai, Shenzhen, and HKEX.
Quality Scoring System
Quantify earnings quality with a multi-dimensional scoring system — no more relying on gut feeling.
How the AI earnings analysis works
This is for investors who want a structured read of a filing, not a short news summary. EarningsMoat starts from normalized financial statements and the source filing, then shows what matters for earnings quality, moat strength, capital allocation, and risk.
Core checks
- - Revenue, margin, cash flow, leverage, and return metrics are read together instead of as isolated headlines.
- - The model separates recurring operating performance from one-time gains, accounting noise, and balance-sheet strain.
- - Company-specific facts from the filing are used to explain why a score moved, not just whether the score is high or low.
What you get
- - A plain-English takeaway that explains the main research question.
- - Scores for quality, moat, capital allocation, and risks.
- - A report you can revisit, share, and compare with sector peers.
The analysis supports your research. It does not issue buy, sell, or price-target recommendations, and it should be checked against the original SEC filing before capital is committed.
Try It Now
Enter a ticker or company name to get AI earnings analysis in seconds.