MoatScan Methodology
A systematic framework for analyzing competitive moats, validating financial health, and assessing current price conditions across three time horizons — combining time-tested investment principles with modern AI-augmented research capabilities.
The 5-Pillar Moat Framework
Our moat analysis is grounded in the competitive advantage framework pioneered by legendary value investors. Rather than relying on subjective opinions or random AI outputs, every analysis evaluates a company through five distinct strategic pillars:
Network Effects
Does the product or service become more valuable as more users join? Examines direct and indirect network effects, platform dynamics, and ecosystem lock-in.
Switching Costs
How difficult or expensive is it for customers to switch to a competitor? Considers financial, operational, procedural, and relational switching barriers.
Intangible Assets
What non-physical assets create a competitive edge? Analyzes brand strength, intellectual property, regulatory advantages, and proprietary data.
Cost Advantages
Can the company deliver products or services at a structurally lower cost? Evaluates economies of scale, process advantages, unique resources, and proprietary technology.
Efficient Scale
Does the market structure limit viable competitors? Assesses niche market dynamics, infrastructure requirements, and barriers to new entrants in concentrated industries where serving the market efficiently requires only 1-2 players.
The 6-Dimension Financial Analysis
Alongside the moat framework, MoatScan analyses a company's fundamental financial health across six dimensions — each sourced from live financial data and assessed independently by AI to produce structured insights and a rating.
Income Statement
Revenue growth, profitability trends, and margin evolution across fiscal years and trailing twelve months (TTM).
Balance Sheet
Asset base, liability structure, liquidity position, and balance sheet strength over time.
Cash Flow
Operating cash flow, free cash flow generation, and capital allocation quality across reporting periods.
Key Ratios
Profitability ratios (ROE, ROA, ROIC, ROCE), leverage ratios, and liquidity ratios evaluated in historical context.
Forecast & Growth
Analyst consensus ratings, price targets, and multi-year forward estimates for revenue and EPS growth.
Valuation
AI-driven fair value estimate using the most appropriate model for the business (DCF, EV/EBITDA, P/E, DDM, P/FCF, or Sum-of-Parts), with margin of safety and valuation verdict.
Each of the first five dimensions (Income Statement through Forecast) receives an AI rating from 1–10. The Financial Score (10–100) is the sum of these five ratings multiplied by 2. The Valuation dimension runs sequentially after all five sections complete and produces a fair value estimate independently of the score.
Valuation model selection is AI-driven: DCF for asset-light, high-FCF businesses; EV/EBITDA for capital-intensive or cyclical industries; P/E for mature, stable earners; DDM for dividend-paying companies; P/FCF when GAAP earnings are distorted by D&A or SBC; Sum-of-Parts for conglomerates with separable business units.
The Three-Horizon Technical Analysis
The third pillar evaluates current price conditions across three distinct time horizons. Unlike the moat and financial analyses, technical results are always-fresh — never cached globally — reflecting the real-time nature of price action. Each run fetches the latest market data, recomputes all indicators, and generates a new AI verdict.
Short Term
1–4 weeks
Price vs 20-day and 50-day MA, RSI(14) with interpretation, MACD trend, Bollinger Band position, and volume trend. Support & resistance derived from MA20 and MA50 anchors.
Medium Term
1–6 months
Price vs 50-day and 200-day MA, 52-week range position, trend direction (Uptrend / Downtrend / Sideways), Golden/Death Cross signal, and relative volume. Support & resistance from MA50 and MA200 anchors.
Long Term
6 months+
Price vs 200-day MA, 52-week high and low, distance from 52-week high, Bollinger Band bandwidth (volatility), and recent crossover detection. Support & resistance from MA200 and 52-week extremes.
Understanding Scores & Ratings
Moat Ratings
The Moat Type is an independent qualitative judgment made by the AI — it is not derived from the Moat Score. Instead, it reflects a structural assessment of the durability and defensibility of the company's competitive advantage. The three categories are:
Little to no sustainable competitive advantage. The company operates in a highly competitive market with few structural barriers protecting its position.
Moderate competitive advantages that provide some protection but could be challenged by well-resourced competitors over a 10–20 year horizon.
Strong, durable competitive advantages that are difficult to replicate. The company has structural protections that should endure for 20+ years.
Because the Moat Type is assessed independently, it may diverge from the Moat Score. For example, a company may score moderately on individual pillars yet still earn a Wide Moat if its structural advantages are exceptionally durable — or vice versa. The AI's executive summary will note any meaningful divergence.
Management Verdicts
The Management Verdict is an independent qualitative assessment of leadership quality — not derived from the Moat Score or pillar ratings. It evaluates the management team's track record, capital allocation discipline, and governance based on web-verified evidence.
Proven capital allocators with long track records of compounding value; strong insider alignment; visionary leadership.
Above-average management with clear evidence of disciplined capital allocation and shareholder alignment.
No major red flags but no standout track record either; adequate stewardship of the business.
Evidence of value-destructive decisions, poor capital allocation, or governance concerns.
Actively value-destructive management; major red flags or governance failures.
Financial Score
The Financial Score (10–100) is the sum of the five section ratings (Income Statement, Balance Sheet, Cash Flow, Key Ratios, Forecast) multiplied by 2. Higher scores reflect stronger overall financial health across all dimensions.
Strong financial health. Solid performance across most or all dimensions.
Moderate financial health. Mixed results — some strong areas offset by weaknesses.
Weak financial health. Significant concerns across multiple dimensions.
Technical Verdicts
Each time horizon receives an independent AI verdict based on the indicator set for that horizon. Verdicts are not scores — they are qualitative assessments of the current price condition. A stock can simultaneously be Very Bearish short-term and Bullish long-term.
Strong alignment of positive indicators. Momentum and trend both favourable across the horizon.
Moderately positive signals. More indicators are supportive than cautionary.
Mixed or inconclusive signals. No clear directional edge in either direction.
Moderately negative signals. More indicators are cautionary than supportive.
Strong alignment of negative indicators. Momentum and trend both unfavourable.
The Role of AI: Assistant, Not Oracle
MoatScan uses Google's Gemini 2.5-Flash model as an analytical assistant—a tool to process and synthesize information at scale, not a crystal ball for predicting stock prices or making investment decisions.
Instead of manually sifting through hundreds of articles, reports, and financial statements, the AI gathers and analyses information in minutes.
Every moat analysis follows the same five-pillar structure; every financial analysis follows the same six-dimension structure; every technical analysis follows the same three-horizon structure — ensuring systematic and comparable assessments across companies.
The AI provides structured insights based on current information. You interpret those insights within your own investment philosophy and risk tolerance.
What AI does NOT do: It does not guarantee stock price predictions, provide personalised buy/sell advice, or replace professional financial analysis. Fair value estimates are model-based research outputs — not guaranteed outcomes. Technical verdicts are pattern-based research aids — not trading signals. AI analyses current competitive positioning, financial health, and price conditions using structured frameworks and pre-computed data.
Educational Research, Not Investment Advice
MoatScan is designed as an educational tool for learning about competitive strategy and financial analysis. It is not a financial advisor, portfolio manager, or stock picker.
All analyses are AI-generated interpretations based on publicly available information and are subject to errors, biases, and limitations.
Past performance and current competitive advantages do not guarantee future results. Markets are dynamic and moats can erode.
Technical verdicts and support/resistance levels are AI-generated research aids — not trading signals or entry/exit recommendations. Price levels are computed from moving averages and historical extremes, not predictive targets.
You are solely responsible for your investment decisions. Always consult with a qualified financial professional before making investment choices.
MoatScan does not receive compensation from any companies analyzed and does not make any claims about the investment suitability of any security.
By using MoatScan, you understand that this is a research framework designed to organize and present competitive, financial, and technical analysis — not a substitute for your own due diligence, professional advice, or independent judgment.