Fair Isaac Corporation (FICO)
Quantitative Summary
DeterministicAt 39.7x earnings — a 39% discount to the sector average of 65.0x — FICO is in the lower valuation range. Financial health metrics are strong: Piotroski 7/9, Altman Z 9.7 (above 3.0 safe zone threshold). DCF fair value of $121 implies 88% downside based on model assumptions.
Generated deterministically from quant metrics and financial statements. Not a recommendation.
Algorithmic Teardown
AI-GeneratedThe company exhibits a profound disconnect between its operational efficiency and capital structure, characterized by an exceptionally high ROIC of 72.6% contrasted against a negative DuPont-decomposed ROE of -37.3%. This anomaly stems entirely from the equity multiplier of -1.07x, indicating substantial net debt or other liabilities that invert the return on equity despite robust profitability metrics like a 32.8% net margin and an impressive Piotroski F-Score of 7/9. The Beneish M-Score of -2.67 further reinforces earnings quality, while revenue growth remains healthy at 15.9%, suggesting strong underlying demand that is being mechanically obscured by leverage rather than operational weakness.
Valuation analysis reveals a significant divergence between market pricing and intrinsic value models. Trading at a P/E multiple of 40.3x against a sector average of 57.8x, the stock appears relatively undervalued relative to peers; however, this perception conflicts sharply with a DCF fair value calculation implying an -88% downside from current levels. This discrepancy suggests the market is pricing in extremely aggressive future assumptions, reflected in an implied free cash flow growth rate of 37.7% over ten years, which may be difficult to sustain given the weak profitability factor (RMW) score of -0.260.
Risk assessment highlights conflicting signals regarding momentum and insider sentiment. While the Fama-French alpha stands at a robust 10.38%, indicating strong risk-adjusted performance independent of market style factors, recent insider activity shows $1,125,248 in net selling over ninety days. This outflow from management could signal caution regarding near-term execution or valuation levels, creating a tension between the stock's historical factor-based strength and current internal positioning that investors must weigh against the stark DCF implications.
Generated by LLM from quantitative data inputs. May contain inaccuracies. Not investment advice.
DCF Sandbox
Interactive5-year two-stage DCF. Terminal growth 3%. Default sliders match the pre-computed base case. Drag to explore scenarios. Not investment advice.
The growth rate the market implicitly expects over the next 10 years to justify today's price. Compare with historical growth of 16% YoY revenue.
Sensitivity Matrix
| TG ↓ / WACC → | 10.2% | 12.2% | 14.2% |
|---|---|---|---|
| 2% | $145 | $109 | $85 |
| 3% | $164 | $121 | $92 |
| 4% | $189 | $134 | $101 |
Center = base case. Green = >10% upside, Red = >10% downside vs $1251.63.
Pre-computed DCF: WACC=12.3%, terminal growth 3%. Fair value $121 (-88.0%). Not investment advice.
Valuation Context
Currently trading 70% below its 5-year average P/E of 114.8x.
Price Chart with Moving Averages
Technical Setup
AI GeneratedFair Isaac Corporation's current trading price of $1228.10 establishes a specific context within its broader technical envelope, though the immediate position relative to the Short-Term Moving Average remains undefined in this isolated dataset. Without visibility into where the long-term trend lines sit or how far the stock has deviated from these averages over recent sessions, assessing mean-reversion potential requires inferring that any significant distance from a central tendency would typically invite corrective movement toward equilibrium. In relative-value terms, if the price is trading above an established upper boundary of a standard moving average band, it may suggest extended momentum rather than an immediate pullback opportunity; conversely, positioning below such boundaries could imply oversold conditions ripe for stabilization. The absence of specific envelope levels or volatility metrics prevents a definitive calculation of whether this $1228.10 mark represents a statistical outlier or a consolidation point within normal price ranges. Ultimately, the technical narrative here hinges on unknown variables regarding recent trend strength and standard deviation widths. If historical data indicates that FICO frequently reverts to its mean after reaching such highs or lows, the current level might signal a high-probability zone for counter-trend activity. However, without knowing if this price is near a support floor or resistance ceiling defined by past moving averages, one cannot ascertain whether the market is in a state of exhaustion or acceleration. The synthesis suggests that while mean-reversion strategies are theoretically applicable when prices stray significantly from their central trends, confirming such a
Quant Health Deep Dive
Profitability & Value Creation
DuPont Analysis — ROE Decomposition
Breaking down Return on Equity to see how the company generates its ROE — efficiency, margins, or leverage.
Balance Sheet Health
Insider Activity (Last 90 Days)
Open-market buys vs sells by company insiders. Source: yfinance.
Earnings Surprise History
EPS estimates vs actuals for the most recent reported quarters. Source: yfinance.
Dividend History
| Date | Amount | Change |
|---|---|---|
| 2017-03-01 | $0.0200 | 0.0% |
| 2016-11-30 | $0.0200 | 0.0% |
| 2016-09-12 | $0.0200 | 0.0% |
| 2016-05-23 | $0.0200 | 0.0% |
| 2016-03-07 | $0.0200 | 0.0% |
| 2015-11-30 | $0.0200 | 0.0% |
| 2015-09-14 | $0.0200 | 0.0% |
| 2015-05-22 | $0.0200 | 0.0% |
| 2015-03-05 | $0.0200 | 0.0% |
| 2014-12-01 | $0.0200 | 0.0% |
| 2014-09-08 | $0.0200 | 0.0% |
| 2014-05-23 | $0.0200 | 0.0% |
Dividend and split data from SEC filings and market data. Amounts are per share, not adjusted for splits. Source: yfinance.
Risk Profile
Sharpe = risk-adjusted return (higher is better). Max drawdown = largest peak-to-trough decline. 1,200+ trading days.
Underwater (Drawdown from Peak)
How far below the all-time high the price has been over time. Deeper = more pain for holders.
Rolling 60-Day Beta vs S&P 500 (VOO)
How the stock's sensitivity to market moves changes over time. β > 1 = more volatile than the market.
Fama-French 5-Factor Exposure
Academic factor model decomposition — what's really driving this stock's returns.
Fama-French 5-Factor Model. Data: Kenneth French Data Library. Regression over 3 years of daily returns.
Fundamentals
Passive Flow Attribution
ETF Draft EffectWhen investors buy or sell ETFs like XSW or VOT, the fund manager is mechanically forced to buy or sell FICO shares regardless of Fair Isaac Corporation's individual fundamentals. We estimate $3.8B of passive capital is structurally linked to FICO through 8 tracked ETFs. Index rebalances and ETF creation/redemption cycles can create noticeable volume spikes unrelated to company news.
Passive exposure = Σ (ETF AUM × stock weight in ETF) across 8 tracked ETFs. Actual passive ownership is larger (includes mutual funds). Not investment advice.
ETF Contagion Visualizer
Simulate a price drop in Fair Isaac Corporation to visualize passive redemption contagion across ETFs and collateral stocks.
If Fair Isaac Corporation (FICO) experiences a significant drawdown, ETF redemptions can create collateral selling pressure on co-held stocks. Our model identifies NVIDIA CORP (NVDA) as the most exposed collateral stock, sharing 1 ETFs with FICO. This is the "Passive Contagion" effect described in the Inelastic Market Hypothesis.
Contagion model based on shared ETF exposure and constituent weights across 28 tracked ETFs. Estimated selling pressure is a simplified model — actual impact depends on market liquidity, ETF redemption mechanics, and market-maker activity.
FICO Ownership Dynamics
Passive funds hold 1 in every 6 FICO shares, reducing daily market volatility.
Fair Isaac Corporation (FICO) exerts notable gravity on the passive index market, currently representing 0.7% of the XSW (XSW) and 0.5% of the VOT (VOT). Across 28 tracked ETFs, approximately 4M shares (15.9% of float) are held by passive funds and rarely trade on the open market. This level of passive ownership means index rebalances can create outsized volume events.
ETFs with Highest FICO Exposure
Float lock-up computed from 28 ETFs tracked by SecuritiesDB. Actual passive ownership is higher (includes mutual funds, pension funds, etc.).
FICO Institutional Volume Profile
252-day volume distribution by price level. The Point of Control (POC) marks — the price where the most institutional volume transacted — an implicit support/resistance floor.
The highest-volume price zone for Fair Isaac Corporation over the past year sits near $1518.61 (13% of 252-day volume). The current price of $1251.63 sits 17.6% below the POC — suggesting potential mean-reversion upside if institutional demand reasserts at this level. The highly concentrated volume profile (13% at POC) indicates strong consensus on fair value — institutional participants have repeatedly transacted near this price.
Volume Profile computed from 252 trading days of OHLCV data. Volume allocated to price bins proportionally based on daily high-low range. Not investment advice.
FICO Capital Efficiency
How efficiently does Fair Isaac Corporation convert operating profits into free cash? The FCF Conversion ratio measures the gap between accounting earnings and real cash generation.
Fair Isaac Corporation converts 78% of its EBITDA into free cash flow, an exceptional conversion rate indicating an asset-light business model with minimal capital reinvestment drag. The positive ROIC-WACC spread of 60.3% confirms that reinvested capital creates shareholder value.
Capital efficiency = Free Cash Flow ÷ EBITDA. Reinvestment = (EBITDA − FCF) ÷ EBITDA. Metrics from latest annual filings. Not investment advice.
Fails-to-Deliver (FTD) History
SEC-reported settlement failures. Elevated FTDs can indicate high short-selling pressure, operational settlement issues, or naked shorting activity.
| Date | Failed Shares | Close Price | Notional Value |
|---|---|---|---|
| 2026-05-08 | 18 | $1128.39 | $20,311.02 |
| 2026-04-23 | 102 | $970.17 | $98,957.34 |
| 2026-04-22 | 4,380 | $1036.70 | $4.5M |
| 2026-04-14 | 56,456 | $1000.91 | $56.5M |
| 2026-04-13 | 68,899 | $922.37 | $63.6M |
| 2026-04-10 | 76 | $1072.35 | $81,498.6 |
| 2026-04-07 | 6,315 | $1094.32 | $6.9M |
| 2026-03-23 | 2 | $1127.62 | $2,255.24 |
| 2026-03-09 | 7,351 | $1476.00 | $10.9M |
| 2026-03-04 | 162 | $1448.02 | $234,579.24 |
| 2026-02-05 | 1,456 | $1386.88 | $2.0M |
| 2026-01-28 | 1,249 | $1545.00 | $1.9M |
| 2026-01-27 | 3,417 | $1550.74 | $5.3M |
| 2026-01-26 | 917 | $1544.69 | $1.4M |
| 2026-01-23 | 2 | $1556.95 | $3,113.9 |
| 2026-01-21 | 14,088 | $1494.50 | $21.1M |
| 2025-12-29 | 260 | $1753.19 | $455,829.4 |
| 2025-12-26 | 1,824 | $1731.01 | $3.2M |
| 2025-12-17 | 14,142 | $1792.13 | $25.3M |
| 2025-11-19 | 15 | $1724.97 | $25,874.55 |
| 2025-11-12 | 1,392 | $1797.69 | $2.5M |
| 2025-11-10 | 19 | $1740.00 | $33,060 |
| 2025-10-20 | 100 | $1616.00 | $161,600 |
| 2025-10-15 | 7 | $1649.51 | $11,546.57 |
| 2025-10-08 | 11,577 | $1879.55 | $21.8M |
| 2025-10-07 | 3 | $1850.18 | $5,550.54 |
Source: SEC Regulation SHO FTD data. Data is reported with a ~30 day delay. High FTD quantities relative to average daily volume may indicate settlement stress.
Price Correlations
Statistical correlation of daily returns with other stocks. High correlations indicate stocks that move together; negative correlations can offer diversification.
| Peer | 252-Day (1Y) | 126-Day (6M) | Direction |
|---|---|---|---|
| WTGXX | NaN | NaN | |
| ADSK | 0.391 | 0.506 | Moderate |
| ADP | 0.388 | 0.557 | Moderate |
| MCO | 0.387 | 0.469 | Moderate |
| PAYX | 0.358 | 0.532 | Moderate |
| NDAQ | 0.347 | 0.471 | Moderate |
| INTU | 0.341 | 0.497 | Moderate |
| GEN | 0.341 | 0.512 | Moderate |
| TOST | 0.339 | 0.452 | Moderate |
| VRTPX | 0.338 | 0.302 | Moderate |
Pearson correlation of daily log returns. 252d ≈ 1 trading year. Computed from price history. Not investment advice.
Compare FICO to Peers
Quant metrics computed deterministically from financial statements and price data. Updated: 2026-06-02.
SecuritiesDB provides programmatic data aggregation for informational purposes only. None of the metrics, summaries, or algorithmic flags constitute a recommendation to buy or sell any security.