Verisk Analytics, Inc. VRSK

Revenue Intelligence Report • 17 quarters of SEC filing data • Updated 2026-10-14 • Data through 2026-03-31

Verisk Analytics, Inc.'s latest quarterly revenue is $783M for the period ending 2026-03-31. The model projects $3.2B across the next four quarters (+2.9% versus the preceding four quarters). The forecast uses SG&A data; model selection and estimation exclude the latest quarter, whose retrospective holdout error is 0.4%. These are statistical associations, not estimates of the causal effect of spending.

Investment Thesis

The ARDL forecast is based on reported revenue and SG&A data through 2026-03-31. Training MAPE measures fit to historical data; the separately reported holdout error measures a withheld quarter. Spending coefficients describe associations and do not establish causation.

Next 4 Quarters
$3.19B
+2.9% YoY
SG&A Elasticity
-2.42x
Training Fit
0.8% MAPE
Retrospective holdout (Q1 FY2026): The model predicted $786.0M vs the actual $782.6M — an error of 0.4%.
Retrospective one-quarter holdout: model fitting and selection exclude this quarter. Historical inputs use the latest available restatements, so this is not a preserved real-time forecast.
⚠ Model limitation: One or more estimated spending associations are negative. These observational coefficients do not establish a causal return on spending.
Note: Verisk Analytics, Inc. does not report R&D expenses separately. The model uses the available expense measure without a separate R&D term.

Revenue Forecast

VRSK Revenue Forecast

Quarterly Detail

QuarterModel ForecastActual95% RangeYoY GrowthStatus
Q1 FY2026
Period end 2026-03-31		 $786.0M $782.6M $770.3M–$802.0M +4.4% ✓ In range
Q2 FY2026
Period end 2026-06-30		 $795.4M $773.1M–$818.4M +3.0%
Q3 FY2026
Period end 2026-09-30		 $802.9M $775.4M–$831.4M +4.5%
Q4 FY2026
Period end 2026-12-31		 $796.7M $765.3M–$829.5M +2.3%
Q1 FY2027
Period end 2027-03-31		 $795.6M $760.6M–$832.3M +1.7%

Seasonal Factors

Multiplicative seasonal adjustment: These factors capture Verisk Analytics, Inc.'s systematic quarterly revenue patterns relative to the trend model. A factor of 1.05 means that quarter typically runs 5% above the underlying trend; 0.95 means 5% below. Factors are computed as the median of (actual / fitted) across all available quarters.
Fiscal QuarterSeasonal Factorvs TrendInterpretationObs.
FQ1 (Jan–Mar) 1.0078 +0.8% In line with trend 3
FQ2 (Apr–Jun) 1.0053 +0.5% In line with trend 3
FQ3 (Jul–Sep) 0.9921 -0.8% In line with trend 4
FQ4 (Oct–Dec) 1.0006 +0.1% In line with trend 4

Spending and Revenue

VRSK Spending Timing
Reading this chart: Each line shows the cumulative revenue association with a 1% change in spending over subsequent quarters. These estimates describe historical associations and do not establish causation.

Time-Varying Spending Associations

Time-varying analysis: A penalized spline model (GAM) tracks the association between log spending and log revenue over 17 quarters. Its coefficients describe conditional historical associations, not causal returns on spending.
Current SG&A elasticity: -0.1639x
The model-term chart shows relative absolute term magnitudes. Its percentages are not shares of revenue or causal contributions to growth.

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Data sourced from SEC EDGAR XBRL filings. SEC source data. Forecast model: ARDL; spending associations: ARDL (log-log) with 17 quarters. This analysis is for informational purposes only and does not constitute investment advice.

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