FactSet Q3 revenue edges past estimates as institutional buy-side, wealth management clients drive growth

FactSet Research Systems

01/07/2026 12:13

Overview
US financial data provider's fiscal Q3 revenue rose 6.4%, slightly beating analyst expectations
Adjusted EPS for fiscal Q3 beat consensus, rising 6.1% yr/yr
Company returned $243 mln to shareholders in Q3 via buybacks and dividends

Outlook
FactSet reaffirms fiscal 2026 GAAP revenue guidance of $2.45 bln to $2.47 bln
Company expects fiscal 2026 organic ASV growth of $130 mln to $160 mln
FactSet sees fiscal 2026 adjusted diluted EPS of $17.25 to $17.75

Result Drivers
CLIENT DEMAND - Revenue growth driven by institutional buy-side and wealth management clients
AI ADOPTION - Broader adoption of AI products among top clients and new partnerships expanded AI-enabled workflows
HIGHER OPERATING EXPENSES - Margin decline attributed to higher employee compensation costs, including one-time charges and CEO compensation, and increased technology-related expenses

Company press release: ID:nGNX3BksHf

Key Details
Metric
Beat/Miss
Actual
Consensus Estimate
Q3 Revenue
Slight Beat*
$622.90 mln
$618.25 mln (13 Analysts)
Q3 Adjusted EPS
Beat
$4.53
$4.46 (16 Analysts)
Q3 EPS
 
$3.50
 
Q3 EBIT Margin
 
26.70%
 
*Applies to a deviation of less than 1%; not applicable for per-share numbers.

Analyst Coverage
The current average analyst rating on the shares is "hold" and the breakdown of recommendations is 3 "strong buy" or "buy", 11 "hold" and 6 "sell" or "strong sell"
The average consensus recommendation for the professional information services peer group is "buy."
Wall Street's median 12-month price target for Factset Research Systems Inc is $240.00, about 4.3% above its June 30 closing price of $230.08
The stock recently traded at 12 times the next 12-month earnings vs. a P/E of 12 three months ago

For questions concerning the data in this report, contact Estimates.Support@lseg.com. For any other questions or feedback, contact reuters.support@thomsonreuters.com.

(This story was created using Reuters automation and AI based on LSEG and company data. It was checked and edited by a Reuters journalist prior to publication.)