3 Stocks to Consider From the Booming Business Information Industry

Zacks identifies FactSet, Verisk and TransUnion as beneficiaries of AI-enabled proprietary data, subscription platforms and rising demand for fraud, credit and insurance-risk analytics. FactSet's fiscal Q2 2026 annual subscription value rose 6.7% year over year with retention above 95%; its fiscal 2026 EPS consensus increased slightly to $17.77, while Verisk's 2026 estimate rose to $7.71 and TransUnion's rose 1.5% to $4.84. The industry trades at 17.67x forward P/E, below the S&P 500's 19.76x, but has fallen 13% over the past year versus a 15.2% S&P 500 gain, highlighting competitive, macroeconomic and data-privacy risks.

Analysis

The investable distinction is not "AI exposure" but bargaining power over proprietary data and embedded workflows. VRSK has the cleanest monetization path: insurance customers face regulatory and loss-cost pressures that make analytics spend defensive, while standardized industry datasets are difficult to replicate with general-purpose models. FDS is more exposed to seat rationalization at asset managers; AI can lift product value, but also enables clients to challenge terminal pricing unless adoption converts into higher wallet share rather than merely better retention.

TRU offers the highest operating leverage to a credit-volume recovery over the next 6-18 months, but that cyclicality makes it a less pure data-platform compounder. A reacceleration in originations would improve transaction revenue and fraud/identity attach rates simultaneously; conversely, worsening consumer delinquencies can cause lenders to tighten underwriting and reduce inquiry volumes despite heightened demand for risk tools. The more relevant competitive threat is not NVDA or hyperscalers directly, but customers building thin AI layers atop cheaper alternative data and reducing the premium paid for undifferentiated interfaces.

Near term, this is unlikely to be a standalone catalyst: modest estimate revisions and generic AI positioning rarely sustain a rerating. The contrarian opportunity is selective because the group trades near the low end of its own historical valuation range, but multiple expansion requires proof that AI products generate net revenue retention or pricing uplift after implementation costs. Watch quarterly organic recurring-revenue growth, net retention, and sales-and-marketing intensity rather than product announcements; a deceleration in either FDS ASV growth or VRSK price realization would falsify the quality-premium thesis.

Key Decisions for Investors

• Initiate a 6-12 month long VRSK / short TRU pair, sized beta-neutral: VRSK has more defensive recurring revenue and pricing power, while TRU retains greater consumer-credit sensitivity. Target 10-15% relative return; exit if TRU lending volumes accelerate materially while VRSK organic recurring growth falls below mid-single digits.
• Accumulate FDS only on post-earnings weakness or after evidence of AI-driven net new sales, not merely retention. Use a 9-12 month horizon and require ASV growth to reaccelerate above 7% with stable operating margin; otherwise treat the apparent valuation discount as a value trap from financial-services seat pressure.
• Use TRU as a tactical 3-6 month long only if mortgage, auto, and card originations turn upward concurrently; the relevant confirmation is rising credit inquiries and management guidance, not fraud-volume headlines. A 15-20% upside is plausible in a credit recovery, but stop risk is a renewed deterioration in charge-offs or lender tightening.
• Do not add direct longs in AMZN, GOOG, or NVDA on this theme. Their economic exposure is primarily indirect cloud/model consumption, whereas enterprise AI may also compress information-provider pricing; revisit only if disclosed workload growth or partner economics demonstrate incremental revenue.