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BR · Broadridge Financial Solutions, Inc.

Information Technology Services · mkt cap $17.9B · calls: Q3 FY2026 vs Q2 FY2026
54.0 conviction · conf-adj 54

conf 4/10 1-model

enthusiasm:24.0 · trend:8 · quantifies:0 · impact:0 · under_radar:5 · credibility:0 · business_impact:8 · disruption:0 · commitment:6 · confirmation:3

Enthusiasm latest 8 / prev 6 (rising)

Broadridge's AI story centers on three concrete wedges: an AI-native institutional proxy policy engine (new revenue, displacing proxy advisers), an AI-powered global demand model for asset managers, and internal/client-facing productivity via managed-services AI partnerships and faster SDLC. Management quantifies adoption and efficiency (25% productivity, $800B AUM, $120T tracked) and is investing more, but still frames most AI revenue upside qualitatively (~1 point of governance growth over several years). Credibility is moderate-to-strong on productivity and product rollout, weaker on near-term P&L attribution—management explicitly denies AI is causing sales delays or pricing pressure.

GROUNDED NEXT-FY IMPACT vs CONSENSUS

Grounded on actual base — revenue $6.9B · net income $0.8B · net margin 12.2% · diluted EPS 7.1

These are next-fiscal-year annual uplift estimates, not next-quarter numbers.

Aggregate next-FY est. rev uplift: % · next-FY EPS uplift: % · vs analysts: inline · priced in: medium (model's call-read: high; verdict above is the hard-data one used for ranking) · confidence: 4/10

ClaimFigureArithmeticNext-FY Rev %Next-FY EPS %
$800B AUM on AI-native custom voting-policy engine
engagement · soft		>$800B AUMAUM enabled is a SCALE/usage metric, not BR revenue. No fee/take-rate disclosed in any claim, so $800B*fee cannot be computed. Not convertible to next-FY revenue.
$120T global assets tracked by AI demand model
engagement · soft		$120T assets trackedAssets TRACKED, not assets billed. 'Fastest-growing product' but no product revenue or per-client fee disclosed → no $ base obtainable.
~24 asset-manager clients on demand model
engagement · soft		nearly 2 dozen, growingClient count, no per-client ARR disclosed → unconvertible.
Managed-services productivity +25%, line of sight to 50%
productivity · soft		25% -> 50% productivityReal bottom-line lever, but managed-services cost/headcount base is NOT disclosed in any claim. Productivity% != FTE cut and != $ saving without the labor base. after_tax_saving = saving*(1-0.21) is uncomputable. Illustratively, a hypothetical $20M after-tax saving would be ~2% of $1,005M adj NI — but the $ is not anchorable from inputs.
Shareholder-engagement / policy-engine TAM 'multi-$100M'
revenue · soft		multi-$100M marketTAM/market-size, not BR contracted revenue. 'Multi' is unanchored and the market is multi-year/whole-industry; BR's share and timing undisclosed → not next-FY revenue.
AI engagement adds 'up to a point of growth' to governance over a few years
revenue · soft		~1 pt of governance growth over a few yearsOnly revenue-mappable claim. Governance SEGMENT revenue is NOT disclosed in any input claim, so company-level conversion needs an invented base. Phasing: ~1pp spread over ~3 yrs = ~0.33pp/yr, applied only to the governance subsegment (a fraction of $6,889M) -> company-level well under ~0.3pp/yr. Base undisclosed -> left null per disclosed-base rule.

Assumptions: Tax 21%; EPS% would be sized off the adjusted base consensus uses (current-FY adj NI ~$1,005M / adj EPS $8.49), NOT GAAP $839.5M/$7.10. Incremental revenue would flow at current 12.2% net margin (the governance claim is mid-margin recurring, no software premium stated). Phasing: 'over the next few years' = ~3 yrs, so next-FY share of any multi-year claim is ~1/3. CRITICAL: none of the seven quantified claims supplies a disclosed dollar revenue OR cost base — $800B AUM and $120T are tracked/enabled scale metrics (not billed), ~24 clients is a count, 25%->50% is a productivity % with no labor-cost base, 'multi-$100M' is a TAM, and the '1 point' is on an undisclosed governance subsegment. So no claim is convertible to a hard $ next-FY figure; all marked soft. No supplier-side revenue (BR sells financial-ops software/services, not AI compute/chips).

Top line: AI shows up almost entirely as scale/usage proof points ($800B AUM on the policy engine, $120T assets tracked, ~24 demand-model clients) plus a 'multi-$100M' TAM. The only revenue-mappable claim is 'up to a point of growth to the governance business over the next few years.' But governance segment revenue is undisclosed in the inputs, and even on the generous reading (1pp phased over ~3 yrs on a subsegment of $6,889M) it nets to a fraction of a point of total revenue per year — immaterial next to consensus's already-embedded +7.9% (+$540M) FY26 revenue. est_rev_uplift_pct = null (no disclosed base to size against).

Bottom line: The genuine earnings lever is managed-services productivity rising 25% with line of sight to 50%. But no managed-services cost/headcount base is disclosed, and a productivity % is not a headcount cut, so no after-tax $ saving can be computed (after_tax = saving*0.79 is unanchored). For scale, an after-tax saving would need to reach ~$20M just to move adjusted EPS ~2% off the ~$1,005M adj-NI base — plausible directionally but not anchorable from the inputs. est_eps_uplift_pct = null.

[impact n/m (all claims soft/unanchored)] Consensus already builds in +7.9% FY26 revenue ($6,889M->$7,429M) and +12.4% FY26 adjusted EPS ($8.49->$9.54), then +4.6%/+8.9% in FY27. Those are robust growth rates that plausibly already capture BR's adopter-side AI efficiencies and the sub-1pt governance contribution — none of the quantified AI claims points to a hard next-FY uplift ABOVE that trajectory. The math gap is effectively zero because every AI claim lacks a disclosed revenue or cost base to size; the burden of proof to call this 'above consensus' is unmet. So: priced in, not the interesting under-priced case.

MODEL CONSENSUS (impact)

1-model  degraded to opus only

other model unavailable: cursor: ```json { "math": [ { "claim": "AI-native policy engine: $800B+ AUM enabled", "type": "engagement", "side": "adopter", "figure": "more than $800 billion AUM", "basi

QUANTIFICATIONS
AUM enabled by AI-native custom policy engine: more than $800 billion AUM (today / already live, topline)
“Today, that capability is already enabling asset managers with more than $800 billion AUM to implement their own voting policies without a proxy adviser.”
Assets tracked by AI-powered global demand model: $120 trillion in global assets (current, topline)
“One of our fastest-growing products is our AI-powered global demand model, which tracks $120 trillion in global assets and is assisting products and marketing decisions for nearly 2 dozen and growing leading asset managers.”
Asset-manager clients on global demand model: nearly 2 dozen and growing leading asset managers (current, topline)
“One of our fastest-growing products is our AI-powered global demand model, which tracks $120 trillion in global assets and is assisting products and marketing decisions for nearly 2 dozen and growing leading asset managers.”
Managed services productivity gain from AI: 25% increase in productivity (already realized, bottomline)
“And on the productivity side, our managed services business has already seen a 25% increase in productivity with line of sight to 50%.”
Managed services productivity target: line of sight to 50% (forward, bottomline)
“And on the productivity side, our managed services business has already seen a 25% increase in productivity with line of sight to 50%.”
Shareholder-engagement / AI policy-engine TAM: multi-$100 million market (medium-term opportunity, topline)
“But we think collectively this is a multi-$100 million market.”
Governance segment growth contribution from AI-enabled shareholder engagement: as much as a point of growth (over the next few years, topline)
“But we think collectively this could add, you know, as much as a point of growth to our governance business over the next few years.”
PAST (realized)
CURRENT (now)
FORWARD (guidance)
TRACK RECORD — PROMISE vs DELIVERY

—/100 (no quantified promises)   no-quantified-promises  6 calls reviewed

Across six calls Broadridge cites AI-enabled products (global demand modeling, GenAI/OpsGPT, AI-native voting policy engine) and reports adoption and productivity metrics, but management did not state numeric AI targets with explicit deadlines. Progress is described qualitatively or via backward-looking counts, so promise-versus-delivery cannot be scored.

PRICED-IN (REFINED)
MEDIUM

Est. revisions flat  ·  Fwd P/E 18.2  ·  EV/Sales 2.9x

AI claim maps to Recurring Fee Revenue, Distribution Revenue

Analyst rating counts improved modestly from early 2026 (more buys, fewer holds) but have been unchanged since March, while consensus price targets are flat month-over-quarter at ~183 yet well below the ~221 last-year average—so revisions are not clearly accelerating upward. Forward revenue/EPS growth is steady but not aggressive (~8% rev / ~12% EPS FY25–26, slowing thereafter), and at ~18.2x next-FY EPS and ~2.9x EV/Sales the stock looks fairly valued for a mature recurring franchise rather than AI-premium rich. AI-driven upside would most plausibly flow through Recurring Fee Revenue (and secondarily Distribution), where some steady-state growth is already in estimates without strong upward revision or target-raise momentum—hence partially reflected, not fully priced in nor clearly already captured.
COVERAGE — ENTHUSIASM TRAJECTORY + CATALYSTS
7Q2 FY20256Q3 FY20257Q4 FY20255Q1 FY20268Q2 FY20267Q3 FY2026

AI enthusiasm across 6 calls — trend ↗ rising

AI moved from named features to revenue-linked AI-native voting, with tokenization often overshadowing explicit AI detail.

RECENT AI CATALYSTS & NEWS
BUSINESS IMPACT - QUALITATIVE MATERIALITY

7/10 qualitative impact   material  medium-term · mixed evidence

Where AI matters: governance proxy voting, GTO analytics, managed-services productivity

Live AI-native policy engine ($800B+ AUM) and fastest-growing global demand model ($120T tracked, ~24 clients) are real product wedges, plus 25% managed-services productivity with a path to 50%, but disclosed revenue linkage is thin (~1pp governance growth over years, multi-$100M TAM) and nothing anchors company-level Rev/EPS uplift.

Caveats: Quantified AI metrics are scale/usage (AUM, assets tracked), not disclosed revenue or margin contribution; Managed-services AI partnerships with guaranteed savings may cap margin upside as productivity rises; Longer-term client build-vs-buy risk if agentic APIs commoditize parts of GTO despite current denial

AI DISRUPTION / CANNIBALIZATION RISK  tailwind · 2/10

Core economics are regulated, mission-critical infrastructure and recurring software/workflows at scale—not billable-hour labor arbitrage—where AI is being embedded to displace proxy advisers and sell new capabilities; mgmt reports no sales delays or pricing pressure, though managed-services savings-sharing is a watch item, not a model breaker.

OPTIONS / MARKET STRUCTURE

option liquidity: fair

ATM IV
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TYPICAL BID-ASK
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OPEN INTEREST
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proxy inputs — dollar-ADV $247M · beta 0.901 · px $154.83

source: proxy (no options chain on FMP)
FMP /stable/ exposes no options-chain endpoint on this key, so ATM IV, bid-ask spread and open interest are unavailable. Liquidity below is a PROXY from dollar-ADV, beta and price level (a stand-in for option depth), not measured option-market data.

CONFIRMATION — INSIDERS · 13F · LANGUAGE
Mixed — insiders selling, institutions adding, management language 7/10 committed.
INSIDERS selling 4 open-market sell(s) vs 1 buy(s) — net distribution
INSTITUTIONS (13F) adding as of 2026-03-31: 135 new / 215 closed positions; 567 increased / 314 reduced; institutional ownership +2.38pp; -76 net 13F holders
MGMT LANGUAGE 7/10 committed AI section uses firm present tense and $800B AUM; lighter hedge on scaling/building; transcript cuts off mid-example.
commit “Today, that capability is already enabling asset managers with more than $800 billion AUM”
commit “Our AI capabilities are powering new products, accelerating our software development cycle and driving productivity gains.”
commit “Our new custom policy engine, which is fully AI native, is able to read and analyze source materials”
VERBATIM AI QUOTES
“And we're using our strong free cash flow to return capital to shareholders even as we make tuck-in acquisitions that strengthen and extend our value proposition.”
— Timothy Gokey, Q3 FY2026
“Looking ahead, we're already investing in the next wave of industry innovation. Broadridge is transforming shareholder engagement, leading in tokenization, driving digitization and scaling our AI capabilities.”
— Timothy Gokey, Q3 FY2026
“Third, as I just said, we are taking active steps to address future growth opportunities by leading in tokenization, driving the digitization of communications and scaling AI.”
— Timothy Gokey, Q3 FY2026
“Finally, we're scaling AI by building on top of our common data ontology, shared API architecture and the operating workflows we already run at scale. Our AI capabilities are powering new products, accelerating our software development cycle and driving productivity gains.”
— Timothy Gokey, Q3 FY2026
“Our new custom policy engine, which is fully AI native, is able to read and analyze source materials and apply clients voting policies across thousands of companies.”
— Timothy Gokey, Q3 FY2026
“Today, that capability is already enabling asset managers with more than $800 billion AUM to implement their own voting policies without a proxy adviser.”
— Timothy Gokey, Q3 FY2026
“Now we're building on that progress to modernize the entire front-to-back workflow supporting institutional voting by leveraging agentic AI to enhance our core institutional voting platform.”
— Timothy Gokey, Q3 FY2026
“One of our fastest-growing products is our AI-powered global demand model, which tracks $120 trillion in global assets and is assisting products and marketing decisions for nearly 2 dozen and growing leading asset managers.”
— Timothy Gokey, Q3 FY2026
“And on the productivity side, our managed services business has already seen a 25% increase in productivity with line of sight to 50%.”
— Timothy Gokey, Q3 FY2026
“Going forward, we're extending our Broadridge platform to a growing number of core applications. This platform with its common data and APIs positions Broadridge to create agentic layer our clients can use directly or can leverage to create their own solutions using our embedded services.”
— Timothy Gokey, Q3 FY2026
“In sum, AI is enabling Broadridge to deliver new services, become more embedded in our clients' agentic workflows and drive our own productivity.”
— Timothy Gokey, Q3 FY2026
“Stepping back, we believe that each of tokenization, digitization and AI are growth drivers for Broadridge as we help our clients in our industry take advantage of the next wave of transformation in financial services.”
— Timothy Gokey, Q3 FY2026
“Since the beginning of calendar year '26, we have stepped up our level of investment in tokenization, AI and shareholder engagement initiatives.”
— Ashima Ghei, Q3 FY2026
“We're not seeing AI affecting things. It is -- and if anything, we're seeing interest in AI-enabled products that we do.”
— Timothy Gokey, Q3 FY2026
“But beyond that, we're seeing the benefit from organic product development beginning to bear fruit. I think we will see some benefit from the tuck-in M&A that we just talked about. And we're starting to see benefits from the ongoing investments in our go-to-market capabilities, especially international. So we like the demand going forward. We're not seeing AI or sort of self-builds taking over. And I think people are really liking our platform story, too, which becomes a sort of a build and buy where being able to leverage the agentic layer that we're creating.”
— Timothy Gokey, Q3 FY2026
“We haven't seen that yet. We are -- it is -- as we talked about, it is the improvements in SDLC are certainly helping us innovate faster and bring new products forward faster as you did with custom policy engine, the global demand model, the institutional voting platform, all of which are leveraging AI in the way they work, but also in how we develop them.”
— Timothy Gokey, Q3 FY2026
“I think the managed services one is interesting because there, it is -- we are -- as we talk to clients about that capability today, we're largely talking about AI partnerships. We'll do an AI partnership, we'll guarantee you a level of savings, and we'll share the savings above that. And it really changes the conversation because we're going into it together, their AI plus our AI and the APIs I talked about, and we can really create -- we've seen increases in demand as a result of that.”
— Timothy Gokey, Q3 FY2026
“And as we -- particularly as we think about the productivity from AI going forward and other things, it's really a matter of how do we get the right mix between investment and delivering to shareholders.”
— Timothy Gokey, Q3 FY2026
“And of course, AI is enabling all this at a faster pace.”
— Timothy C. Gokey, Q2 FY2026
“All enhanced by our platform and AI capabilities.”
— Timothy C. Gokey, Q2 FY2026
“We are also rolling out our AI-native policy engine and vote implementation capabilities for institutional investors like JPMorgan and Wells Fargo who are seeking to reduce their reliance on proxy advisers.”
— Timothy C. Gokey, Q2 FY2026
“This is a powerful example of how our AI capabilities are enabling new revenue.”
— Timothy C. Gokey, Q2 FY2026
“And we're leveraging our strong AI and platform capabilities to rapidly build these and other new solutions while improving productivity.”
— Timothy C. Gokey, Q2 FY2026
“With our deep domain knowledge and critical role at the intersection of financial services, AI will both expand Broadridge Financial Solutions, Inc.'s opportunities and drive efficiency improvements.”
— Timothy C. Gokey, Q2 FY2026
“Yeah. And look, we can do different things for different people. Sometimes it'll be the full AI-driven custom policy engine. Sometimes it'll be helping more on the vote execution side.”
— Timothy C. Gokey, Q2 FY2026
“But we think collectively this could add, you know, as much as a point of growth to our governance business over the next few years.”
— Timothy C. Gokey, Q2 FY2026
ANALYST QUESTIONS ON AI
Q (Q3 FY2026, Scott Wurtzel): And then just would love to hear more on the -- just the opportunity with the custom policy voting engine and just sort of the broader opportunity there? And how long could this potential tailwind from selling this into the market last for and impact closed sales over the medium to long term here?
A: Timothy Gokey: We see the custom policy voting engine as one of our most exciting areas... the asset manager we did this year is $800 billion under management, and we have a nice pipeline for next year... we would expect to have -- to be significantly ahead next year of where we are this year... over the next 3 years or so, you'll see some nice growth there.
Q (Q3 FY2026, Puneet Jain): So I wanted to ask about delays that you're seeing in closed sales. Is evolution of AI also contributing to those delays in any way as your clients take like build versus buy decisions? Does AI change any of those dynamics, specifically in GTO?
A: Timothy Gokey: We're not seeing AI affecting things. It is -- and if anything, we're seeing interest in AI-enabled products that we do... We're not seeing AI or sort of self-builds taking over... being able to leverage the agentic layer that we're creating.
Q (Q3 FY2026, Puneet Jain): And second, somewhat related to the first question, like as AI generates productivity in software development as well as in managed services expenses, are any of those dynamics driving any pricing pressure for you?
A: Timothy Gokey: We haven't seen that yet... the improvements in SDLC are certainly helping us innovate faster... custom policy engine, the global demand model, the institutional voting platform, all of which are leveraging AI in the way they work, but also in how we develop them... we're largely talking about AI partnerships. We'll do an AI partnership, we'll guarantee you a level of savings, and we'll share the savings above that... their AI plus our AI and the APIs I talked about... we've seen increases in demand as a result of that.
Q (Q2 FY2026, Alex Kramm): You mentioned JPMorgan. I think you hadn't disclosed that one before. And also Wells Fargo... Can you just talk a little bit more about what that means financially? I mean, is there a big pipeline behind the JPMorgan and Fargo's of the world? How do you view the TAM? How quickly do you think this can ramp?
A: Timothy C. Gokey: Sometimes it'll be the full AI-driven custom policy engine. Sometimes it'll be helping more on the vote execution side... we think collectively, this is a multi-$100 million market... collectively this could add, you know, as much as a point of growth to our governance business over the next few years.