Moody's: when accepted judgment becomes financial infrastructure

Executive summary

Moody's is best understood not merely as a producer of credit opinions or financial data, but as part of the institutional machinery through which risk becomes legible. Its two segments occupy different positions in that machinery:

• Moody's Investors Service, or MIS, publishes credit ratings and provides assessment services for debt obligations, programs, facilities, and issuers.
• Moody's Analytics, or MA, supplies research, curated data, analytical tools, and decision solutions used to identify, measure, monitor, and manage risk.

According to Moody's, its approximately 16,000 employees operate across more than 40 countries, MIS has more than 115 years of operating history, and the company's offerings draw on proprietary and curated data, validated models, and domain expertise.¹

Those are facts reported by management. The investment interpretation is that Moody's potential bottleneck is not raw data alone. Data can proliferate. Models can be copied or improved. The scarcer asset is an assessment that institutions are prepared to recognize, communicate, and insert into consequential workflows.

That distinction matters. Moody's strongest possible advantages reinforce one another:

1. a long-established reputation for credit analysis;
2. accumulated data and analytical processes;
3. regulatory experience and institutional acceptance;
4. integration into customer risk workflows; and
5. cash generation that can fund continued product development and reduce the diluted share count.

The available financial series supports the presence of a strong cash-generating business. From 2016 through 2025, net income rose from $266.6 million to $2.459 billion, operating cash flow rose from $1.259 billion to $2.901 billion, and weighted-average diluted shares declined from 195.4 million to 179.9 million. The path was not smooth: net income and cash flow both fell materially in 2022 before recovering to new highs by 2025.²

The evidence packet does not contain a current share price, enterprise value, debt schedule, capital-expenditure history, complete segment economics, or a verified management-ownership table. It therefore supports publication of a durable business-quality analysis, but not a valuation-based buy or sell conclusion.

The central thesis is:

Moody's may possess standards-like power because its judgments, data, and analytical conventions help multiple institutions describe risk in a common language. But regulatory exposure is not itself a moat, and history is not proof of future relevance. The durability of the franchise depends on preserving trust while embedding its intelligence more deeply into customer decisions.

What Moody's actually sells

Packet-supported facts

Moody's reports two segments:

Segment	Reported function
Moody's Investors Service	Publishes credit ratings and provides assessment services covering issuers and a wide range of debt obligations, programs, facilities, and structured securities
Moody's Analytics	Provides research and insights, data and information, and decision solutions across areas including credit, market, financial-crime, supply-chain, catastrophe, and climate risk

The company identifies banks, insurers, investors, corporations, governments, and public-sector organizations among the users of its offerings. Management describes these offerings as supporting activities such as issuing, underwriting, selecting investments, monitoring risk, compliance, planning, and reporting.¹

The packet does not provide the contractual revenue model, customer concentration, recurring-revenue percentage, retention rate, price realization, or complete segment revenue and margin tables. Claims about subscription economics, issuer-paid ratings, or customer concentration should therefore be tested against the full filing before being treated as established facts.

Interpretation

At a functional level, Moody's converts messy information into institutional decisions:

1. Collect and curate information. Moody's assembles proprietary and third-party data concerning companies, securities, properties, people, economies, and other risk domains.
2. Apply models and judgment. Data is processed through analytical models, taxonomies, and domain expertise.
3. Produce decision-ready outputs. Outputs include ratings, research, data products, and risk-management tools.
4. Enter customer workflows. Customers use those outputs in lending, underwriting, investing, monitoring, compliance, and reporting.
5. Accumulate procedural credibility. Continued use generates operating experience and reinforces institutional familiarity—provided that the outputs remain credible.

This makes the output more valuable than an isolated prediction. A credit judgment becomes economically important when multiple parties can understand it, use it consistently, and defend its use inside regulated or high-consequence processes.

Industry mechanics: where the bottleneck sits

The credit-ratings and risk-analytics value chain can be separated into four layers.

1. Information

Financial statements, security terms, ownership records, economic data, payment histories, and other risk indicators are inputs. More information is available than ever, and artificial intelligence can make unstructured information easier to process.

Raw information is therefore unlikely to be the only durable bottleneck.

2. Analytical transformation

Models, methodologies, taxonomies, and experienced analysts transform information into estimates of creditworthiness or other forms of decision intelligence.

The packet supports Moody's claim that it owns proprietary and curated data and validated analytical models. It does not quantify their accuracy advantage, uniqueness, or replacement cost.¹

3. Institutional acceptance

A technically excellent model has limited value if investment committees, risk officers, regulators, counterparties, and auditors will not recognize or accept its output. Established ratings and risk conventions can function as a common language among parties that otherwise possess different information and incentives.

This is the likely bottleneck, but it remains an interpretation. The filing excerpt establishes that MIS serves a key role in global debt markets and that Moody's is extensively regulated; it does not establish that any particular regulation requires customers to use Moody's products.¹

4. Workflow integration

An accepted assessment becomes more durable when it is embedded in lending, underwriting, monitoring, compliance, planning, or reporting. Moody's explicitly describes its intelligence as being inserted into customer workflows.¹

Workflow integration can raise the practical cost of replacement even when the underlying data is available elsewhere. Replacement may require remapping data, recalibrating thresholds, rewriting policies, retraining employees, and satisfying internal or external reviewers.

The bottleneck conclusion

Moody's likely sits closest to a bottleneck where analytical judgment becomes institutionally usable. That is stronger than simply owning a database, but it is also fragile in a particular way: the system works only while users trust the judgment and continue to treat its format as relevant.

A physical toll bridge can survive angry customers. A trust-based toll bridge cannot survive the widespread belief that its measurements are no longer useful.

Business model and economics

Two related but distinct economic engines

MIS and MA appear to reinforce each other, but they should not be treated as identical businesses.

• MIS produces ratings, assessments, research, and risk analysis connected to global debt markets.
• MA supplies data, research, analytical tools, and decision solutions across a broader set of customer workflows.

The combination potentially allows Moody's to participate at two levels: the shared language used to communicate credit risk and the operating systems used to manage risk internally.

That potential interaction is strategically important, but the packet does not provide enough product-level evidence to prove that MIS data systematically improves MA retention or that MA distribution increases MIS demand. The cross-segment flywheel should remain a hypothesis until supported by customer, retention, and segment data.

Cash generation

The SEC-derived series shows consistently positive operating cash flow from 2016 through 2025. Operating cash flow exceeded net income in every year shown except 2017 and 2021. In 2025, Moody's reported $2.901 billion of operating cash flow and $2.459 billion of net income.²

This is evidence of substantial cash generation. It is not, by itself, proof of free-cash-flow conversion because the packet does not include capital expenditures.

Capital intensity

The original research prompt identifies low capital intensity as a possible strength. The available evidence is directionally compatible with that hypothesis: Moody's describes a business built around data, research, models, software, and professional expertise rather than physical production.

The packet nevertheless lacks the capital-expenditure, property-and-equipment, capitalized-software, and acquisition-spending series required to quantify capital intensity. It would be premature to publish a precise free-cash-flow margin or return-on-invested-capital estimate.

Share count

Weighted-average diluted shares declined from 195.4 million in 2016 to 179.9 million in 2025.²

That is favorable for per-share economics, but the evidence does not reveal gross repurchases, equity issuance, stock-based compensation, or the prices paid for repurchased shares. A falling share count demonstrates reduced net dilution; it does not establish that every repurchase created value.

Balance-sheet development

Reported stockholders' equity moved from negative $1.225 billion in 2016 to positive $4.054 billion in 2025. Over the same period, assets increased from $5.327 billion to $15.830 billion, while year-end cash moved from $2.052 billion to $2.384 billion.²

The packet does not include the corresponding debt, goodwill, acquired-intangible, or lease-liability series. The increase in assets therefore cannot be cleanly separated into organic investment, acquisitions, cash accumulation, or accounting effects.

Does Moody's possess standards power?

“Standards power” is not one of Hamilton Helmer's canonical Seven Powers. It is a useful adjacent concept: a company gains influence when its language, classifications, or measurements become a default coordination mechanism for an industry.

Moody's plausibly exhibits three elements of standards-like power:

1. Common vocabulary. Ratings and risk classifications let market participants communicate judgments in a compact form.
2. Institutional familiarity. MIS has operated for more than 115 years, creating familiarity with its methodologies and outputs.¹
3. Workflow propagation. Moody's says its intelligence supports lending, underwriting, investment, monitoring, compliance, and reporting workflows.¹

But three distinctions are essential.

Regulation is not the same as regulatory dependence

Moody's reports that it is extensively regulated in the United States and foreign jurisdictions and that the applicable rules are complex and continue to evolve.¹ This proves regulatory exposure. It does not prove that regulation guarantees demand for Moody's services.

Regulation can strengthen a trusted incumbent by increasing compliance costs and institutional conservatism. It can also impose liability, constrain methods, encourage alternatives, or deliberately reduce reliance on incumbent ratings.

Usage is not the same as indispensability

A product may be widely used because it is familiar, not because alternatives are impossible. The real test is what breaks when a customer removes it:

• Does a regulatory or contractual requirement fail?
• Must an internal policy be rewritten?
• Does a risk model require recalibration?
• Do counterparties stop recognizing the output?
• Does the customer merely incur inconvenience?

The packet does not answer these questions.

Trust is an accumulated asset with nonlinear downside

A trusted assessment can become more useful as more institutions recognize it. A severe credibility failure can reverse that process because users are buying defensibility as well as information.

The relevant moat is therefore not simply brand awareness. It is the continued willingness of institutions to place consequential decisions on top of Moody's work.

Moody's through the Seven Powers

Power	Assessment	Evidence and interpretation
Scale economies	Plausible, not quantified	Moody's operates with approximately 16,000 employees across more than 40 countries and maintains broad data, model, and domain capabilities. The packet lacks unit costs or peer comparisons needed to prove declining cost per output.
Network economies	Limited direct evidence	Ratings can become more useful when issuers, investors, and institutions recognize the same language. The packet does not provide adoption, cross-side participation, or market-share data demonstrating a conventional network effect.
Counter-positioning	Not established	No evidence in the packet shows that Moody's has adopted a model incumbents cannot copy without damaging their existing businesses.
Switching costs	Plausible in MA workflows	Moody's says its intelligence is embedded in lending, underwriting, monitoring, compliance, and reporting workflows. The filing excerpt does not provide retention, migration cost, implementation duration, or renewal data.
Branding	Strong hypothesis	A 115-year ratings history and management's repeated emphasis on trust support the hypothesis. Independent evidence of customer preference or price premium is absent.
Cornered resource	Partial	Proprietary and curated data, validated models, historical information, and domain expertise could be scarce resources. The packet does not establish exclusivity or demonstrate that competitors cannot assemble substitutes.
Process power	Plausible	Long operating history, analytical methodologies, and accumulated domain expertise may encode hard-to-replicate organizational knowledge. The packet does not quantify accuracy, analyst productivity, or process advantages.

Overall Seven Powers conclusion

The most defensible current combination is:

• branding based on institutional trust;
• process power based on accumulated analytical practice;
• switching costs arising from workflow integration; and
• a partial cornered resource in proprietary data and models.

Network effects and scale economies may strengthen those advantages, but the supplied evidence does not prove them independently. Counter-positioning is not supported.

The more important insight is the interaction among the powers. Data without trust is a commodity. Trust without workflow integration is vulnerable. Workflow integration without continued analytical quality becomes technical debt. Moody's durability depends on maintaining all three.

Porter's Five Forces

Rivalry among existing providers: constrained, but not quantified

Credit assessment and financial analytics are trust-sensitive categories. Long histories, recognized methodologies, global coverage, and integration into customer processes can make competition less price-driven than in undifferentiated data services.

However, the packet includes no competitor list, market-share data, pricing history, or renewal metrics. It cannot establish the intensity of rivalry or Moody's relative position within individual product categories.

Threat of new entrants: likely lower in accepted ratings than in analytical tools

A new entrant can build a model or assemble data more easily than it can earn institutional acceptance. The 115-year operating history of MIS and the company's global regulatory exposure suggest that credibility, compliance, and coverage take time to accumulate.¹

Entry barriers are likely lower in narrow analytical applications, especially where a new tool can augment rather than replace an established rating or risk process. Moody's must therefore keep converting historical credibility into superior current products.

Buyer power: probably uneven

The packet identifies customers ranging from banks and insurers to investors, corporations, and governments. It does not provide customer concentration or contract data.

Buyer power is likely highest when sophisticated customers can combine internal models with competing data sources. It is likely lower when a Moody's output is embedded in multiple policies, systems, or counterparty relationships. This remains a hypothesis rather than a packet-supported measurement.

Supplier power: not assessable from the packet

Moody's depends on skilled employees, data, technology, and access to relevant information. The supplied excerpts do not quantify employee concentration, compensation pressure, third-party data costs, cloud dependencies, or supplier contracts.

Threat of substitutes: real at the analytical layer, harder at the coordination layer

Internal models, alternative data, competing analytics, and AI-enabled research can substitute for parts of the analytical process. They do not automatically replace an assessment that multiple external parties already understand and accept.

The key question is whether customers need Moody's underlying analysis, its institutional imprimatur, or both. A substitute that improves analysis but lacks acceptance may complement Moody's. A substitute that earns both analytical credibility and institutional acceptance would be much more dangerous.

Management and ownership

What the packet supports

Management describes Moody's as an integrated risk-assessment company and emphasizes embedding decision-grade intelligence in customer workflows. The financial record shows:

• positive operating cash flow in every year supplied from 2016 through 2025;
• recovery in net income and operating cash flow after the 2022 decline;
• a lower diluted share count in 2025 than in 2016; and
• a transition from negative to positive reported stockholders' equity.²

These results are relevant to management assessment, but they cannot be attributed solely to managerial skill without segment, market, acquisition, and capital-allocation context.

What remains unsupported

The packet lists Moody's 2026 proxy filing but does not include its substantive contents.³ It therefore does not support verified claims about:

• executive tenure or succession;
• insider ownership;
• compensation design;
• performance targets;
• board independence or relevant expertise;
• major outside shareholders;
• acquisition returns;
• gross repurchase spending; or
• management's purchase and sale of shares.

A durable ownership assessment requires reading and reconciling the proxy tables rather than inferring alignment from share-count changes.

Ten-year financial interpretation

The following figures come from the SEC company-facts snapshot included in the source packet.²

Fiscal year	Net income	Operating cash flow	Cash	Assets	Stockholders' equity	Diluted shares
2016	$266.6M	$1.259B	$2.052B	$5.327B	$(1.225B)	195.4M
2017	$1.001B	$755M	$1.072B	$8.594B	$(327.7M)	194.2M
2018	$1.310B	$1.461B	$1.685B	$9.526B	$459M	194.4M
2019	$1.422B	$1.675B	$1.832B	$10.265B	$612M	191.6M
2020	$1.778B	$2.146B	$2.597B	$12.409B	$1.569B	189.3M
2021	$2.214B	$2.005B	$1.811B	$14.680B	$2.727B	187.9M
2022	$1.374B	$1.474B	$1.769B	$14.349B	$2.519B	184.7M
2023	$1.607B	$2.151B	$2.130B	$14.622B	$3.318B	184.0M
2024	$2.058B	$2.838B	$2.408B	$15.505B	$3.565B	182.7M
2025	$2.459B	$2.901B	$2.384B	$15.830B	$4.054B	179.9M

1. Earnings expanded, but cyclicality did not disappear

Net income increased substantially across the period, but the 2022 decline demonstrates that a trusted financial-information franchise is not immune to changes in market activity or the broader economy. Net income fell from $2.214 billion in 2021 to $1.374 billion in 2022, then recovered to $2.459 billion in 2025.

The packet does not contain enough segment detail to attribute that movement among ratings issuance, analytics, acquisitions, expenses, taxes, or other factors.

2. Cash generation was more durable than any single year's earnings

Operating cash flow remained positive throughout the period and reached $2.901 billion in 2025. The 2022 decline was meaningful, but cash flow subsequently recovered above its 2021 level.

Because capital expenditures are absent, operating cash flow should not be mislabeled as free cash flow.

3. Per-share economics received a tailwind

Diluted shares declined across the decade. A durable per-share thesis should still separate operating growth from the effect of share-count reduction and should evaluate the prices paid for repurchases.

4. The asset base grew faster than the evidence can explain

Assets increased materially between 2016 and 2025. The 10-K identifies goodwill and acquired intangible assets as a critical accounting-estimate area, indicating that acquisition-related assets are relevant to Moody's financial statements.¹ The packet does not provide their balances or impairment history, so it cannot establish how much asset growth was organic.

5. Book equity is a poor standalone measure of franchise quality

Moody's generated positive operating cash flow even when reported stockholders' equity was negative. Equity later became positive and reached $4.054 billion in 2025.

This illustrates a broader analytical point: book equity can be distorted by historical capital returns, acquisitions, and accounting conventions. For a data- and trust-based franchise, cash generation, reinvestment requirements, liability structure, and per-share value creation matter more than book value alone.

Revenue-series limitation

The packet labels its revenue table as a ten-year snapshot, but the underlying dates run from 2008 through 2017 rather than 2016 through 2025. That older series shows revenue increasing from $1.755 billion in 2008 to $4.204 billion in 2017, but it cannot be combined with the 2016–2025 series as though it were a complete current-decade revenue history.

Accordingly, this note does not publish a ten-year revenue growth rate, operating margin, free-cash-flow margin, or return-on-invested-capital estimate.

Principal risks

Company-disclosed risk: legal and regulatory change

Moody's states that it is subject to extensive regulation in the United States and foreign jurisdictions. It describes the rules as complex, evolving, and increasingly stringent over time, while noting uncertainty related to political, legislative, and judicial changes.¹

Regulatory embeddedness is therefore a two-sided force. It may make experience and compliance infrastructure more valuable, but it also increases legal exposure and gives policymakers power to alter industry economics.

Company-disclosed risk: macroeconomic and geopolitical disruption

The 2025 10-K identifies inflation, monetary-policy responses, international conditions, and military conflicts as factors that may amplify business risks.¹

The financial series confirms variability but does not establish the sensitivity of each segment to interest rates, debt issuance, defaults, or economic growth.

Inferred risk: loss of credibility

Because the business depends on decision-grade intelligence, a sustained failure of methodology, governance, independence, or analytical quality could damage more than one product. It could weaken the institutional acceptance on which both ratings and workflow products rely.

This risk is inferred from the business model; the bounded risk-factor excerpt does not quantify it.

Inferred risk: analytical commoditization

AI and alternative data may reduce the cost of gathering information, generating research, and constructing risk models. That could pressure products whose value comes mainly from analytical convenience.

The defense is not merely having more data. Moody's must preserve differentiated data, model quality, institutional acceptance, and workflow integration. If those layers separate, parts of the portfolio could become easier to substitute.

Inferred risk: regulation reduces reliance rather than increasing barriers

Rules can favor established providers indirectly, but policymakers can also seek to reduce mechanistic dependence on external ratings. An investor should not capitalize regulatory embeddedness as a perpetual subsidy.

Acquisition and intangible-asset risk

The 10-K identifies goodwill and acquired intangible assets as a critical accounting-estimate area.¹ Without acquisition-spending, impairment, and segment-return data, this note cannot determine whether acquired growth has earned attractive returns.

Capital-allocation risk

A declining share count is not sufficient evidence of good capital allocation. Repurchases made above intrinsic value can transfer value away from continuing shareholders even while improving reported per-share metrics.

Valuation risk

No current price, enterprise value, debt schedule, pension obligation, or consensus estimate is included in the packet. Even an excellent business can be a poor investment at the wrong price. No expected-return conclusion is justified from the supplied evidence.

What would falsify the thesis?

The business-quality thesis would weaken if several of the following occurred:

1. Institutions reduced their reliance on Moody's ratings or ceased to recognize its classifications as a useful common language.
2. Regulatory changes lowered barriers to acceptance without lowering Moody's compliance burden.
3. MA products failed to maintain customer workflow integration, evidenced by weak retention, falling recurring revenue, or sustained pricing pressure.
4. Proprietary data and models ceased to produce meaningfully differentiated customer outcomes.
5. A credibility event impaired demand across ratings, research, and analytics.
6. Operating cash flow persistently failed to track reported earnings.
7. Acquisitions expanded assets and intangible balances without producing durable per-share cash growth.
8. Diluted shares began increasing without offsetting per-share value creation.
9. Competitors or internal customer systems achieved both analytical quality and comparable institutional acceptance.

Evidence needed for a complete investment underwriting

Before reaching a valuation-based conclusion, the following should be added:

• 2016–2025 revenue and operating-income series;
• MIS and MA revenue, margin, growth, and customer-retention history;
• recurring versus transaction-sensitive revenue;
• ratings issuance sensitivity by debt category;
• capital expenditures and capitalized software;
• gross debt, maturity schedule, interest expense, and leverage targets;
• goodwill, acquired intangibles, acquisition spending, and impairment history;
• gross repurchases, stock-based compensation, and average repurchase price;
• customer concentration and renewal statistics;
• regulatory references that identify where ratings are recognized or required;
• competitor market shares and pricing behavior;
• executive tenure, compensation, insider ownership, and major shareholders; and
• current market capitalization, enterprise value, and normalized owner earnings.

Without these items, Moody's can be classified as a potentially exceptional franchise, but not yet underwritten as an attractive security at a specific price.

Knowledge-compounding takeaways

1. The scarce resource may be accepted judgment, not information

Many information businesses are analyzed as databases. That misses the more valuable layer. In high-consequence markets, customers often need an output that other institutions will recognize and that internal decision-makers can defend.

The transferable question is:

Who owns the judgment that the system is organized around?

This applies to benchmarks, audits, certifications, indexes, laboratory standards, identity verification, and other trust infrastructure.

2. Standards power is strongest when it spans organizations

An internal workflow can create switching costs. A shared convention used across organizations can create something more powerful: coordination dependence.

The test is not whether customers like the product. It is whether replacing it requires multiple parties to change together.

3. Regulatory embeddedness is an amplifier, not a moat by itself

Regulation can amplify brand, process power, and switching costs. It can also amplify liability and political risk. The right analytical sequence is:

1. identify the underlying customer value;
2. determine whether institutions voluntarily coordinate around the product;
3. measure workflow integration;
4. then assess how regulation strengthens or weakens those forces.

Reversing that sequence risks mistaking legal complexity for customer captivity.

4. Trust, data, and workflow integration can create a lollapalooza effect

Each advantage is incomplete alone:

• Data without trust can be commoditized.
• Trust without current analytical quality decays.
• Quality without workflow integration can be displaced at renewal.
• Workflow integration without external acceptance creates only local switching costs.
• Regulation without customer value creates fragility.

When all five coexist, they can reinforce one another nonlinearly. The resulting franchise may be much stronger than a checklist of individual moats suggests.

5. Artificial intelligence attacks production costs before it attacks acceptance

AI can make research and modeling cheaper. It does not automatically make a new output acceptable to regulators, investment committees, counterparties, or auditors.

Incumbents are not safe, however. If AI allows challengers to establish better performance and institutions gradually accept their outputs, the historical moat can erode from the analytical layer outward.

6. Per-share discipline remains part of moat analysis

A durable business is not automatically a durable investment. The economic benefit must reach each share. Moody's declining diluted share count is directionally positive, but acquisition returns and repurchase prices still determine whether management converts franchise cash flow into per-share value.

Conclusion

Moody's appears to occupy an unusually valuable point in financial infrastructure: the place where information is converted into judgments that institutions can use, communicate, and defend.

The evidence supports the existence of a globally scaled, cash-generating business with long operating history, proprietary and curated data, analytical models, broad workflow relevance, and a declining diluted share count. It also shows that earnings are not immune to cyclical pressure and that regulation is a major source of both resilience and risk.

The strongest interpretation is not that Moody's owns an unassailable rating standard. It is that the company has accumulated several mutually reinforcing assets—trust, process knowledge, data, institutional familiarity, and workflow position—that could make replacement difficult.

The decisive investment questions remain unanswered by this packet: how the two segments produce their economics, how much capital and acquisition spending those economics require, whether management allocates cash intelligently, and what price investors are being asked to pay.

Moody's belongs on a high-quality-franchise watchlist. The supplied evidence does not yet support a valuation-based investment decision.

Source notes

The source packet is located at /Users/hiroyoshisuzuki/Documents/Obsidian Vault/Research/Investment analysis raw/2026-07-24/source-packet.md. Company statements are identified as reported facts or management descriptions. Moat assessments, bottleneck analysis, competitive-force judgments, and falsification tests are interpretations rather than company disclosures.

Footnotes

1. Moody's Corporation, 2025 Form 10-K, filed February 18, 2026. Used for the company overview, segment descriptions, operating footprint, regulatory-risk discussion, macroeconomic-risk discussion, and critical-accounting-estimate references. ↩ ↩² ↩³ ↩⁴ ↩⁵ ↩⁶ ↩⁷ ↩⁸ ↩⁹ ↩¹⁰ ↩¹¹ ↩¹² ↩¹³

2. SEC company-facts data included in the source packet, corresponding to Moody's Corporation, CIK 0001059556. Public SEC endpoint: Moody's company facts. Figures are reproduced as supplied in the packet and have not been supplemented with non-SEC estimates. The packet's revenue series covers 2008–2017, while the net-income, operating-cash-flow, cash, asset, equity, and diluted-share series cover 2016–2025. ↩ ↩² ↩³ ↩⁴ ↩⁵ ↩⁶

3. Moody's Corporation, 2026 definitive proxy statement, filed March 4, 2026. The packet lists the filing but does not include its ownership, compensation, or governance tables; no substantive management-ownership claims have therefore been drawn from it. ↩