Mutual fund disclosures read, unsurprisingly, like the legal documents they are—full of terms of art, legalese, and stock language about performance, fees, and investment risk. It is tempting to dismiss disclosures as “boilerplate”—a four-letter word in the law, belittling the drafting and dismissing the informative value. The SEC shares this instinct, cautioning mutual funds to avoid boilerplate. And yet, when we examined more than 23,000 mutual fund disclosure filings spanning 2011 to 2022, we found that roughly 80 percent of the language in investment strategy and principal risk sections is recycled year to year.

Is the system failing? We don’t think so. Our analysis suggests that boilerplate in mutual fund disclosures is neither an unconsidered shortcut nor a compliance failure. It is a rational equilibrium—one that serves funds, the SEC, and investors alike. And when funds deviate from their standard language, that deviation carries real information.

The Regulatory Game Behind the Language

To understand boilerplate, consider the disclosure task mutual funds face. Funds must simultaneously satisfy SEC requirements, inform investors and their intermediaries, and avoid inadvertently revealing proprietary strategy to competitors—all through a document reviewed by layers of internal stakeholders—legal, compliance, outside counsel, and independent directors. Writing a high-quality disclosure from scratch each year is costly. Changing language introduces regulatory uncertainty and requires fresh consensus across that entire stack.

Against this backdrop, recycling familiar, previously accepted language is not unconsidered—it is strategy. Boilerplate builds shared meaning over time. When an SEC examiner has seen a fund’s description of merger arbitrage or emerging market risks before, that familiar formulation is easier to assess and approve. Repeated language, once vetted, functions as a term of art—carrying complex legal and financial concepts efficiently to the regulators and intermediaries who will encounter it across many filings. Boilerplate, in this account, is infrastructure.

House Language

The most striking evidence of boilerplate’s functional role comes from within fund families. We find that funds managed by the same complex share significantly more language with each other than with comparably situated funds at other firms. We call this “house language”: family-specific boilerplate developed by shared legal and compliance teams. The pattern is robust: Every one of our within-family pairs exhibited statistically significant higher similarity compared with out-of-family disclosure with similar asset classes.  For example, Vanguard equity funds are more similar to other Vanguard equity funds than Fidelity equity funds.

Consistent language reflects in-house drafting across products and reduces the burden of review, maintains coherent compliance controls, and gives everyone inside the fund a shared vocabulary for what the disclosures say. House language is, in short, efficient governance.

When Language Changes, Portfolios Change

Boilerplate’s functional role becomes most apparent when funds depart from it. We identify the funds with the most significant changes to their investment strategy disclosures in a given year—those in the bottom 5 percent of year-over-year language similarity—and then examine what happened to their portfolios.

The relationship is clear and consistent: Funds that change their disclosure language the most also show the largest and most variable shifts in portfolio composition across all four asset categories—equity securities, debt securities, cash, and other holdings. Funds with stable language, by contrast, maintain stable portfolios. The correlation between disclosure change and portfolio change is statistically significant across all measures we employ.

This is what our theoretical model predicts. Funds face substantial costs when they revise disclosure language—the full weight of multi-tiered internal review, potential regulatory scrutiny, and the operational disruption of updating the compliance controls that were built around the prior language. Funds bear those costs when strategy has changed and existing language no longer reflects it—making boilerplate the stable baseline against which deviations become legible.

The Crypto Case:  Emerging Strategies and Deviations

Emerging investment strategies—compared with established ones-—exhibit less boilerplate. Cryptocurrency and digital asset funds are a clear example. Where an S&P 500 index fund can—and does—reuse essentially identical strategy language year after year (Vanguard’s S&P 500 fund repeated the same investment strategy statement across 20212024), a fund investing in digital assets cannot. The vocabulary is still being invented, the regulatory environment is in flux, and the relevant risks have not yet settled into terms of art.

Practical Takeaways

For the SEC, boilerplate analysis offers a scalable tool for monitoring and enforcement. Identifying filings where investment strategy language has not changed for five or more years, where strategy sections have shifted significantly without corresponding updates to the risk narrative, or where a fund’s boilerplate is a pronounced outlier relative to its asset class can direct limited examiner resources toward the most anomalous cases.

For plan fiduciaries, broker-dealers, and other investment intermediaries, the implication is pointed: Focus on what changes. Given the institutional costs funds incur to revise language, significant deviations from boilerplate are not mere wordsmithing. For administrators overseeing 401(k) and 403(b) plans, a systematic review of language change—rather than a full annual re-read of every prospectus—offers an efficient and well-grounded approach to fiduciary oversight.

For fund governance more broadly, house language is already working. Boards and compliance officers who have developed consistent family-wide language should recognize that the stability it provides also means departures from it carry weight, internally as much as externally.

Boilerplate, at first glance, may look like a failure of a disclosure regime. Our model and our data suggest a different reading: It is a feature of that regime, and one that makes deviation, when it occurs, all the more meaningful.

Methodology

Our findings draw on an original dataset of 23,828 mutual fund summary prospectuses filed with the SEC between 2011 and 2022. We measure boilerplate using two text similarity methods—TF-IDF cosine similarity and five-gram shingle cosine similarity—applied to the Investment Strategy and Principal Risk sections of each filing. Additional details on data construction and methodology are available in the full article.

Anne M. Tucker is the Robert Cotten Alston Chair in Corporate Law at the University of Georgia School of Law. Susan Navarro Smelcer is an assistant professor at Wake Forest University in the Department of Politics and International Affairs. Yusen Xia is the Anne and Michael D. Easterly Distinguished Professor and Director, Institute for Insight at Georgia State University Robinson College of Business. This post is based on their article, “The Function and Form of Boilerplate in Mutual Fund Disclosures,” forthcoming in the NYU Journal of Law & Business  and available here.