The Rise and Fall of DeFi Fund Managers: Lessons from Stream Finance

By: crypto insight|2025/11/21 12:30:09

Key Takeaways

DeFi fund managers have emerged as new financial intermediaries, managing billions without regulatory oversight.
The collapse of Stream Finance highlighted the systemic risks inherent in the DeFi ecosystem.
Traditional financial accountability mechanisms are largely absent in the DeFi space, leading to unmitigated risks.
The DeFi model encourages high-yield but high-risk strategies, often at the expense of careful risk management.
Suggestions for reform include mandatory identity disclosure, capital requirements, and reserve proof.

Introduction to DeFi Fund Managers

In the last 18 months or so, the decentralized finance (DeFi) landscape has seen the emergence of a new class of financial intermediaries. These entities, known by titles such as “risk managers,” “vault managers,” or “strategy operators,” exert considerable influence within DeFi ecosystems. They manage substantial sums on protocols like Morpho and Euler, implementing risk parameters, selecting collateral types, and deploying yield strategies. For managing these assets, they extract performance fees ranging from 5% to 15%. However, these roles operate without the licenses, regulatory oversight, or mandatory disclosure of credentials that traditional financial institutions are subject to.

Stream Finance Collapse: A DeFi Debacle

In November 2025, the collapse of Stream Finance exposed the vulnerabilities and risks inherent in the DeFi architecture. The incident resulted in significant financial losses across the ecosystem, with estimated ripple effects causing around $285 million in total damages. Several managers, including TelosC, Elixir, MEV Capital, and Re7 Labs, had excessively concentrated user deposits with a single counterparty, who operated with a collateral of only $1.9 million against the leveraged position reaching up to 7.6 times this amount. Despite clear warning signals from figures like KOLCBB and Yearn Finance months before the crash, prevailing incentives deterred fund managers from taking preventive actions.

Comparing DeFi and Traditional Financial Intermediaries

The operational model of DeFi fund managers borrows from traditional finance but eschews the accountability mechanisms that have been honed over centuries. In contrast to the capital requirements, fiduciary duties, and regulatory scrutiny that banks or brokerage firms face, DeFi fund managers rely mainly on market incentives. These incentives prioritize asset accumulation and yield maximization over risk mitigation, while protocols claim to be “neutral infrastructure,” profiting without accountability for the ensuing risks—a stance long rejected in traditional finance due to past catastrophic failures.

The Double-Edged Sword of Permissionless Architecture

Platforms like Morpho and Euler function as permissionless lending infrastructures, allowing anyone to create vaults, set risk parameters, and gather deposits freely. While such architecture promotes innovation and broadens access to underserved participants, it also introduces fundamental problems, as highlighted by the 2025 crisis. There are no entry checks to ensure the quality of managers, no registration to hold failed managers accountable, anonymity that allows managers to walk away from losses, and no capital requirements ensuring managers have skin in the game beyond fickle reputations.

Case Study: Stream Finance’s Path to Collapse

Stream Finance exemplified a specific failure pattern within DeFi’s permissionless framework. The absence of barriers allowed anyone to compete for deposits by offering high yields—either through genuine alpha (rare and hard to sustain) or through heightened risks (common and potentially disastrous). Users attracted by promises of high annual returns often placed undue trust in so-called risk managers, assuming their due diligence. In contrast, fund managers, driven by fee opportunities, accepted risks that prudent risk management would typically reject.

Inherent Conflicts of Interest and Incentive Failures

The operational model of fund managers inherently engenders conflicts of interest, where the financial incentives of users and managers diverge. Users seek safety and reasonable returns, whereas managers focus on maximizing fee income. The most dangerous conflict arises when yield opportunities necessitate risks that users themselves would usually avoid. An instructive case involves RE7 Labs, which identified counterparty risk before integrating xUSD but proceeded, swayed by the prospect of demand. This dynamic penalizes caution: prudent managers earn less, while reckless ones prosper—until disaster exposes their unhedged positions.

Asymmetrical Fee Structures

Fund managers commonly extract performance fees of 5%-15% from user yields, a model favoring profit-sharing without equivalent loss sharing. For instance, in a scenario where a $100 million vault generates a 10% return, a manager might earn $1 million in fees. However, if by doubling the risk, the return reaches 20%, their earnings double to $2 million, even if subsequent losses wipe out half the deposit, affecting only future earnings without reclaiming past fees.

Protocol Conflicts

Protocols like Morpho and Euler face their own conflicts of interest, earning fees from vault activities, which incentivizes maximizing activity—even if it requires permitting high-risk vaults to attract deposits. While protocols present themselves as neutral, they profit from transactions like brokers do, and as history shows, entities profiting from mediation should not be fully shielded from the risks they create.

Accountability Vacuum in DeFi

While traditional finance punishes customer fund losses through regulatory investigations, license revocations, and legal liabilities, DeFi fund managers face mainly reputational damage and can often restart under a new identity. The March 2024 Morpho incident, where a minor oracle price deviation led to losses, established a precedent of shared responsibility evasion—a deliberate design that capitalizes profits while society bears the losses.

Anonymity and the Lack of Accountability

Many DeFi managers maintain anonymity, purportedly for security and privacy, yet this undermines accountability, enabling malfeasance without repercussions. Unlike in traditional finance, where civil liabilities and reputation tracking impose deterrence, DeFi lacks such checks.

Opaque Strategies and the Risks of Authority

Fund managers bill themselves as risk experts but often lack the necessary infrastructure or expertise, as demonstrated in November 2025. Traditional institutions invest significantly in risk management, unlike DeFi managers, who tend to focus on yield generation and asset gathering. The opaqueness in strategy disclosures allows fraudulent or reckless behavior to flourish unnoticed.

Reserve Proof: An Underutilized Solution

Despite the availability of efficiently privacy-preserving reserve proof technologies like Merkle trees, Stream Finance lacked any form of reserve verification, choosing opacity. Protocols managing significant funds should require reserve proofs, much like demanding external audits from banks.

Stream Finance: An Exemplary DeFi Failure Case

Stream Finance’s demise showcased the systemic issues plaguing DeFi fund management—a convergence of inadequate diligence, conflicted interests, ignored warnings, opacity, and lack of accountability. Warnings from industry analysts were disregarded as managers continued risky practices.

Recommendations for Improvement

While the current model presents a vacuum of accountability, its advantages in capital efficiency and professional fund management can persist alongside necessary reforms:

Identity Disclosure: Compulsory identity disclosure for managing substantial funds can ensure accountability without compromising privacy.

Capital Requirements: Managers should be required to hold risk capital, aligning their interests with those of users.

Transparency: Mandating a standardized disclosure of strategies can mitigate the risks associated with opaque practices.

Reserve Proof: Enforcing reserve proof requirements can safeguard against the unchecked management of off-chain assets.

Concentration Limits: Imposing limits on exposure will curb the dangerous trend of excessive risk concentration.

Protocol Accountability: Protocols must share in the responsibility and offer safeguards like insurance funds to protect user investments.

Conclusion

The existing DeFi fund management model harbors systemic failures, entrusting vast amounts of user funds to unregulated entities. While not a wholesale rejection of the model, given its potential benefits, there’s a clear need to incorporate accountability mechanisms honed in traditional finance settings. Only when the industry acknowledges the necessary balance between profiteering and responsibility will it avert repeating past failures.

FAQs

What caused the collapse of Stream Finance?

Stream Finance’s collapse was chiefly due to excessive leverage and risk concentration in a single counterparty, compounded by ignored warnings and systemic incentive flaws within the DeFi ecosystem.

How does DeFi lack traditional financial accountability?

Unlike traditional finance, DeFi lacks regulatory oversight, capital requirements, and identity disclosure, making fund managers operate in a largely unregulated environment.

Can DeFi reconcile innovation with accountability?

Yes, by integrating identity disclosure, capital requirements, and transparency measures, DeFi can maintain its innovative edge while ensuring greater accountability.

What lessons does the Stream Finance collapse offer?

Stream Finance underscores the risks of opaque practices, unchecked leverage, and the failure of relying solely on reputational accountability in DeFi.

How can reserve proof enhance DeFi safety?

By mandating reserve proof, DeFi protocols can bolster transparency and verify asset backing, preventing fraudulent activities and reinforcing trust.

Editor's Note: Citrini7's cyberpunk-themed AI doomsday prophecy has sparked widespread discussion across the internet. However, this article presents a more pragmatic counter perspective. If Citrini envisions a digital tsunami instantly engulfing civilization, this author sees the resilient resistance of the human bureaucratic system, the profoundly flawed existing software ecosystem, and the long-overlooked cornerstone of heavy industry. This is a frontal clash between Silicon Valley fantasy and the iron law of reality, reminding us that the singularity may come, but it will never happen overnight.

The following is the original content:

Renowned market commentator Citrini7 recently published a captivating and widely circulated AI doomsday novel. While he acknowledges that the probability of some scenes occurring is extremely low, as someone who has witnessed multiple economic collapse prophecies, I want to challenge his views and present a more deterministic and optimistic future.

Never Underestimate "Institutional Inertia"

In 2007, people thought that against the backdrop of "peak oil," the United States' geopolitical status had come to an end; in 2008, they believed the dollar system was on the brink of collapse; in 2014, everyone thought AMD and NVIDIA were done for. Then ChatGPT emerged, and people thought Google was toast... Yet every time, existing institutions with deep-rooted inertia have proven to be far more resilient than onlookers imagined.

When Citrini talks about the fear of institutional turnover and rapid workforce displacement, he writes, "Even in fields we think rely on interpersonal relationships, cracks are showing. Take the real estate industry, where buyers have tolerated 5%-6% commissions for decades due to the information asymmetry between brokers and consumers..."

Seeing this, I couldn't help but chuckle. People have been proclaiming the "death of real estate agents" for 20 years now! This hardly requires any superintelligence; with Zillow, Redfin, or Opendoor, it's enough. But this example precisely proves the opposite of Citrini's view: although this workforce has long been deemed obsolete in the eyes of most, due to market inertia and regulatory capture, real estate agents' vitality is more tenacious than anyone's expectations a decade ago.

A few months ago, I just bought a house. The transaction process mandated that we hire a real estate agent, with lofty justifications. My buyer's agent made about $50,000 in this transaction, while his actual work — filling out forms and coordinating between multiple parties — amounted to no more than 10 hours, something I could have easily handled myself. The market will eventually move towards efficiency, providing fair pricing for labor, but this will be a long process.

I deeply understand the ways of inertia and change management: I once founded and sold a company whose core business was driving insurance brokerages from "manual service" to "software-driven." The iron rule I learned is: human societies in the real world are extremely complex, and things always take longer than you imagine — even when you account for this rule. This doesn't mean that the world won't undergo drastic changes, but rather that change will be more gradual, allowing us time to respond and adapt.

The Software Industry Has "Infinite Demand" for Labor

Recently, the software sector has seen a downturn as investors worry about the lack of moats in the backend systems of companies like Monday, Salesforce, Asana, making them easily replicable. Citrini and others believe that AI programming heralds the end of SaaS companies: one, products become homogenized, with zero profits, and two, jobs disappear.

But everyone overlooks one thing: the current state of these software products is simply terrible.

I'm qualified to say this because I've spent hundreds of thousands of dollars on Salesforce and Monday. Indeed, AI can enable competitors to replicate these products, but more importantly, AI can enable competitors to build better products. Stock price declines are not surprising: an industry relying on long-term lock-ins, lacking competitiveness, and filled with low-quality legacy incumbents is finally facing competition again.

From a broader perspective, almost all existing software is garbage, which is an undeniable fact. Every tool I've paid for is riddled with bugs; some software is so bad that I can't even pay for it (I've been unable to use Citibank's online transfer for the past three years); most web apps can't even get mobile and desktop responsiveness right; not a single product can fully deliver what you want. Silicon Valley darlings like Stripe and Linear only garner massive followings because they are not as disgustingly unusable as their competitors. If you ask a seasoned engineer, "Show me a truly perfect piece of software," all you'll get is prolonged silence and blank stares.

Here lies a profound truth: even as we approach a "software singularity," the human demand for software labor is nearly infinite. It's well known that the final few percentage points of perfection often require the most work. By this standard, almost every software product has at least a 100x improvement in complexity and features before reaching demand saturation.

I believe that most commentators who claim that the software industry is on the brink of extinction lack an intuitive understanding of software development. The software industry has been around for 50 years, and despite tremendous progress, it is always in a state of "not enough." As a programmer in 2020, my productivity matches that of hundreds of people in 1970, which is incredibly impressive leverage. However, there is still significant room for improvement. People underestimate the "Jevons Paradox": Efficiency improvements often lead to explosive growth in overall demand.

This does not mean that software engineering is an invincible job, but the industry's ability to absorb labor and its inertia far exceed imagination. The saturation process will be very slow, giving us enough time to adapt.

Redemption of "Reindustrialization"

Of course, labor reallocation is inevitable, such as in the driving sector. As Citrini pointed out, many white-collar jobs will experience disruptions. For positions like real estate brokers that have long lost tangible value and rely solely on momentum for income, AI may be the final straw.

But our lifesaver lies in the fact that the United States has almost infinite potential and demand for reindustrialization. You may have heard of "reshoring," but it goes far beyond that. We have essentially lost the ability to manufacture the core building blocks of modern life: batteries, motors, small-scale semiconductors—the entire electricity supply chain is almost entirely dependent on overseas sources. What if there is a military conflict? What's even worse, did you know that China produces 90% of the world's synthetic ammonia? Once the supply is cut off, we can't even produce fertilizer and will face famine.

As long as you look to the physical world, you will find endless job opportunities that will benefit the country, create employment, and build essential infrastructure, all of which can receive bipartisan political support.

We have seen the economic and political winds shifting in this direction—discussions on reshoring, deep tech, and "American vitality." My prediction is that when AI impacts the white-collar sector, the path of least political resistance will be to fund large-scale reindustrialization, absorbing labor through a "giant employment project." Fortunately, the physical world does not have a "singularity"; it is constrained by friction.

We will rebuild bridges and roads. People will find that seeing tangible labor results is more fulfilling than spinning in the digital abstract world. The Salesforce senior product manager who lost a $180,000 salary may find a new job at the "California Seawater Desalination Plant" to end the 25-year drought. These facilities not only need to be built but also pursued with excellence and require long-term maintenance. As long as we are willing, the "Jevons Paradox" also applies to the physical world.

Towards Abundance

The goal of large-scale industrial engineering is abundance. The United States will once again achieve self-sufficiency, enabling large-scale, low-cost production. Moving beyond material scarcity is crucial: in the long run, if we do indeed lose a significant portion of white-collar jobs to AI, we must be able to maintain a high quality of life for the public. And as AI drives profit margins to zero, consumer goods will become extremely affordable, automatically fulfilling this objective.

My view is that different sectors of the economy will "take off" at different speeds, and the transformation in almost all areas will be slower than Citrini anticipates. To be clear, I am extremely bullish on AI and foresee a day when my own labor will be obsolete. But this will take time, and time gives us the opportunity to devise sound strategies.

At this point, preventing the kind of market collapse Citrini imagines is actually not difficult. The U.S. government's performance during the pandemic has demonstrated its proactive and decisive crisis response. If necessary, massive stimulus policies will quickly intervene. Although I am somewhat displeased by its inefficiency, that is not the focus. The focus is on safeguarding material prosperity in people's lives—a universal well-being that gives legitimacy to a nation and upholds the social contract, rather than stubbornly adhering to past accounting metrics or economic dogma.

If we can maintain sharpness and responsiveness in this slow but sure technological transformation, we will eventually emerge unscathed.

Source: Original Post Link

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