GAIM Ops Cayman 2026

GAIM Ops Cayman 2026: Key Takeaways on AI, ODD & Risk Management

GAIM Ops Cayman 2026: Key Takeaways on AI, ODD & Risk Management

GAIM Ops Cayman 2026 · April 19–22 · Grand Cayman

What We Heard.
What the Room Revealed.

Three days at GAIM Ops Cayman. Our read on AI, risk management, and operational due diligence — from the sessions, the sponsors, and the conversations that don't make it into the official notes.

Published
April 2026
Topics
AI · Risk · ODD · Operations
Reading time
20 minutes
0Before the Sessions 1All Things AI 2Risk Management 3Operational Due Diligence The Bigger Picture
Key Takeaways
  • Over 90% of managers report using AI — but most are in assistive mode. The firms generating real operational ROI invested in data quality and process structure before layering AI on top.
  • ODD practitioners are returning to in-person site visits — because AI-generated DDQ responses, fabricated credentials, and deepfake risk mean written verification is no longer sufficient on its own.
  • SEC examiners in 2026 are focused on AI governance, off-channel communications, and valuation practices. Treat every examination as if it could become an enforcement referral.
  • The sponsor mix reveals a competition to own the system of record for alternatives operations — every service category had firms arguing the current infrastructure was built for a different era.
  • Governance is the differentiator — across AI, compliance, and ODD, the consistent message is that clear accountability, documented controls, and oversight mechanisms separate firms that can scale from those that cannot.
Before the Sessions

What the Conference Itself Is Telling You

Reading the sponsor mix and agenda structure as a market signal

The Service Groups Showing Up

The firms that sponsor GAIM Ops are there because the COOs, CCOs, CFOs, and ODD heads in that room make or directly influence the buying decisions that shape operational infrastructure in alternatives. Reading the sponsor list by service category — not just by name — reveals which parts of the stack are in active competition.

Service category & what their presence signals
Who is here
Audit, Tax & Accounting Six firms spanning the Big Four and mid-market — the broadest category by firm count. Beyond traditional assurance, sessions from this group addressed AI governance, valuation oversight, and management company transparency. The audit relationship is expanding into operational advisory.
Legal & Fund Structure Offshore and onshore counsel are a fixture at GAIM Ops Cayman — but sessions this group anchored shifted from fund formation toward AI compliance obligations, regulatory examination strategy, and contract risk. The legal practice is moving where the operational risk is.
Fund Administration The largest category by firm count. Every fund admin here is making the same pivot: from accuracy-and-processing to data infrastructure and AI-enabled reporting. The competitive argument has shifted. The ones that cannot make it credibly are losing ground to those that can.
Custody, Prime & Banking Custody and prime brokerage sitting alongside specialty banks reflects how broad the capital infrastructure conversation has become. Clear Street's presence is notable — they are making an active argument for modernizing prime services for the next generation of managers.
Cybersecurity & IT Managed Services Three firms across managed security and IT infrastructure — a category that barely registered at this conference five years ago. Abacus at platinum and Drawbridge running two dedicated sessions reflects a buyer community that now treats technology infrastructure as ODD subject matter, not just an IT checkbox.
Data & Portfolio Infrastructure The most contested layer at the conference. Each is making the same underlying argument: the portfolio data, reporting, and post-trade infrastructure of alternatives needs to be rebuilt for the AI era. Arcesium and FINBOURNE are particularly aggressive in positioning as open, API-first replacements for legacy middle-office infrastructure. Arch and Discern round out the data side — tax data infrastructure and alternative data respectively.
Compliance, Governance & Risk Eight firms spanning AI-native surveillance, compliance program management, board governance, regulatory intelligence, and insurance-linked risk. Behavox and Norm AI represent the new wave — AI-first from inception. ACA Group, Diligent, and FIS represent incumbent compliance infrastructure under pressure to modernize. Price Forbes connects directly to the ODD session message that lack of business-level insurance is a disqualifier.
Diligence & Investor Workflow ODD and investor workflow platforms are becoming infrastructure categories rather than point solutions — sitting at the intersection of data, governance, and the manager-allocator relationship. The layer that AI amplifies when the data is structured and permissioned correctly.
Verification & Background Intelligence Four verification and background intelligence firms at the same conference as custody banks and data platforms reflects how central identity verification, ownership transparency, and screening have become to the ODD workflow — particularly as AI-generated documentation and deepfake risk increase the demand for independent confirmation.
Valuation & Financial Advisory Independent valuation and financial advisory firms appearing prominently reflects the valuation scrutiny that dominated the ODD and private credit sessions. The question of whether marks are defensible — not just calculated — is becoming a first-order allocator concern.
Retailization & Wealth Infrastructure iCapital at platinum — with a session on digital identity and data-first onboarding compliance — signals that the retailization of alternatives is an active infrastructure buildout, not a future trend. Monetaforge and Steward represent emerging tooling for the distribution and investor servicing layer that retail access requires.
Treasury & Derivatives Treasury and derivatives management tools migrating into the alternatives operating model — categories historically absent from this conference. Their appearance reflects growing complexity in cash management, hedging, and liquidity operations as fund structures diversify.
Workflow & Productivity AI A mixed category — digital asset custody, AI meeting tools, and emerging manager infrastructure — that reflects the breadth of operational tooling now being evaluated by COOs and CCOs. Fellow's appearance signals that productivity AI is being taken seriously as a compliance-adjacent workflow tool, not just a convenience.

The Agenda Tells the Same Story, in Sequence

The agenda structure this year moved through four phases, and the progression is worth naming explicitly because it is not how operations conferences used to be structured.

It opened with failure — landmark financial scandals, insider risk, leadership under pressure. The argument: the most significant industry crises were operational and cultural failures that were visible before they became crises. This is not a warm-up. It is a framing device.

The middle days moved into system transformation: AI in fund administration, data-first compliance, digital identity, retailization. Operations is no longer back-office process management. It is becoming the infrastructure and product layer of the firm.

The conference closed on governance — AI ethics, SEC enforcement, ODD best practices, service provider oversight. The message: you can innovate, but only if you can defend it.

Three new tracks added for 2026 sharpen the point. A Hedge Fund Track on operating models and allocator expectations. A Fund Strategy and Structure Track on retailization, tokenization, and capital formation. A Leadership and Culture Track on talent, AI literacy, and governance. Taken together, they redefine the COO and CCO role. It is no longer process management. It is architecture.

The Competition Is for the System of Record

AI is not the underlying story. It is the forcing function that has made the underlying story urgent. That story is: who owns the system of record for alternative investment operations — for data, workflows, governance, the manager-allocator relationship, compliance, and ODD?

These have historically been fragmented across fund administrators, auditors, legal firms, prime brokers, and manual processes inside allocator teams. That fragmentation worked when the pace of change was slower and the regulatory surface was narrower. Neither condition holds in 2026. AI cannot be deployed effectively on fragmented, unstructured, unverified data. Retailization cannot scale on manual onboarding. SEC examiners cannot be satisfied with documentation that lives in email threads.

The firms that own clean, structured, permissioned data at the center of the manager-allocator relationship are the ones AI will amplify. Everything else is still figuring out what it wants to be when it grows up.

Before the sessions All Things AI Risk Management Operational Due Diligence The bigger picture
Theme 1

All Things AI

Use cases, named tools, adoption reality, and the ethics conversation the industry can't avoid

The headline number out of the AI Summit: more than 90% of hedge fund managers report using AI in some capacity. The follow-up question that matters — what does "using AI" actually mean — is where the conversation got interesting.

90%+
Report using AI
Managers reporting AI use in some capacity as per AIMA's survey. Depth varies enormously.
3%
Now restrict AI use
Down from 33% as per Albourne's survey — creating new governance questions for ODD practitioners.
60–70%
DDQ automation rate
Standard DDQ questions handled by leading tools drawing on prior responses based on attendee feedback.

What AI Is Actually Being Used For

Workflow automation

The most widely deployed AI applications are not the flashiest. Firms are using agents to analyze the tone and intent of inbound investor emails and automatically route them to the right person on the IR team. End-of-day summary agents scan inboxes and generate structured digests of outstanding action items. The value is in the cumulative time recovered and the reduction in things falling through the cracks.

DDQ and RFP automation

Multiple firms described using AI to handle 60–70% of standard DDQ questions. Where this gets important for the allocator community: With AI-generated DDQ responses are increasingly common, which managers are drawing on how prior questionnaires were answered, and which managers are generating responses without the source. This is raising the question of what verification looks like.

Document intelligence and knowledge management

Firms are loading fund documents, fund history, contracts, and compliance policies into AI-queryable knowledge bases for compliance research, contract redlining, clause-level standardization, and regulatory change management. In fund administration, agents are being used to extract data from K-1s and tax forms into transactional databases, removing significant manual entry from operations teams.

Legal and compliance workflows

AI is being applied to legal document review, compliance surveillance, trade monitoring, and contract management. Several CCOs noted areas where they are deliberately holding AI back: regulatory filings, final compliance sign-offs, and any output that could constitute legal advice. Human judgment must remain accountable for compliance decisions.

"Move fast and break things is not a viable compliance strategy." — GAIM Ops AI Ethics panel

Tools the Industry Is Talking About

The following tools were mentioned by name across sessions. The ecosystem remains fragmented — enterprise search, document intelligence, contract management, workflow automation, and compliance surveillance are all being deployed, but rarely in an integrated stack.

Enterprise Search
Glean
Universal search across email, Slack, and internal documents. Used for investor meeting prep and handling 80–90% of standard DDQ questions by drawing on prior responses.
Multi-model AI
LibreChat
Open-source platform displaying side-by-side responses from multiple AI models, allowing teams to compare outputs. Also supports building custom chatbots for specific workflows.
Regulatory knowledge
Norm AI
Builds AI-queryable knowledge bases from fund documents and fund history. Primarily used for compliance and legal research workflows.
Legal workflows
ClauseBase, EverSort, Harvey AI, ILS
ClauseBase manages legal language at the clause level. EverSort handles contract organization. Harvey AI auto-generates redlines against counterparty documents based on pre-set preferred language. ILS handles MFN processes and investor comment workstreams.
Fund admin automation
Microsoft 365 Copilot Studio
Used to build customized agents for fund administration workflows including document review, data extraction, and K-1 processing.
Workflow AI
ChatGPT, Claude (Anthropic)
ChatGPT uses generative pre-trained transformers to produce text, speech, and images from user prompts. Claude by Anthropic operates within controlled workflows with firm specific compliance guardrails rather than open ended access.
Diligence infrastructure
DiligenceVault
DV's AI-powered DDQ workflow suite was cited as part of the infrastructure layer being used by allocators and managers to automate and standardize the data exchange at the center of ODD. Autofill and AI-powered AFS extraction were specifically referenced.

The Adoption Reality: Wide but Shallow

The 90% figure masks a wide spectrum. Most firms are still in assistive AI mode — writing assistants, general-purpose chat, email drafting — rather than operating embedded, system-integrated agents. The gap between those two postures is significant, and it is widening. The firms that have crossed it share a common trait: they invested in data quality and process clarity before layering AI on top. AI built on poor data produces poor outputs, regardless of model sophistication. The laggards are not failing because the technology is difficult. They are failing because governance and change management are difficult.

Talent is the binding constraint. The demand for people who can sit at the intersection of investment and operations knowledge and AI technical fluency far exceeds supply. Firms are building internal training programs and partnering with service providers to bridge this gap.

Ethical AI and the Regulatory Horizon

Regulatory expectations around responsible AI use remain largely principles-based. Firms are expected to self-govern for now. The areas CCOs flagged as highest-risk:

Core compliance requirements emerging
Data protection — particularly where proprietary investment data or investor PII is being fed into external models
Model bias and explainability — regulators and LPs increasingly want to understand how an AI arrived at a conclusion
Accountability — someone human must own every AI-driven output that carries compliance significance
Auditability — firms need documented evidence of implementation and oversight, not just policies on paper

The "black box" problem is not going away. Explainability is non-negotiable in regulated environments. Firms need to be able to show why the AI said what it said — that standard applies to surveillance, risk monitoring, and DDQ workflows alike.

The growing expectation: managers should be able to articulate not just that they use AI, but how it is controlled, monitored, and audited.

One specific failure mode already emerging: AI-generated compliance policies that look real but have not been implemented, and AI-generated DDQ responses containing wrong interpretations of the manager's own policies. The practical consequence: ODD practitioners are returning to in-person site visits, because video can be faked, documents can be generated, and direct human verification remains the most reliable check available.

Overview Use cases Tools named Adoption reality Ethical AI
Theme 2

Risk Management Expectations

Insider threat, governance under pressure, and what the SEC is actually looking at in 2026

The risk surface in alternatives has changed faster in the last three years than in the decade before it, and the pace of adaptation varies significantly across the industry.

Insider Threat: The Human Signal Precedes the Technical One

The session on insider risk challenged the assumption that security programs are primarily a technology problem. The data is clear: most insider incidents are driven by behavioral and psychological factors — financial pressure, resentment, rationalization — before they manifest in system logs.

The framing that landed: most insider risk programs focus on detection after the fact. The more effective approach is building cultures where concerns can be raised early and safely. The behavioral signal almost always precedes the technical one — a person changes how they communicate, how they behave in team settings, how they interact with systems — and that signal is visible to the people around them long before any alert fires.

Practical guidance from the panel
Pay attention to behavioral changes in employees, not just access logs
Build escalation paths that feel safe to use — psychological safety is not softness, it is how accurate information reaches leadership in time to act
Structure post-mortems around systems and processes rather than individuals — this is how you prevent recurrence rather than just assign blame

The most dangerous risks are often the ones that feel too uncomfortable to raise internally.

For fund managers, the takeaway is structural: the question is not whether your firm has risk. Every firm has risk. The question is whether your culture and your reporting lines give risk a path to the surface before it becomes a crisis. The journalists noted they now work with investment managers on crisis preparation and communications — a signal that media relations and narrative management are operational competencies, not just PR.

SEC Examinations: What Examiners Are Actually Looking At

SEC examination activity is intensifying. Examiners are increasingly zeroing in on AI and technology risk, off-channel communications, valuation practices in private markets, and conflicts of interest. Firms that have done the preparation work are navigating exams more efficiently. Firms scrambling to reconstruct documentation during an exam are in a different situation.

The framing that matters: treat every examination as if it could become an enforcement referral. The gap between a routine exam and an investigation is smaller than many firms assume.

Preparation practices that work

Exam readiness
Run an internal mock exam before regulators arrive — find the gaps yourself before they do
Present a proactive walkthrough of your compliance program, including known risk areas and remediation steps already underway
Frame known issues with documented timelines — an issue you are already fixing looks very different from one they uncover
Keep a living exam-readiness file — policies, org charts, training records, surveillance summaries — current and accessible at all times

The tone from the top signal

Leadership during examination
Have CEO, COO, and CCO present and available, not just the compliance team
Align all senior leaders on a consistent narrative about firm history and compliance culture before the exam begins
Leaders should speak to the why behind the compliance program, not just the what
Transparency and direct answers always land better than deflection

You are working with the SEC, not managing them. That distinction matters more than most firms realize.

Additional Risk Highlights

Cybersecurity: the human problem

The firms with the best cyber outcomes share common traits: regular testing rather than annual assessments, strong vendor management, and a culture where security is everyone's responsibility. The most common failure mode is not technical — phishing, credential theft, and social engineering account for the majority of successful attacks. AI is a dual-use technology here: improving threat detection while enabling more sophisticated and scalable attacks, particularly AI-generated phishing at scale.

Regulatory complexity

"Whiplash" was used more than once across sessions. Rules are being proposed, delayed, reversed, and reinterpreted faster than compliance teams can adapt. Building regulatory agility into operating models is no longer optional. SEC examination focus areas are shifting toward technology risk, AI governance, and off-channel communications — firms that have not updated their compliance frameworks are exposed.

The outsourced CCO model

The outsourced CCO model is gaining traction among emerging managers. The key considerations: genuine authority and access, not just a title; divided attention across multiple clients is a real risk; and clear accountability must be maintained. Regulators are paying closer attention and want evidence of real oversight, not a checkbox.

Overview Insider threat SEC examinations Additional highlights
Theme 3

Operational Due Diligence

What allocators are asking, what managers are getting wrong, and how AI is changing both sides of the table

The ODD track at GAIM Ops Cayman 2026 was more candid than most panels are willing to be. Practitioners on both sides of the table spoke plainly about what is working, what is not, and where the function is heading.

75%
No management company audit shared
North American managers that do not conduct or share an audit of the management company — a gap that is harder to defend as allocator expectations rise.
3%
Restrict AI use
Down from 33% — creating new questions for ODD practitioners about governance, not just adoption.
5%
Markdown applied
Markdown on a position in active restructuring, moving from cash interest to PIK, in the case study discussed.

The Valuation Question

A detailed case study walked through a scenario that is becoming representative: an allocator believed they had purchased a senior secured portfolio. In practice, one position had stopped paying cash interest and moved to PIK. The enterprise value was in active restructuring. The markdown applied was approximately 5%. Portfolio NAV was reported as flat. The disconnect between the operational reality and the valuation treatment was visible — and it was the subject of allocator scrutiny precisely because it should have been.

The lesson: valuation is not the hardest challenge in private credit ODD. Structure is. Understanding asset/liability mismatch, redemption mechanics, and the actual content of the portfolio — particularly in evergreen structures — requires line-by-line engagement, not summary review.

The allocators who want to walk through each deal by line item are not being difficult. They are doing their job.

Expense Transparency and Business Viability

Allocators are pushing for transparency beyond the Annual Financial Statement — allocation of expenses across products, cost-sharing arrangements between vehicles, and an understanding of how compensation payout ratios are trending. What is the gross-to-net ratio, and what governance exists around it? One panel noted a shift in comp payout ratios from the high teens toward the low-to-mid twenties, reflecting the increasing cost of PM talent and technology.

Business viability is now part of ODD in a way it was not five years ago: how many years can a manager sustain a modest return level?

Business viability is everyone's problem. If a manager can't sustain the economics of running the fund, that is an operational risk, not just an investment one.

Outsourcing and Service Provider Quality

The pattern described for emerging managers is familiar: the PM called a friend, the fund admin is less well-known, and the CFO role is fractional. This may be appropriate for Fund I. The expectation is that it improves meaningfully for Fund II.

A practical framework offered: build a three-column matrix. Column one lists key operational processes. Column two assigns primary responsibility. Column three assigns secondary responsibility. Where there are gaps — where secondary responsibility is unclear — those are the decisions: hire in-house, or upgrade the service provider.

One panelist stated plainly: you can outsource a function. You cannot outsource the risk. Accountability for what goes wrong stays with the manager, always.

What ODD Teams Are Actually Doing

Veto authority

Some ODD teams operate with a formal veto; others operate in an advisory capacity to an investment committee. The consensus: veto authority, or at minimum clear escalation to a committee that can block, is essential for the function to have credibility.

Independence

Majority of he ODD teams have an independent reporting line into Risk or Compliance leadership, and very few report into the investment function.

Monitoring cadence

Cadence by fund type
Open-end funds: quarterly questionnaires anchored to a heat map of changes, onsite visits every 12–18 months, re-underwrite every 1–2 years based on risk signals
Closed-end funds: thorough initial diligence, semi-annual DDQ, onsite for the initial and for material changes
Ongoing: quarterly fund administrator verification of cash, AUM, and performance; monthly investment team data
Background checks: updated every 2–3 years, with some allocators running ongoing checks and mixing providers

Non-negotiables

Automatic or near-automatic disqualifiers
Insufficient transparency around ownership structure and succession planning
Background check findings that were not disclosed
Hiding behind exemptions where the spirit of the disclosure obligation applies
No insurance at the business level
Insufficient cash controls
Significant discrepancy between what a manager says and what the fund documents or audited financials show

What Good Looks Like from the Manager's Side

One session featured a senior manager who described their internal ODD preparation process. The practices that stood out:

Manager best practices
Conduct a debrief after every ODD meeting — what was asked, what the answers were, what could be tighter
Get junior staff supporting the CFO and Director of Compliance comfortable with being in ODD conversations
Reach out to large existing investors before making significant operational changes, not after
Be honest when a process does not yet exist — and ask the allocator how they would like to see it done, rather than improvise an answer
Get feedback from allocators after approval on what worked and what could be improved

The managers who do best in ODD are not the ones with the most polished materials. They are the ones who can speak plainly about their operations and tell you immediately when something did not go as planned.

AI in ODD: The New Questions and the New Risks

AI is now appearing in ODD in two distinct ways: as a subject of inquiry — how is the manager using AI? — and as a tool ODD practitioners are deploying themselves.

On the inquiry side, allocators are adding AI-specific questions to standard frameworks: What tools are in use? Who has access? What data is being fed into external models? What vendor risk management exists? Governance around AI usage — policies, oversight, audit trails — is becoming a significant factor in ODD assessments.

On the practitioner side, the picture is more cautionary. ODD teams described failure modes they have already encountered:

Failure modes already observed
Manager-side DDQ responses that were AI-generated and contained wrong interpretations of the manager's own policies
The same person appearing with three different titles across different documents
AI-generated policies that look credible but have not been implemented
Manufactured organizations and deepfake-enabled verification risks in remote due diligence

The practical response from several allocator teams: returning to in-person site visits, because video can be faked, polished documents can be AI generated, and direct human interaction with the people and systems remains the most reliable verification available.

The broader shift the conference was describing has a direct implication for how DiligenceVault thinks about what it is building. Trust in allocation is moving from disclosure to verifiability. It is no longer sufficient for a manager to say what they do. Allocators and regulators increasingly want to see the structure behind the statement: the data, the workflow, the audit trail, the consistency over time. A purpose-built diligence data layer does not replace judgment. It gives judgment something clean and traceable to work with.

Overview Valuation question Expense transparency Outsourcing ODD cadence Manager best practices AI in ODD

Governance Is the Differentiator

Across all three tracks — AI, risk management, and ODD — the same theme kept surfacing. AI is accelerating capabilities. Regulation is raising expectations. ODD is becoming sharper and less forgiving. The firms that win will not just adopt new tools. They will build structured, transparent, and well-governed operating models that can stand up to scrutiny from investors and regulators alike.

The sponsor stack at GAIM Ops told the same story from a different angle. Every service category in that room — from audit and legal to data infrastructure, compliance surveillance, and diligence platforms — is making a version of the same bet: the operational infrastructure of alternatives is being rebuilt, and the firms that own the structured data layer at the center of that rebuild will compound their value as AI makes clean, permissioned data more useful.

The firms that are ahead treated data quality and process structure as prerequisites, not afterthoughts. They built the foundation before the tools. The ones still struggling built the tools first and are now discovering that the foundation was the hard part.

The industry is moving from trusting processes, to trusting data, to verifying everything. That shift is redefining where value and control sit in the operating model.

Frequently Asked Questions

GAIM Ops Cayman 2026

What were the key themes at GAIM Ops Cayman 2026?

Three themes dominated: AI adoption in alternative investment operations (wide but shallow, with significant gaps between leaders and laggards), risk management and SEC examination readiness, and operational due diligence becoming more intrusive and continuous. A fourth theme — the competition to own the system of record for alternatives operations — was visible in the sponsor mix across every service category.

How is AI changing operational due diligence in 2026?

AI is appearing in ODD in two ways: as a subject of inquiry (allocators are now asking managers how they use AI, who has access, and what governance exists) and as a tool ODD practitioners deploy themselves. Key risks include AI-generated DDQ responses containing wrong interpretations of the manager's own policies, AI-generated compliance policies that were never implemented, and deepfake risk in remote verification. Several allocator teams have responded by returning to in-person site visits as the most reliable verification available.

What are SEC examiners focused on in 2026?

SEC examination activity in 2026 is focused on AI and technology risk, off-channel communications, valuation practices in private markets, and conflicts of interest. Best practices include running internal mock exams, maintaining a living exam-readiness file with current policies and training records, presenting proactive walkthroughs of known risk areas, and ensuring CEO, COO, and CCO are present and aligned during examinations.

What does the GAIM Ops Cayman 2026 sponsor list reveal about the industry?

The sponsor mix — spanning audit, legal, fund administration, custody, data infrastructure, compliance surveillance, ODD platforms, verification, valuation, and retailization — reflects a competition to own the system of record for alternative investment operations. Every major service category had multiple firms arguing that the current operational infrastructure of alternatives was built for a different era. The presence of AI-native compliance firms, verification specialists, and retailization infrastructure alongside traditional service providers signals that the operating model of alternatives is being actively rebuilt.

What ODD best practices were discussed at GAIM Ops Cayman 2026?

ODD best practices discussed include quarterly questionnaires anchored to a heat map of changes for open-end funds, onsite visits every 12–18 months, background checks updated every 2–3 years with some allocators running ongoing checks, and formal veto authority or clear escalation paths for the ODD function. Non-negotiable disqualifiers cited include insufficient ownership transparency, undisclosed background check findings, no business-level insurance, and significant discrepancies between manager statements and fund documents.

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