Hedge Funds
Operational Due Diligence
Business Advisory
Our ODD experts focus on non‑investment risk—how the firm is run, controlled, and sustained—so leadership can demonstrate institutional-grade readiness to allocators, regulators, primes, and auditors. The advisory program is built to uncover hidden risks, prevent fraud, and prove operational resilience, spanning governance, trade-to-settlement controls, valuation independence, service provider oversight, compliance/AML/KYC, cybersecurity/BCP, and key-person exposure. The approach goes beyond document collection: DDQ verification, management interviews (COO/CFO/CCO/Risk), targeted background/reference checks, and a roadmap for ongoing monitoring rather than “ODD once a year.”
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Allocator-grade ODD blueprint across the full pillar set: Fund structure & governance, operational controls, valuation/IPV, service providers, compliance/legal, technology/cyber/BCP, and team/personnel—translated into an executive risk heatmap and prioritized remediation plan.
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Verification-first diligence: DDQ deep review + on-site/virtual interviews + evidence testing that validates how work actually gets done (trade capture, cash movement, reconciliations, pricing overrides, incident response).
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Emerging-tech defensibility built in: AI governance (model inventory, approvals, human-in-the-loop, audit trails), blockchain controls (custody/wallet governance, on-chain/off-chain reconciliation, proof posture), and quantum readiness (where optimization truly matters and where security needs post-quantum planning).
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Ongoing monitoring strategy for sustainability: Annual refresh cadence, regulatory-change watch, service-provider performance reviews, and “always-ready” evidence expectations—so allocator confidence doesn’t degrade between reviews.
AltsCentralAI Solutions
For executives running lean teams or relying on outsourced functions, the managed model delivers continuous ODD assurance—institutional controls, continuous monitoring, and evidence packaging—without building a large internal operational risk function. The service is designed to keep leadership ahead of allocator questions by maintaining an always-current view of governance, operational processes, valuation discipline, service provider performance, compliance posture, cybersecurity readiness, and key-person risk. AI reduces cycle time and increases consistency; blockchain oversight closes the “digital asset ODD gap”; quantum-ready optimization can be introduced where it directly improves liquidity/collateral decisions and operational resilience.
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Continuous ODD monitoring (not annual fire drills): Always-on controls dashboards, exception thresholds, incident readiness, and remediation tracking across the full ODD pillar set—so issues surface early and are closed with proof.
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Allocator-ready evidence room + DDQ response engine: Curated, current evidence packs (policies, procedures, logs, reconciliations, valuation memos, provider reports, audited financial artifacts) with consistent narrative, version control, and executive sign-off workflows.
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Managed operational controls and provider oversight: Daily reconciliations and break management, cash movement governance, valuation workflows, and formal monitoring of administrators, auditors, primes, and key vendors—turning outsourced operations into a transparent control environment.
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Managed emerging-tech risk and governance: AI usage controlled via model/prompt governance and monitoring; blockchain programs governed through custody/wallet controls and on-chain/off-chain reconciliation; quantum readiness delivered as a practical roadmap and selective optimization capability—without introducing “black box” risk.
Technology Execution & Delivery
A practitioner-led delivery team embeds ODD into the operating fabric so the organization can prove controls continuously, not assemble narratives under pressure. The build concentrates on the pain points that create ODD failures: manual workflows, fragmented data across admin/PB/custodian/OMS/PMS, inconsistent reconciliations, opaque valuations (especially complex/illiquid or digital), weak vendor oversight, and incomplete cyber/BCP evidence. AI is applied to reduce operational friction and improve detection; blockchain integrations eliminate gaps across wallets/venues/protocols; quantum-ready methods are introduced selectively where they improve constraint-heavy decisions without compromising explainability.
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Trade-to-settlement, cash, and position controls—automated and evidenced: Straight-through reconciliations, exception workflows, maker-checker approvals, and immutable logs to reduce errors (“fat finger,” misallocations) and shorten break resolution time.
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Valuation & IPV rigor that stands up to scrutiny: Independent pricing workflows, challenger checks for hard-to-price assets, override governance, and full audit trails—built to withstand allocator focus on consistency, transparency, and independence.
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Compliance/AML/KYC engineered for modern complexity: Normalized transaction monitoring across traditional rails and on-chain activity, identity resolution across entities/accounts/wallets, and case management that packages evidence for exams and investor review.
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ODD-grade AI + cyber controls by design: Controlled AI copilots (DDQ support, incident summaries, exception triage) with strict logging and approvals; cybersecurity/BCP artifacts, access controls, and resilience testing structured to be “audit-ready” at any time—plus quantum-aware security planning where encryption/key management needs a forward roadmap.