Every trading day, hedge funds depend on proprietary software their teams design, build, and continually improve, yet many asset managers have never evaluated whether the technology behind their investment process could generate a tax credit. Internal Revenue Code (IRC) Section 41, the federal credit for increasing research activities, rewards qualifying development and improvement work of this kind — including execution algorithms, research platforms, data pipelines, machine-learning (ML) models and risk engines with no off-the-shelf equivalent.
The opportunity to claim credits is growing as systematic and quantitative managers deepen their investment in engineering, data science, alternative data and artificial intelligence (AI). Purchasing technology or data is not enough on its own, because the credit depends on whether the firm incurs eligible wages and other costs while resolving technological uncertainty through a process of experimentation. For many firms, a multi-year opportunity is sitting unexamined inside the technology budget.
At a Glance
- Hedge funds are among the most technology-intensive, and most underclaimed, participants in the federal research credit.
- The real value of the credit depends on entity structure, software classification, and cost tracing, not headline technology spend.
- A complimentary opportunity assessment can quantify the benefit and identify open issues before any commitment.
Why Fund Development Work Qualifies
The Section 41 credit is not limited to laboratories or groundbreaking inventions. Evolutionary improvements to software and processes qualify routinely. Each business component must satisfy the four-part test:
- Permitted Purpose: Development or improvement of function, performance, reliability or quality.
- Technological in Nature: The work fundamentally relies on computer science, engineering, physical science or biological science.
- Technological Uncertainty: Uncertainty exists at the outset regarding capability, method or appropriate design.
- Process of Experimentation: The team identifies alternatives and evaluates them through modeling, simulation, testing, or systematic trial and error.
An uncertain investment outcome is not, by itself, technological uncertainty. The qualifying inquiry concerns uncertainty in how the underlying software, model, data architecture, or computational method can be designed or developed.
Qualifying development arises across the modern fund through:
- Systematic and Algorithmic Trading: Execution algorithms, smart order routers, and order and execution management systems engineered for performance and latency.
- Quantitative Research and Alpha Generation: Factor models, statistical-arbitrage strategies, and ML models, including natural language processing (NLP) applied to filings and news.
- Backtesting and Simulation: Event-driven engines, market-impact, and transaction-cost models and point-in-time data infrastructure.
- Market and Alternative Data Engineering: Ingestion, normalization, streaming pipelines, entity resolution, feature engineering and point-in-time controls.
- Risk, Pricing and Portfolio Systems: Real-time risk engines, factor and value-at-risk models, derivatives pricing, and portfolio optimization.
- Research Computing: Scalable environments, graphics processing unit (GPU) and high-performance computing, parallel back tests, and infrastructure-as-code supporting experimentation.
- Trade Lifecycle and Operations: Portfolio, order and reconciliation systems, and engineered integrations using Financial Information eXchange (FIX) and application programming interfaces (APIs).
- Digital Assets and New Markets: Venue connectivity, on-chain data, and systems adapted to changing market structures.
Internal-use Software Requires a Careful Analysis
Many proprietary trading, execution, and market-connectivity systems perform a fund’s core investment function or enable interaction with third parties. Depending on the facts, those systems often fall outside the internal-use software rules or qualify under a regulatory exception. Other systems, particularly software supporting financial management, compliance, administration, or other general business functions, require a separate internal-use software analysis and may be subject to the heightened innovation standard.
Classification depends on the intended use of the software at the beginning of development and the surrounding facts, not simply on the system’s importance to revenue generation. Mixed-use platforms also require a functional analysis and allocation.
The Entity That Builds the Technology Matters
Hedge fund structures are rarely simple. The investment manager, general partner, domestic and offshore funds, technology affiliates, and employee entities are often not the same taxpayer. A proper assessment identifies where the employees, vendor contracts, intellectual property, cloud accounts, development activity, and tax liability reside before calculating the benefit.
Common-control rules, partnership provisions, foreign-research exclusions, and owner-level limitations affect computation and utilization. A headline credit estimate is meaningful only once the legal-entity structure and tax posture have been mapped.
The AI Inflection Point
AI development presents some of the most significant qualified-research opportunities available to a fund today, but the line is clear: Adopting a tool is not research, but building or improving one often is.
|
Often Qualifies |
Requires Caution |
|
Designing or improving model architecture |
Purchasing an AI subscription |
|
Experimental feature engineering |
Routine prompt use |
|
Training or fine-tuning models to resolve technical uncertainty |
Deploying a commercial model with no technological uncertainty |
|
Evaluating alternative methods or architectures |
Routine monitoring after uncertainty is resolved |
|
Improving performance, scalability or reliability |
Production operation once the design question is settled |
|
Building data pipelines needed for experimentation |
Data labeling or cleansing with no direct link to experimentation |
The wages, contractor costs, and eligible computing behind the left column are the potential qualified research expenses. The right column generally is not, absent additional facts.
Alternative Data Is a Lead Indicator, Not Automatically a QRE
High alternative data spending is a strong indicator of substantial engineering and experimentation around ingestion, normalization, entity resolution feature development, validation and point-in-time controls. The recurring purchase price of a data feed or license, however, is not itself a qualified research expense (QRE). The stronger opportunity lies in the eligible wages and development costs of building and experimentally improving the systems that use the data.
Which Costs Can Qualify
Once the activities qualify, the analysis focuses on four cost categories:
- W-2 wages for employees performing, directly supervising or supporting qualified research.
- 65% of eligible payments to third parties performing qualified research on the taxpayer’s behalf.
- Amounts paid for the right to use computers in conducting qualified research, subject to specific requirements.
- Supplies consumed in qualified research, excluding depreciable property and other excluded items.
Cloud and high-performance computing charges require particular care. Eligibility turns on the service arrangement, the underlying resource, and the ability to connect usage to qualified development and experimentation. Software subscriptions, data licenses, production hosting, managed services, and dedicated hardware are not automatically qualified computing costs.
Third-party development costs also require contract-level review. Eligibility depends on who bears the economic risk, who retains substantial rights to the research, where the work is performed, and whether the vendor is conducting qualified research on the taxpayer’s behalf. External developers, quantitative consultants, staff augmentation firms, and offshore teams can produce different results under these rules.
How Is the Research & Development (R&D) Tax Credit Calculated?
To claim the R&D tax credit, taxpayers must identify the amount of qualified research expenses (QREs) in prior years to calculate a base amount of qualified spending that must be overcome before current-year spending becomes eligible.
Section 174A Makes an Integrated Review More Important
New Section 174A guidance permits current deductions for domestic research or experimental expenditures paid or incurred in tax years beginning after December 31, 2024. Taxpayers may instead elect to capitalize qualifying domestic expenditures and amortize them over at least 60 months. Foreign research expenditures remain subject to capitalization and 15-year amortization.
Transition provisions allow recovery of unamortized domestic expenditures from 2022 through 2024. Certain eligible small business taxpayers may also elect retroactive treatment, subject to gross-receipts, tax-shelter, return-procedure, partnership and Section 280C considerations. A fund group revisiting those years for deduction purposes should evaluate the Section 41 credit, entity structure, and state treatment together.
The 2026 Form 6765 Reporting Change
For tax years beginning after 2025, Section G of Form 6765 requires business-component information, subject to the form’s applicable instructions and exceptions. For a hedge fund, this raises the importance of defining the relevant systems, models, platforms, and development initiatives, connecting QREs to those business components, and preserving evidence of technical uncertainty and experimentation.
A study built primarily from job titles and broad wage percentages will not provide the level of project detail the return or an examination now requires. The strongest studies map technical evidence and costs to clearly defined business components from the outset.
Form 6765 readiness is not a year-end exercise. It begins with how the firm identifies, documents, and costs its development initiatives throughout the year.
If Your Firm Has Never Claimed
Common misconceptions keep many firms on the sidelines. Research does not need to be groundbreaking. Formal time tracking is not required if defensible allocations are supported through interviews, development records, organizational data and financial information. Claiming the credit does not make an examination inevitable, but the position should be supported by careful eligibility analysis, detailed calculations, and substantiation of the technical uncertainties involved.
A preliminary assessment can start with organization charts, payroll by function, vendor detail, cloud spending, and a high-level inventory of systems and initiatives. Technical discussions focus on development methods, uncertainty, and experimentation, without requiring disclosure of proprietary positions or the economic substance of trading signals.
If You Already Claim: Is the Study Complete and Defensible?
Existing studies often miss qualifying business components, use overly broad project groupings, overlook eligible computing or contractor costs, or fail to align the claim with the legal entities that incurred the expense. The 2026 reporting changes add a timely reason to reassess whether current documentation is sufficiently granular.
A focused second-opinion review tests:
- Whether the correct taxpayer and controlled group were analyzed.
- Whether proprietary, internal-use, and mixed-use software were classified appropriately.
- Whether investment uncertainty was distinguished from technological uncertainty.
- Whether cloud, contractor, and alternative-data-related costs were treated correctly.
- Whether foreign research and offshore development were identified.
- Whether business components and supporting evidence align with Form 6765 reporting.
- Whether open years and state opportunities were evaluated.
Evidence Funds Often Already Have
A defensible study frequently leverages records created in the ordinary course of development, including development tickets, source-control histories, pull requests, model-validation records, backtesting logs, architecture decisions, performance reports, cloud tags, release documentation, vendor agreements and model-governance materials. The goal is to translate existing technical evidence into a clear tax record, not to construct a research process after the fact.
Your Guide Forward
Hedge fund R&D tax credit claims demand more than a generic software study. They require professionals who distinguish investment uncertainty from technological uncertainty, analyze proprietary and internal-use software, trace cloud and contractor costs, navigate fund and management-company structures, and produce business-component documentation that supports Form 6765 and an Internal Revenue Service (IRS) examination.
Cherry Bekaert’s Tax Credits & Incentives Advisory practice works alongside the firm’s Asset Management tax and audit professionals, integrating technical interviews, legal-entity and contract analysis, federal and state calculations, and business-component documentation into a single engagement.
Whether a fund has never evaluated the credit or wants an independent review of an existing study, the first step is a targeted opportunity assessment. Our assessment:
- Estimates the potential federal and state benefit
- Identifies the entities and cost centers that require analysis
- Assesses documentation readiness
- Outlines a study approach designed to minimize demands on investment and technology teams
The assessment also surfaces adjacent Section 174A, state, contract and Form 6765 issues before the firm commits to a full study, giving both the potential benefit and the work required to support it in a single view.
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