Five years ago, the conventional wisdom at most asset managers and hedge funds in the $500M-$5B AUM range was: build your quant infrastructure in-house. The reasoning was that quant infrastructure was foundational, that core capabilities should be proprietary, and that the cost of external dependencies in a regulated investment business was unacceptable.
That conventional wisdom has shifted. In 2026, a meaningful percentage of mid-sized managers are now outsourcing the foundation layer of their quant infrastructure (data integration, valuation engines, portfolio analytics, risk systems) and reserving in-house engineering exclusively for alpha generation. This article looks at why the shift happened, what's actually being outsourced, and what the strategic implications are for managers thinking about their own infrastructure decisions.
What changed in the build-vs-buy calculation
Three structural factors:
Factor 1: Available external infrastructure became materially better. The quant infrastructure vendors that existed in 2018 mostly built thin wrappers around Bloomberg and Refinitiv data feeds. They were not impressive technology businesses. The current generation of infrastructure vendors (including, full disclosure, ours, Arizet's institutional offering) build genuinely sophisticated platforms that handle multi-source data integration, real-time valuation across instrument types, scenario analysis, and risk decomposition at a level that most internal teams cannot match.
Factor 2: The cost of building in-house increased dramatically. Senior quant developer compensation in the major financial centers has roughly doubled since 2019. A serious quant infrastructure team today costs $3M-$8M per year in fully-loaded compensation, before considering data, infrastructure, and management overhead. For mid-sized managers, this is no longer a marginal cost.
Factor 3: Cycle times got faster. The market now demands faster iteration on alpha strategies, faster integration of new alternative data sources, and faster response to regime changes. Managers that have to wait 6-12 months for internal infrastructure projects to deliver new capabilities are losing ground to managers that can deploy in weeks.
The combined effect: outsourcing the foundation layer is now cheaper, technically superior, and faster than building in-house for managers below a certain scale threshold. The threshold is approximately $3-5B AUM; above that scale, the economics of building start to make sense again because the fixed costs amortize across more capital.
What managers are actually outsourcing
Not everything. The decision is granular. From conversations across our institutional partners, here's the typical pattern:
| Layer | Typical decision |
|---|---|
| Alpha generation models | Build in-house. This is the proprietary edge. |
| Backtesting infrastructure for own strategies | Mixed. Some build, some buy. |
| Multi-asset valuation engine | Increasingly buy. The "valuation correctly across instrument types" problem is hard and well-solved by specialists. |
| Data integration (market data, fundamental, alternative) | Increasingly buy. Maintaining 30+ data integrations is a full-time team problem. |
| Portfolio analytics + attribution | Increasingly buy. Strong vendor ecosystem. |
| Risk decomposition + scenario analysis | Increasingly buy. Same as portfolio analytics. |
| Process automation (NAV, reconciliation, reporting) | Almost always buy. Commoditized infrastructure. |
| Compliance and regulatory reporting | Almost always buy. |
The principle: own the layer where your differentiation lives; outsource everything else. For most quant managers, the differentiation is the alpha-generation model and the data sources they've built proprietary insight into. Everything underneath that. The infrastructure that turns positions into reports, reports into risk decompositions, decompositions into actionable views. Is increasingly handled by specialist vendors.
The objection that doesn't survive scrutiny
The most common objection we hear from managers considering outsourcing: "We can't have a critical dependency on an external vendor for our core operations."
The objection sounds reasonable but doesn't survive analysis. Most managers already have critical dependencies on Bloomberg, Refinitiv, MSCI, S&P, FactSet, IHS Markit, prime brokers, custodians, fund administrators, and dozens of other external vendors. The question isn't whether to have external dependencies. Every modern manager has them by the dozen. The question is which dependencies make sense.
The structural reasons a quant infrastructure vendor is a reasonable dependency:
- The vendor's incentive is to maintain service quality. Their entire business depends on it. An internal team can have a key person leave with little notice; vendors have institutional continuity.
- The vendor sees patterns across many managers and can ship improvements that benefit all customers. Internal teams can only build what their specific firm needs, slower.
- Switching costs are manageable if the vendor uses standard data formats and provides export capabilities. Which serious vendors do.
The objection that does survive scrutiny: "Our alpha is in our data and our models, and we don't want vendor systems seeing either." That's a legitimate constraint, and it's why the foundation layer (which doesn't see proprietary alpha logic) gets outsourced while the alpha-generation layer stays internal.
What good outsourced infrastructure looks like
Across the vendor ecosystem, the dimensions that distinguish serious infrastructure from amateur infrastructure:
- Multi-source data integration at production quality. Not a wrapper around Bloomberg; an actual data layer that handles market data, fundamental data, alternative data, with appropriate time-series semantics, point-in-time integrity, and corporate-action handling.
- Valuation across instrument types. Not just equities; serious coverage of fixed income, FX, derivatives, structured products. Most amateur vendors break down on anything beyond vanilla equities.
- Open architecture. The vendor's platform should integrate with your internal systems, not require you to use only their UI. Programmatic API access is non-negotiable.
- Audit trails and regulatory compliance. Every calculation should be reproducible, every change should be logged, every output should be exportable for regulatory inspection.
- Reasonable economics. Pricing that makes sense relative to the cost of building the same thing in-house.
The Arizet institutional offering, for full disclosure, addresses these dimensions and several others. The broader vendor ecosystem has 10-15 credible options across various scope subsets.
The case for keeping infrastructure in-house
Not every manager should outsource. The cases where in-house infrastructure makes sense:
- Very large managers (>$5B AUM) where the fixed costs of internal infrastructure amortize across enough capital that the per-dollar cost is competitive with vendor pricing.
- Strategies with extremely specialized data or computation requirements that vendors don't serve well. For example, certain microstructure or HFT use cases.
- Managers whose differentiation is technology itself rather than insight (a small subset of quant firms).
- Operational concentration concerns. For example, managers running strategies where vendor outages would create material business risk, and who can't tolerate even brief downtime.
For managers outside these categories (which is the majority of $500M-$5B AUM funds) the outsourcing case is strong and growing stronger.
What this means for the broader industry
The shift toward outsourcing core infrastructure has several knock-on effects:
- Lower barriers to launching a quant fund. A two-person team with a good model and access to vendor infrastructure can spin up a credible institutional operation faster than was possible five years ago. Expect more new fund launches in the niche segment.
- More specialization in alpha. If infrastructure is commoditized, the differentiation has to come from somewhere else. Typically deeper specialization in particular markets, strategies, or data sources.
- Faster idea-to-production cycles. Alpha researchers no longer need to wait on engineering teams for infrastructure changes. They iterate against existing vendor APIs.
- Vendor concentration risk for the industry. If too many managers depend on the same handful of vendors, vendor outages could create systemic issues. This is a structural concern that hasn't been tested yet.
The bottom line
For managers below ~$5B AUM, the build-vs-buy calculation for quant infrastructure has decisively shifted toward buy in the last 24 months. The vendors got better, in-house costs got higher, and cycle time pressure increased. Managers that haven't reconsidered their infrastructure approach in the last 12 months are likely operating on assumptions that no longer hold.
Our institutional offering at Arizet is purpose-built for this category. Engagements typically start with a 60-minute diagnostic conversation with our team to identify where the highest-leverage opportunities are. We're not the right answer for every manager (particularly very large funds or specialized HFT operations) but for the mid-sized quant managers who are the bulk of the market, we're worth a serious look.