By Ian Salmon, Head of Product Marketing, Adaptive.
Prediction markets have moved from the edges of the financial ecosystem into a space that increasingly resembles regulated market infrastructure. What began as a retail phenomenon around political events and sports outcomes has evolved into a sector attracting institutional capital, established exchanges and serious regulatory attention. The pace of that shift has caught many observers by surprise, and it is now reshaping the way technology providers think about what exchange infrastructure needs to deliver.
Recent months have seen traditional exchanges partnering with prediction market operators, new institutional access layers emerging, and regulators in the EU, Singapore and Latin America beginning to issue statements or review frameworks for this activity. The regulatory conversation is no longer confined to the United States, and the commercial conversation is no longer confined to retail. For technology providers supporting this market, the question is how to build platforms that can launch quickly enough to capture the opportunity, while meeting the resilience, regulatory and performance standards that institutional participation demands.Event contracts: A market taking shape along multiple tracks
One of the more striking features of the current prediction markets landscape is that it is not consolidating around a single model. Several distinct operating structures are emerging in parallel, each with its own regulatory pathway, commercial logic and participant base.
A first group of venues has sought direct regulatory approval as trading venues in their own right, building out full exchange-style infrastructure under CFTC oversight in the US or equivalent frameworks elsewhere.
A second operates through existing clearing relationships, settling trades through established futures commission merchants rather than seeking venue status directly. A third comprises established exchanges themselves, which are beginning to explore whether prediction market functionality can be integrated into existing platforms, either to capture retail flow or to protect against disintermediation. Alongside these, institutional access providers are building the OTC liquidity, collateral management and workflow layers that allow regulated participants to engage in a way that fits their existing risk and compliance frameworks.
The existence of these parallel tracks matters for infrastructure discussions. It suggests that the technology providers serving this market will not be building for a single standardised model, but for a range of business designs with different requirements around regulation, clearing, settlement and participant access.
Why time-to-market is the defining constraint for event contracts
In traditional exchange launches, the timeline is typically shaped by regulatory approval processes, participant onboarding and the build cycle of the underlying technology. Commercial urgency matters, but the rhythm of the project is rarely dictated by external events.
Prediction markets are different. Much of the commercial opportunity is tied directly to specific moments in the calendar, whether that is a major sporting event, an election cycle or a geopolitical flashpoint. An operator that is not live before those events does not capture the liquidity window they create. Missing one cycle may mean waiting months for the next comparable opportunity, by which point a competitor may have established the participant relationships and brand recognition that are difficult to displace.
That dynamic changes the nature of the technology decision. Time to market is not simply a commercial preference; it becomes a defining constraint on how the platform can be built. Multi-year development programmes of the kind that have historically been common in exchange technology are difficult to reconcile with a market in which the window of opportunity may be measured in weeks or months. Yet the participants these platforms are trying to attract – regulated institutions, established clearing members or sophisticated retail intermediaries – are not willing to engage with infrastructure that cuts corners on resilience, performance or operational integrity. The challenge is therefore to compress the build timeline without compromising the standards that make the platform credible.
Robustness is not negotiable
It would be a misreading of the current moment to assume that speed is the only consideration. Regulators assessing prediction market operators apply the same core tests they would apply to any trading venue: high availability, deterministic behaviour under stress, clear audit trails, appropriate risk controls and the operational resilience to recover cleanly from disruption. Operational resilience frameworks such as DORA in Europe and equivalent regimes elsewhere apply regardless of asset class, and regulators in newer prediction market jurisdictions are drawing on similar principles.
The always-on character of many prediction markets adds another layer of complexity. Contracts tied to global events cannot easily pause for maintenance windows or scheduled downtime, which means availability expectations are closer to those of a 24/7 digital asset venue than a conventional equities exchange. For technology providers serving this market, that combination – exchange-grade robustness, delivered on a compressed timeline, for operators who may themselves be relatively new organisations – is a demanding brief. It is not one that is well served by either end of the traditional build-buy continuum.
Speed, IP ownership and the accelerator path
Operators looking at how to build their platforms generally encounter two familiar options:
- A fully custom build offers complete control over the architecture, the roadmap and the underlying intellectual property, but is hard to square with the timelines that prediction markets demand.
- An off-the-shelf vendor platform can in principle accelerate launch, but typically ties the operator into someone else’s roadmap, product cadence and design decisions. In a market that is still defining itself, that loss of control over the platform trajectory is a significant strategic cost.
A third approach is increasingly relevant. An accelerator model – in which the operator builds on a proven, production-grade backbone with configurable components, but retains ownership of the platform IP and control over the roadmap – offers a route that combines speed with architectural independence. This is not a new idea in exchange technology, but the specific demands of prediction markets make it particularly well suited to the sector.
The practical implication is that operators can go live quickly on infrastructure that has already been validated in regulated trading environments, while still being able to differentiate on contract design, participant experience, data products and commercial model. They are not competing with peers on identical vendor infrastructure, and they are not carrying the full burden of building an exchange platform from the ground up.
Nimbleness, data and the institutional value layer
The other characteristic that distinguishes prediction markets from more established venues is the need for continuous product innovation. New contracts have to be designed, listed and operationalised at a pace that reflects the speed of real-world events. A rigid platform that cannot accommodate new contract types, new settlement logic or new data feeds without significant rework will struggle to keep up.
Data and analytics sit alongside this as a strategic consideration rather than a secondary feature. For institutional participants, the product of a prediction market is not simply the ability to take a position; it is the signal that the market produces. Implied probabilities, sentiment shifts and crowd-aggregated forecasts are potentially valuable inputs into risk management, portfolio construction and research workflows. Platforms that can capture, distribute and integrate that data at the quality institutional users expect will have a more durable value proposition than those that treat data as an afterthought. That has architectural consequences: high-fidelity data capture, real-time and analytical distribution, and integration straightforward enough that the data becomes genuinely usable rather than sitting in a separate silo.
Prediction Markets – what operators should look for
For operators weighing build decisions in this segment, the practical requirements are becoming clearer. A platform built for prediction markets needs to:
- Deliver exchange-grade resilience and deterministic performance from day one, regardless of the compressed build timeline.
- Support rapid contract launch and adaptation as the market evolves, without requiring structural rewrites.
- Preserve the operator’s ownership of platform IP and roadmap, so that differentiation remains possible as the sector matures.
- Integrate cleanly with clearing, settlement, data distribution and participant workflows, including institutional connectivity requirements.
- Accommodate the regulatory expectations of multiple jurisdictions as the market continues to expand beyond its initial US footprint.
None of these requirements is exotic in exchange technology terms. What is new is the combination: delivering all of them together, on a timeline that is measured in months rather than years, for operators who are often building under commercial pressure while the regulatory picture is still evolving around them.
A market still finding its shape
Prediction markets remain an emerging sector, and it would be premature to assume that the current operating models, regulatory frameworks or participant structures will be the ones that prevail. What seems increasingly clear, however, is that the infrastructure decisions being made now will shape which platforms are positioned to capture institutional flow as the market matures. Operators that manage to combine speed to market with institutional-grade robustness, architectural flexibility and meaningful control over their own platform trajectory will be best placed to compete.
The wider exchange technology debate – balancing resilience with adaptability, scale with agility, standardisation with differentiation – is playing out in prediction markets in a particularly concentrated form. For the operators building in this space, and for the technology providers supporting them, the stakes of getting that balance right are rising as the sector scales.
These themes will be explored further at A-Team Group’s upcoming TradingTech Summit, New York, where venue operators, technology providers and market participants will discuss how prediction market infrastructure is evolving and what it means for the broader exchange technology agenda.
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