Regulatory Considerations for Banks Entering Prediction Markets: Compliance and Market-Making Risks

Hook: Why your board should worry when a bank announces interest in prediction markets

Boards and risk committees at large financial institutions face a familiar pain: new product opportunities that promise revenue and client engagement—but also create ambiguous regulatory and market-making exposure that can produce outsized legal, capital, and reputational cost if mishandled. Prediction markets combine elements of trading, gambling, derivatives, data products, and sometimes tokens. For a bank the size of Goldman Sachs, a public exploration of prediction markets (reported in January 2026) signals an appetite for innovation—but also triggers a checklist of complex regulatory, compliance and market-making questions that must be answered before product launch.

The state of play in 2026: regulators, technology, and market realities

By 2026 prediction markets have evolved from retail novelty to institutional pilots. Major banks, hedge funds and trading venues are experimenting with event-based contracts that settle on economic indicators, corporate outcomes, and geopolitical events. Regulators in major jurisdictions — including the U.S. Securities and Exchange Commission (SEC), the Commodity Futures Trading Commission (CFTC), and European authorities implementing post-MiCA frameworks — have increased scrutiny. Two trends are decisive:

• Regulatory convergence on substance-over-form. Authorities look at the economic characteristics of a contract (transfer of risk, leverage, investor protection) rather than labels like “prediction” or “bet.”
• Technology maturation. Oracles, hybrid on-chain settlement, and institutional custody reduce operational frictions, but add new vectors for model risk and governance scrutiny.

What regulators are watching (late 2025 — early 2026)

• Securities vs. derivatives vs. gambling classification: If a contract pays based on corporate earnings, stock price, or economic indicators, will it be treated as a security, a swap, an exchange-traded derivative, or an unlawful gambling product? Classification drives licensing, disclosure, and capital rules.
• Market integrity: Surveillance for manipulation, wash trading, insider trading, and front-running—especially where outcomes depend on scheduled public data or corporate actions.
• AML/KYC and sanctions: Cross-border flows in crypto-linked markets and tokenized positions have made AML/KYC controls a priority.
• Consumer protection and suitability: Retail access to binary-like products draws heightened scrutiny on disclosures, suitability assessments, and cooling-off mechanisms.

“Prediction markets look super interesting,” Goldman Sachs CEO David Solomon said in a January 2026 call — but interest opens a wide regulatory door that large banks cannot ignore.

Top legal and compliance questions for bank leadership

Before spinning up a trading desk, product team or white-label platform, senior legal and compliance teams must resolve a set of foundational questions. Each answer materially affects licensing, capital, tax, and operational requirements.

1. Jurisdictional product classification

Map each proposed contract type to regulatory regimes across key jurisdictions. Required outcomes include:

• Whether the contract is a security, commodity derivative, or gambling/betting product.
• Whether it falls within the scope of existing exchange or swap execution facility rules (e.g., DCM/SEF in the U.S.).
• Which licensing pathways (broker-dealer, futures commission merchant, authorized betting operator, crypto-asset service provider) are necessary.

2. Retail vs institutional distribution strategy

Decide early whether the product will be offered to professional counterparties only, or to retail clients. Retail distribution triggers suitability, disclosure, and often product intervention rules (e.g., leverage caps, marketing limits).

3. Settlement and reference data governance

Contracts that settle on third‑party oracles or public releases require documented, auditable processes for source selection, redundancy, and dispute resolution. Regulators expect robust governance for reference data — delays or incorrect settlement are regulatory and reputational risks.

4. Market surveillance and reporting

Design surveillance tailored to prediction-market behaviors: rapid price discovery ahead of scheduled events, cross-market arbitrage, and potential use of non-public information. Reporting obligations (trade reporting, large position reports) must be mapped to local rules and exchange requirements.

5. Tax treatment and reporting

Tax classification (capital gains, ordinary income, gambling winnings) affects withholding, 1099/B reporting, and platform tax reporting infrastructure. Cross-border tax withholding for tokenized payouts must also be planned.

Market-making challenges specific to prediction markets

From an execution and trading desk perspective, market making in prediction markets looks familiar but contains distinctive risks and operational nuances.

Inventory and hedging complexity

Prediction contracts often have binary payoff profiles that create non-linear inventory exposures. Hedging these exposures with standard instruments (options, futures, swaps) can be imperfect or impossible when the underlying event is non-financial (e.g., election outcome, FDA approval). That leads to:

• Higher adverse selection risk—sophisticated participants will trade against uninformed liquidity providers if hedging costs are mispriced.
• Requirement for bespoke hedges or synthetic replication strategies, which increase operational and model risk.

Capital and regulatory capital treatment

Banks’ market-making books attract capital charges under Basel III/IV. Novel contracts may be assigned high risk weights or require internal model approval. Expect additional capital overlays for model risk, incremental default risk and wrong‑way risk associated with event concentration.

Latency, front-running and fair access

Prediction markets that settle quickly after public announcements are vulnerable to latency arbitrage and event-time front-running. Market-makers must implement controls (pre-announce windows, time-stamped submissions, latency-equalization) and document them for regulators.

Liquidity management and stress testing

Design stress tests that model event clustering (multiple high-impact events within short windows), thin liquidity scenarios, and forced unwind costs. KPIs should include bid-ask spread under stress, maximum adverse inventory, and expected time-to-liquidate positions without market impact.

Operational and tech compliance requirements

Prediction markets are technology-intensive. Compliance must be embedded into engineering, product and operations from day one.

Oracle and smart contract risk controls

If using on-chain settlement, implement multi-source oracles, fallback manual settlement rules and timelocks. Legal agreements must define dispute resolution, force majeure and finality norms. Expect regulators to demand deterministic settlement procedures and audit trails.

Auditability and recordkeeping

Keep granular logs: order books, time-stamped price feeds, matching engine decisions, and oracle inputs. Retain data in accessible format for regulatory requests and internal reviews.

Surveillance powered by AI — and the governance around it

AI-based surveillance can detect nuanced manipulation patterns but introduces model explainability and governance requirements. Compliance teams must be able to explain detection logic and ensure the system does not create false positives that suppress legitimate trading.

Practical, actionable roadmap for banks considering a prediction market product

Below is a pragmatic, step-by-step playbook that legal, compliance and trading leaders should follow when evaluating and launching prediction market initiatives.

1. Preliminary legal mapping (0–3 months)
   • Engage external counsel with structured-products, gaming law, and crypto experience.
   • Map each prospective contract to U.S., EU, UK and top APAC regimes.
   • Decide distribution target (institutional-only pilot vs. retail product).
2. Regulatory engagement & sandboxing (3–9 months)
   • File early engagement requests with relevant regulators or join official sandbox programs.
   • Run a restricted pilot with accredited counterparties and report transparently to the regulator.
3. Compliance program build (6–12 months)
   • Create policies for AML/KYC, transaction monitoring, best execution, conflict-of-interest management and data governance.
   • Establish an event-data governance playbook (oracle selection, redundancy, dispute resolution).
4. Market-making and risk controls (6–12 months)
   • Design hedging strategies and capital allocations; model stress scenarios and back-test on historical event datasets.
   • Develop real-time inventory limits, automated quoting controls, and kill-switch mechanisms.
5. Operational readiness and launch (12–18 months)
   • Complete end-to-end testing including settlement fail scenarios, oracle outages, and cross-border flows.
   • Implement reporting pipelines for trade reporting, tax forms and regulatory surveillance feeds.

Compliance checklist: what regulators will ask for in examinations

Expect regulators to audit for these items. Be ready to produce documentation and quantitative metrics.

• Product legal memos mapping to securities/derivatives/gambling regimes.
• AML/KYC rules, sanctions screening results, and suspicious activity report (SAR) thresholds relevant to event markets.
• Reference data governance: oracle selection criteria, SLA metrics and dispute records.
• Market surveillance logic, alerting thresholds and remediation workflows.
• Stress testing results, VAR, expected shortfall measures and scenario analyses specific to event clustering.
• Client onboarding and suitability frameworks for retail participants.
• Tax reporting processes and cross-border withholding procedures.

Case studies and illustrative scenarios

Two short vignettes highlight likely regulatory flashpoints.

Scenario A: Election-linked contract offered to U.S. retail clients

A national bank offers binary contracts that pay on U.S. election outcomes. Regulators raise concerns about state gambling laws, voter influence, and potential for market manipulation when outcomes can be impacted by last-minute non-public actions. Outcome: the bank pauses retail distribution, refocuses on institutional counterparties, and files for an advisory opinion while enhancing disclosure and removing leverage.

Scenario B: Corporate earnings contract that settles to an earnings surprise metric

Contracts tied to quarterly earnings releases create insider-trading exposure. The bank’s surveillance flagged unusual pre-release positions by employees. Outcome: the firm implemented stricter Chinese walls, expanded employee trading blackouts, and established pre-trade surveillance for positions near material non-public information (MNPI) windows.

Metrics and KPIs for an institutional prediction market business

To monitor product and regulatory health, track a mix of market, risk and compliance metrics:

• Liquidity KPIs: average bid-ask spread, depth at top-of-book, time-to-fill for standard lot sizes.
• Risk KPIs: inventory VaR, max intraday drawdown, hedging slippage percentage.
• Compliance KPIs: AML alerts per 1,000 trades, SAR filing rate, time-to-resolve surveillance alerts.
• Operational KPIs: oracle SLA uptime, settlement fail rate, mean time to reconcile disputed settlements.

Final considerations: governance, reputation and strategic options

Large banks should treat entry into prediction markets as a cross-functional initiative—not a single desk project. Governance must include legal, compliance, risk, product, operations and public affairs. Options to mitigate risk include:

• Launching institutional-only pilots to limit retail exposure while refining models and surveillance.
• White-labeling the technology to licensed betting operators or regulated venues, shifting regulatory risk while capturing fee revenue.
• Forming strategic partnerships with regulated crypto-exchanges or licensed derivatives venues that already have market infrastructure in place.
• Choosing product design levers that reduce regulatory friction: longer settlement windows, no leverage, restrictions on event types (no political outcomes in sensitive jurisdictions), and robust disclosure frameworks.

Actionable takeaways

• Do a regulatory-first product design: Map legal classification before building tech. Classification determines almost every downstream requirement.
• Limit initial exposure: Start with institutional counterparties and accredited investors to reduce retail consumer-protection issues.
• Build surveillance early: Embed trade surveillance, oracle monitoring, and AI governance into the MVP—not as an afterthought.
• Stress test for event clustering: Design liquidity and capital plans for adjacent-event stress where multiple outcomes converge in short periods.
• Engage regulators proactively: Early, documented dialogue and sandbox participation materially reduce launch friction and regulatory surprise.

Why this matters to investors, compliance officers and platform buyers in 2026

Prediction markets offer differentiated client products and new revenue streams, but they sit at an intersection of trading, data and public policy. For investors and platform buyers, the regulatory posture of the provider (licensed? robust surveillance? clear settlement governance?) is now a primary element of vendor due diligence. For compliance officers, the complexity is operational: a misclassified contract, a weak oracle or an insufficient AML program can create outsized legal and reputational fallout.

Call to action

If your institution is evaluating prediction markets, start with our custom checklist and workshop: we map product designs to likely regulatory regimes, produce a market-making risk assessment and draft the compliance program blueprint you need for regulator engagement. Download the prediction-market compliance playbook from hedging.site or request a tailored advisory session to move from concept to compliant pilot with confidence.

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