Risk Management for Prediction Market Platforms

Risk management in prediction platforms is broader than fraud prevention. Teams must manage abuse behavior, infrastructure resilience, and outcome-settlement integrity at the same time.

Market abuse controls

Deploy surveillance logic for abnormal order patterns, coordinated account activity, and suspicious timing around news events. Escalation paths should be automated, not ad hoc.

Exposure and limit framework

Define user-level and market-level exposure caps. Dynamic controls are useful during highly volatile windows when fixed limits become ineffective.

Settlement integrity

Publish resolution rules before market launch and attach source hierarchy for edge cases. Dispute handling should follow documented timelines and approval checkpoints.

Operational resilience

Risk teams need system health dashboards, feed-failure fallback logic, and planned degradation modes to keep markets orderly during outages.

Governance model

Assign responsibility by function: product for market design, risk for control logic, operations for response execution, and legal/compliance for policy boundaries.

What good looks like

A mature risk stack catches abuse early, resolves disputes predictably, and protects user trust during high-attention events.