The company says clients can connect event outcomes with exposures across asset classes.
The probabilities will feed stress testing, scenario analysis, value at risk and sensitivity workflows.
TS Imagine has added prediction-market probabilities to its institutional risk platform, the company announced Wednesday. Clients can connect defined event outcomes with portfolio exposures and use changing probabilities in stress testing, scenario analysis, value at risk and sensitivity workflows.
TS Imagine provides trading, portfolio management, prime brokerage and risk software to financial institutions. Its latest update is aimed at political, economic, regulatory and geopolitical events that may affect several asset classes at once.
The company has previously expanded its risk technology through AI-based monitoring and margin tools. The prediction-market feature adds an event probability signal to those existing portfolio workflows.
TS Imagine said clients can map those outcomes to positions and sensitivities across asset classes. The related analysis will update automatically when the market-implied probability changes, allowing risk teams to rerun portfolio scenarios without manually replacing the probability input.
The use cases listed by the company include central bank decisions, elections, economic data releases and regulatory changes. TS Imagine did not provide an example portfolio or disclose how a probability change would be translated into shocks for individual instruments.
Prediction markets add a forward looking, event-specific view, TS Imagine Founder and Chief Executive Officer Rob Flatley said. He added that connecting the signal to positions could give clients portfolio-level information as expectations change.
Risk Tooling Moves Beyond Data Feeds
Institutional market providers have spent much of 2026 building connections to prediction markets. In February, Intercontinental Exchange launched its Polymarket Signals and Sentiment tool, which normalizes Polymarket data for professional investors.
Trading technology vendors are also adding execution. In June, Trading Technologies announced Kalshi connectivity for its TT platform, with trading expected to begin in the third quarter. The vendor said clients would receive execution and algorithmic tools similar to those available for other asset classes.
Interactive Brokers took another route in May by combining contracts from Kalshi, CME Group and ForecastEx in a single prediction-markets interface. That system lets clients compare and execute event contracts while tracking the positions alongside conventional investments.
TS Imagine did not identify which prediction markets supply the data. The announcement also did not explain how contracts from different venues are normalized, how thinly traded markets are handled or whether clients can select the events included in their models.
Those details may affect how institutions assess the signal. An Acuiti survey cited in Finance Magnates’ recent coverage found that 57% of respondents viewed regulatory uncertainty as the main obstacle to wider institutional participation in prediction markets.
The announcement contained no pricing information or separate rollout schedule. It also did not say whether the capability is included across TS Imagine’s platform or supplied as an optional data and analytics module.
TS Imagine has added prediction-market probabilities to its institutional risk platform, the company announced Wednesday. Clients can connect defined event outcomes with portfolio exposures and use changing probabilities in stress testing, scenario analysis, value at risk and sensitivity workflows.
TS Imagine provides trading, portfolio management, prime brokerage and risk software to financial institutions. Its latest update is aimed at political, economic, regulatory and geopolitical events that may affect several asset classes at once.
The company has previously expanded its risk technology through AI-based monitoring and margin tools. The prediction-market feature adds an event probability signal to those existing portfolio workflows.
TS Imagine said clients can map those outcomes to positions and sensitivities across asset classes. The related analysis will update automatically when the market-implied probability changes, allowing risk teams to rerun portfolio scenarios without manually replacing the probability input.
The use cases listed by the company include central bank decisions, elections, economic data releases and regulatory changes. TS Imagine did not provide an example portfolio or disclose how a probability change would be translated into shocks for individual instruments.
Prediction markets add a forward looking, event-specific view, TS Imagine Founder and Chief Executive Officer Rob Flatley said. He added that connecting the signal to positions could give clients portfolio-level information as expectations change.
Risk Tooling Moves Beyond Data Feeds
Institutional market providers have spent much of 2026 building connections to prediction markets. In February, Intercontinental Exchange launched its Polymarket Signals and Sentiment tool, which normalizes Polymarket data for professional investors.
Trading technology vendors are also adding execution. In June, Trading Technologies announced Kalshi connectivity for its TT platform, with trading expected to begin in the third quarter. The vendor said clients would receive execution and algorithmic tools similar to those available for other asset classes.
Interactive Brokers took another route in May by combining contracts from Kalshi, CME Group and ForecastEx in a single prediction-markets interface. That system lets clients compare and execute event contracts while tracking the positions alongside conventional investments.
TS Imagine did not identify which prediction markets supply the data. The announcement also did not explain how contracts from different venues are normalized, how thinly traded markets are handled or whether clients can select the events included in their models.
Those details may affect how institutions assess the signal. An Acuiti survey cited in Finance Magnates’ recent coverage found that 57% of respondents viewed regulatory uncertainty as the main obstacle to wider institutional participation in prediction markets.
The announcement contained no pricing information or separate rollout schedule. It also did not say whether the capability is included across TS Imagine’s platform or supplied as an optional data and analytics module.
Damian Chmiel is a Senior Analyst & Editor at Finance Magnates with more than 15 years of experience in the CFD and online trading industry. Active as both a trader and journalist since 2010, he focuses on broker coverage, fintech innovation, and regulatory developments across Europe, the Middle East, and Asia.
His work includes interviews with C-level leaders at major brokerages and fintech platforms, as well as co-authoring Finance Magnates’ quarterly industry benchmarking reports. Damian’s reporting is data-driven, market-aware, and grounded in direct industry engagement. His analysis and commentary have also been cited by external media outlets, including Investing.com, Binance, The Asset, Stockhead, and Dispatch.
Education:
MA in Finance and Accounting, Cracow University of Economics
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