On June 22, 2026, the Hong Kong-listed company Beibo Group (8331) announced in a statement the establishment of a strategic research collaboration with the decentralized prediction market platform SigMarket to jointly explore the application of prediction market technology in internal risk management and decision support within enterprises. On June 25, the Hong Kong-listed company Dingli Capital (356) announced the signing of a strategic cooperation memorandum with the decentralized prediction market platform SigMarket to jointly research prediction market risk management, including AI and RWA. This marks the first public case of a listed company in Hong Kong, the Asian financial center, incorporating decentralized prediction technology into the scope of enterprise risk management.

Prediction Market Opens in Asia, The First Tool for Enterprise Productivity

In recent years, prediction markets have seen explosive growth globally; however, this has also been accompanied by controversies over whether prediction markets are equivalent to gambling markets. SigMarket is leading the way by designing prediction technology as a productivity tool for internal risk management within enterprises, embedding it into the traditional financial sector and providing a new perspective for a comprehensive assessment of the strategic value of prediction markets.

In fact, using prediction markets as tools for internal risk management is not a new concept. Google started implementing prediction markets internally as early as 2005 to forecast product release dates and business metrics. In 2015, the publication "The Review of Economic Studies" by Oxford University published a paper analyzing cases of companies like Google and Ford using internal prediction markets to enhance forecasting accuracy. In recent years, interest in the application of enterprise-level internal prediction markets has been rekindled with the development of public prediction markets such as Polymarket and Kalshi.

In 2024, at the Manifest conference hosted by the prediction market platform Manifold, technicians from AI company Anthropic publicly stated that the company has launched an internal prediction market primarily used to assist decision-makers in strategic judgments. Additionally, in February 2026, the American consulting firm Deloitte released a report recommending that companies consider establishing internal prediction markets to gather strategic signals.

Although the strategic cooperation established by SigMarket with the Hong Kong-listed companies is currently limited to the field of internal risk management, according to the white paper released by SigMarket, there will be further development of a publicly accessible general hedging prediction market in the future.

Decentralization: The Next Battlefield for Prediction Markets

“Ethereum creator Vitalik Buterin has always opposed the gamification of prediction markets; he has repeatedly expressed concerns about the current development direction of prediction markets and suggested that prediction markets should be pushed towards “hedging, in a very generalized sense.” Our entire product design embodies the vision proposed by Vitalik Buterin in his article on “Prediction Markets and Information Finance.” SigMarket's Chief Scientist Miles Ng stated: prediction markets can serve as more refined general hedging tools to help enterprises break down risk factors that traditional financial products find hard to hedge and has high innovative potential when combined with AI Agent and RWA.

“When we buy a company's stock, we are essentially purchasing a bundled risk factor package, which includes production factors like raw materials, production, R&D, but also includes non-production factors such as the health of the entrepreneur, their family situation, tax policies in the country of headquarters, and changes in geopolitical situations, all of which can seriously impact stock value. In traditional financial markets, you cannot isolate these events for hedging, but prediction markets can. ” Miles Ng proposed that for future AI Agents to perform comprehensive data analysis and general hedging in prediction markets, what is needed first is for all trading data to be on-chain and completely decentralized. If it is just off-chain matching of results on-chain, or if it is a centralized trading market where results are not even on-chain, it becomes a black box for AI, which cannot aggregate address behavior for each transaction placed under the prediction market, nor can it observe internal order placements and cancellations. Simply put, centralized prediction markets cannot achieve AI's “machine trust.” Therefore, the next battlefield for prediction markets must be a more thorough decentralization.

With Polymarket and Kalshi forming a dual-strong competitive landscape in the US market, the industry is also beginning to pay attention to whether new scaled prediction markets will emerge in Asia. The emergence of decentralized general hedging prediction markets—SigMarket has become the forerunner of the resurgence of prediction markets in Asia.

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