Insurance Industry Faces Its Biggest Competitor: Are Prediction Markets the 'Barbarians at the Gate'?

Odaily星球日报Publicado em 2026-06-22Última atualização em 2026-06-22

Resumo

"Insurance Industry Faces New Rival: Are Prediction Markets the 'Barbarians at the Gate'?" Prediction markets, exemplified by platforms like Kalshi and Polymarket, are emerging as potential disruptors to the traditional insurance industry by offering alternative risk-hedging mechanisms. These markets allow users to bet on specific event outcomes, effectively creating a form of customizable, on-demand insurance. Key examples highlight this shift. In sports, Kalshi partnered with insurance broker Game Point Capital to provide NBA teams with more affordable options to hedge performance bonuses compared to traditional insurers. In real estate, Polymarket's collaboration with Parcl lets users speculate on city-specific housing price indices, allowing homeowners to hedge against price drops or buyers against price increases. Furthermore, businesses like a New York bar have used Kalshi to hedge marketing promotions (e.g., offering free drinks if a team wins), framing the transaction explicitly as placing a "hedge." The article argues prediction markets offer advantages over traditional insurance and even sports betting in transparency, liquidity, and flexibility. They provide a wider range of event coverage, act as neutral platforms rather than counterparties, and offer clearer pricing. The piece cites historical precedents like large "refund promotion" hedges by businesses using sportsbooks but notes prediction markets modernize the concept. However, challenges remain for wides...

Original|Odaily Planet Daily (@OdailyChina)

Author|Wenser(@wenser2010 )

For a long time, the insurance industry has held a dominant 'ballast' position in the economic system with its monopolistic posture. However, with the emergence of prediction markets, this status quo is poised for a change.

In early June, the NBA Finals concluded, with the Knicks ultimately defeating the Spurs 4-1 to win the championship, bringing joy or sorrow to countless participants in game predictions. Among the happiest individuals might be Andy Freedman, owner of The Jeffrey bar in New York's Upper East Side. Before the series began, he launched a marketing campaign promising "free drinks for all customers if the Knicks win Game 1," while simultaneously hedging the risk with a $5,000 bet on the prediction market platform Kalshi. In the end, the Knicks secured victory in the first game. The Jeffrey bar used the prediction winnings to cover the beverage costs, and the bar patrons enjoyed free drinks, concluding the story with a 'triple-win' outcome.

This is just a microcosm of how prediction market platforms function in risk hedging and property insurance. With the World Cup attracting tens of billions of dollars in participation, the real-world insurance industry now faces a 'barbarian at the gate.'

Prediction Market Platforms Can Also 'Buy Insurance,' Do You Believe It?

Yes, you read that correctly. To some extent, prediction market platforms like Kalshi and Polymarket are now encroaching on the business territory of insurance companies, covering not only conventional marketing but also sports insurance, weather disasters, and more.

When Prediction Markets Steal Sports Insurance Clients: Kalshi Partners with Game Point Capital

In February of this year, professional sports insurance broker Game Point Capital announced a partnership with Kalshi. The latter will provide the former with NBA team performance bonus hedging (e.g., playoff advancement bonuses).

As a professional company issuing hundreds of millions of dollars in sports insurance annually, Game Point Capital's shift is clearly not merely to align with the development of the prediction market industry but is a comprehensive consideration based on business and cost factors.

From a market demand perspective, sports insurance has always existed. It is understood that since championship bonuses are typically paid by the teams themselves, professional sports teams often purchase insurance in advance to cover these expenses. Due to the substantial amounts involved, teams traditionally turned to conventional insurance companies for support—such as Lloyd’s, Munich, Swiss, and other established U.S. insurers.

From an insurance cost perspective, prediction market platforms offer more competitive pricing. According to reports, Kalshi provides significantly lower pricing than traditional over-the-counter markets (e.g., approximately 6% for a certain bonus hedge vs. the traditional 12-13%). It is estimated that the platform could handle tens of millions of dollars in hedging funds through this partnership, marking a direct example of prediction markets entering the traditional insurance and reinsurance fields. Kalshi CEO Tarek Mansour describes this as "a better way to hedge risk and insure," emphasizing that "the pricing will be more transparent."

When Prediction Markets Become 'Housing Price Hedging Tools': Polymarket Teams Up with Parcl to Launch a 'New Model for Property Speculation'

In January of this year, the on-chain real estate platform Parcl announced a partnership with Polymarket, introducing Parcl's daily home price indices into Polymarket's new real estate prediction markets. The initial markets will focus on major U.S. cities (New York, Los Angeles, Miami, Austin, etc.). Users can predict the rise, fall, or threshold outcomes of specific city home price indices on a monthly, quarterly, or annual basis.

The news caused Parcl's native token PRCL to surge over 100% on the day. For Americans unable to purchase homes due to high prices, they can now participate in "property speculation" without actually buying a house. Joel Berner, Senior Economist at Realtor, believes that "beyond speculating on housing prices, homeowners and potential buyers can also use these markets to protect their market interests."

For sellers concerned about falling prices, they can buy "Under" predictions on Polymarket; if prices subsequently fall, the corresponding gains can partially offset actual property losses, serving an insurance-like effect. For buyers, or those planning to purchase a home, if they fear rising prices, they can predict "Over," and the corresponding gains can help cover the increased purchase costs.

When NBA Games Are Linked to Free Drinks: The Cross-Marketing of a New York Bar and Kalshi

In early June, Kalshi officially announced that The Jeffrey bar in New York had placed a $5,000 bet predicting "the Knicks will win Game 1," with the slogan—"If the New York Knicks win, then all customer bills will be covered by the bar." Notably, Kalshi's official statement used the phrase—"place a $5,000 hedge on Kalshi" (Odaily Planet Daily note: Insuring $5,000), emphasizing the insurance value of prediction markets.

In this official press release, Kalshi also revealed greater ambitions—to become a "small business insurance provider," offering services such as sports event predictions, weather condition predictions, and import/export policy change predictions to hotels and inns affected by seasonal fluctuations due to sports events, clothing stores and restaurants whose customer traffic is impacted by weather, other commercial venues, and small businesses reliant on imported goods—thereby enabling insurance hedging.

Kalshi's Head of Business, Nicolas Hull, believes, "Small businesses face various real-world risks daily—issues related to weather, politics, sports, the economy, etc. Traditional insurance methods are both expensive and inefficient, failing to effectively address such operational risks. Kalshi changes this: we provide a liquid, transparent market platform that allows any business to take action against risks affecting their operational outcomes. This marks a fundamental shift in how small businesses manage risk."

Various cases indicate that the insurance value of prediction markets can be widely applied across multiple fields, not limited to sports events, brand marketing, etc. Furthermore, successful cases of traditional sports betting have already existed in practical applications.

Old Wine in a New Bottle, But the New Bottle Is Better: The Insurance Value of Prediction Markets Lies in Transparency and Liquidity

In 2018, the home appliance brand Vatti created a massive marketing campaign with the gimmick "full refund if the French national team wins the World Cup." Although it ended in a farce with excuses like "tight schedule, cumbersome process, coupons instead of cash," it left a deep impression on many regarding "freebie marketing."

Coincidentally, such tactics are not new.

In 2017, Houston home furnishings magnate Jim McIngvale (AKA "Mattress Mack") staged a "refund marketing" campaign worth up to $12 million, with the gimmick "if the Houston Astros win the championship."

Five years later in 2022, "Mattress Mack" repeated the trick. From May to July that year, he invested a total of $10 million across six different betting companies in Louisiana, Iowa, Las Vegas, etc., again predicting "the Astros will win the championship," and explicitly stated he would "refund every penny" of the winnings to the approximately 3,000 customers who had previously participated in his furniture store's promotional activities. (Odaily Planet Daily note: The promotion targeted customers purchasing furniture worth over $3,000, offering a full refund or even a double refund depending on the participation time).

Ultimately, the 71-year-old "Mattress Mack" emerged victorious once more, winning $72.6 million in prizes, setting a record for sports betting winnings at the time.

However, compared to sports betting, the "insurance" function of prediction markets has undergone significant updates.

First, monetization of information. This brings two major advantages: (1) Broader market scope. Compared to betting with limited, narrow options, prediction markets offer a wider "range of choices"; (2) More flexible exit strategies. Unlike betting activities where at most one can get a refund, prediction market events more directly reflect the potential impact of information changes, allowing participants to make timely decisions.

Second, the neutral role of the platform. Unlike the "platform," "house," or "whales" in sports betting events, prediction market platforms serve as neutral entities, providing only trading channels and not directly acting as counterparties to traders.

Third, transparency of trading information. Odds in sports betting are typically determined by the companies based on their own algorithms and internal information. Many companies even adopt a "copy trading" model, directly copying odds changes from larger platforms, making odds fluctuations and order transaction information extremely opaque. Furthermore, event determination criteria often face disputes or involve insider last-minute bets.

Fourth, participant access systems. In the U.S., most sports betting operators adopt a "ban or bankrupt" operational model—a business strategy that "restricts high-win-rate clients from trading while encouraging losing and average players to trade." In 2024, legendary gambler Billy Walters, "Spanky" Kyrollos, and former casino executive Richard Schuetz co-founded a nonprofit advocacy group called American Bettors Voice (ABV). Its core advocacy is against the "ban or bankrupt" model, demanding reasonable regulation of betting limits to ensure market fairness.

Compared to traditional sports betting, the insurance value of prediction markets is undoubtedly more attractive and secure. SIG CEO Jeff Yass, a prominent market-making institution, previously mentioned in a Forbes interview: "Prediction markets allow parties to share risk more efficiently based on specific parameters. For example, a homeowner in Florida facing hurricane risk could choose to buy a contract that 'pays off for sure,' based on the latest weather data, providing insurance protection when wind speeds exceed a specified threshold. Compared to buying annual insurance, this method can more effectively address potential property loss risks."

Of course, at present, the insurance value of prediction markets is not yet fully developed or widely promoted, still facing the following challenges:

  • Insufficient liquidity. A wide range of choices does not guarantee sufficient market depth.
  • Blurred regulatory boundaries. Whether platforms like Kalshi and Polymarket can sustainably serve insurance functions awaits regulatory recognition.
  • Decentralized democratic risks. For instance, the incident on Polymarket's weather prediction market where someone used a hair dryer to influence the observation machine for profit serves as an example. Sometimes, event determination criteria can be unpredictably influenced by external forces, and platform judgment rules may contain various vulnerabilities.

Regardless, the first step has been taken. Whether the insurance industry acknowledges it or not, prediction market platforms threaten not only sports betting platforms but also many traditional insurance business companies.

Recommended Reading

Not Speculation But a Necessity: The 4 Unique Values of Prediction Markets

The Prediction Markets Are Coming For Risk Markets and Insurance

Perguntas relacionadas

QWhat are the main ways prediction market platforms like Kalshi are threatening the traditional insurance industry according to the article?

AThe article states that prediction markets are threatening the traditional insurance industry by offering risk hedging and insurance-like services in areas such as sports performance bonuses (e.g., NBA playoff incentives), price hedging for real estate, and operational risks for small businesses (e.g., weather, sports outcomes). These platforms offer more transparent pricing and greater liquidity compared to traditional insurance models.

QHow did the partnership between Game Point Capital and Kalshi demonstrate the insurance value of prediction markets?

AThe partnership between sports insurance broker Game Point Capital and Kalshi demonstrated the insurance value of prediction markets by using Kalshi to hedge performance bonuses for NBA teams. Kalshi offered pricing significantly lower than traditional over-the-counter insurance markets (e.g., 6% vs 12-13%), making it a more cost-effective and transparent 'better way to hedge risk and insure,' as described by Kalshi's CEO.

QWhat example is given in the article to show how prediction markets can be used for hedging real estate price risks?

AThe article cites the collaboration between Parcl and Polymarket. They created a real estate prediction market where users can bet on the price index movements of major US cities. This allows homeowners to hedge against potential price drops by betting on a decline, and potential buyers to hedge against price increases by betting on a rise, effectively creating an insurance mechanism for real estate market exposure.

QWhat key advantages do prediction markets have over traditional sports betting according to the article?

AAccording to the article, prediction markets have several key advantages over traditional sports betting: 1) Greater transparency in pricing and trading information. 2) Broader market scope and more flexible exit options for participants. 3) Platforms act as neutral facilitators, not direct counterparties. 4) They avoid the 'ban or bankrupt' model used by many sportsbooks which restricts successful bettors.

QWhat are the current challenges or limitations facing prediction markets in their expansion into insurance functions?

AThe article mentions three main challenges: 1) Insufficient liquidity in many markets. 2) Unclear regulatory boundaries regarding whether platforms like Kalshi and Polymarket can legally function as insurers. 3) Risks associated with decentralized event resolution, such as potential manipulation of outcome determination (e.g., the Polymarket weather event where a hairdryer was used to influence a sensor).

Leituras Relacionadas

Critical Game Week: BTC Retracement Confirmation vs. HYPE Support Battle | Guest Analysis

This weekly analysis outlines a critical juncture for BTC and HYPE markets, focusing on key price level confirmations. **BTC Analysis:** BTC is at a pivotal point after a five-wave rally from the June 5th low of $59,100. The price has broken below a short-term rising channel's lower boundary, with the current move seen as a pullback to test this breakdown. Failure to reclaim this level could lead to a retest of the $59,000-$60,000 support zone. The core scenario hinges on this channel retest outcome. * **Key Levels:** Resistance at $64,500-$65,000 (channel boundary) and $69,500-$70,500. Support at $59,000-$60,000 and $55,000. * **Strategy:** A core bearish stance is maintained (20% short from last week), with short-term plans for tactical trades. Three detailed contingency plans (A/B/C) are provided for short positions on resistance tests or breakdowns, emphasizing strict stop-loss discipline. **HYPE Analysis:** HYPE shows strong momentum but is currently in a corrective phase after hitting a new high of $76.94. The price is retesting the crucial $64-$66 support area. * **Key Levels:** Resistance near $77 and $80-$82. Support at $64-$66 and $52-$54. * **Strategy:** The short-term approach is "buy on dips, avoid chasing rallies." A long position is considered only if clear stabilization signals appear at the $64-$66 or deeper $52-$54 support zones, with tight risk controls. **General Risk Management:** A standardized trailing stop-loss protocol is emphasized: set initial stop, breakeven at +1% profit, then trail stops upward to lock in gains. *Disclaimer: All analysis is presented as a personal trading framework, not investment advice. Market conditions are complex and require dynamic adjustment.*

marsbitHá 6m

Critical Game Week: BTC Retracement Confirmation vs. HYPE Support Battle | Guest Analysis

marsbitHá 6m

Research Report Interpretation: Citi Attends AWS Summit, Bullish on Cloud Business Acceleration but Data Governance Remains Key Variable

Citi analyst Tyler Radke's team attended the AWS New York Summit (June 17-18), engaging with over 10 clients and partners. In a June 19 report, they highlighted the summit's focus on scaling agent AI for enterprise deployment. Citi maintains a "Buy" rating on Amazon, forecasting AWS revenue growth to accelerate to 37% in FY27 from 30% in FY26, noting this estimate may be conservative. Key takeaways: 1. **AWS Strategy Shift:** AWS is moving from proof-of-concepts to scalable deployment. New offerings like AWS Context (building enterprise knowledge graphs), Amazon Quick (cross-application AI assistant), and security tool Continuum address core enterprise pain points for AI adoption. 2. **Data Infrastructure Beneficiaries:** Data infrastructure companies like Snowflake, Elastic, Oracle, and ClickHouse are seen as direct beneficiaries of scaling AI workloads, as evidenced by strong growth and use cases presented. 3. **Critical Role of Data Governance:** As AI agents scale from hundreds to thousands, effective data governance becomes the key variable for deploying AI in core business processes. AWS Context represents AWS's strategic extension from providing compute/models to offering a data governance infrastructure layer. The report emphasizes that without solving data governance, AI will remain confined to pilot projects. The investment thesis focuses on AWS revenue acceleration and data infrastructure vendors' growth, while monitoring signals like AWS's quarterly revenue growth, Bedrock AgentCore task volume, and pricing impacts on companies like Elastic.

marsbitHá 12m

Research Report Interpretation: Citi Attends AWS Summit, Bullish on Cloud Business Acceleration but Data Governance Remains Key Variable

marsbitHá 12m

Crucial Week of Contention: BTC Tests Support and HYPE's Key Level Battle | Special Analysis

**Market Enters Critical Week: Bitcoin Pullback Test and HYPE Support Battle** The market enters a crucial phase of contention this week. The marginal shifts in Federal Reserve policy expectations continue to dictate the pricing rhythm for risk assets. Meanwhile, in the crypto market, following a period of sideways consolidation, the divergence between bulls and bears is becoming concentrated at key price levels. **Bitcoin (BTC) Analysis & Strategy** * **Technical View:** The 4-hour chart suggests BTC is in a five-wave structure since the June 5th low near $59,100. Price action shows a short-term rising channel. The recent drop below this channel's lower boundary is now being followed by a pullback attempt (wave 40-41). The outcome of this retest is critical. * **This Week's Outlook:** The core focus is whether BTC can reclaim and hold above the channel's lower boundary. * **Bullish Scenario:** A successful hold could lead to a continued rebound, potentially challenging the $69,500 - $70,500 resistance zone. * **Bearish Scenario:** Failure to hold may trigger a renewed test of the $59,000 - $60,000 core support area, with $55,000 as a deeper support level. * **Operational Strategy:** The author maintains a 20% mid-term short position initiated last week near $64,500, based on a model signaling a shift to a bearish structure. Short-term tactics involve using 30% capital for potential "spread" trades, with three contingency plans (A, B, C) outlined for reacting to resistance tests, breakouts, or support breakdowns. **HYPE Analysis & Strategy** * **Technical View:** On the 4-hour chart, HYPE shows strong momentum, having recently broken to a new high since January. The current pullback presents a clear three-wave correction structure, bringing the price back to the critical $64 - $66 support zone. * **This Week's Outlook:** The focus is on the battle for the $64 - $66 support area. * **Bullish Scenario:** Holding this support could signal a continuation of the uptrend from the June 10th low, leading to new highs. * **Bearish Scenario:** A breakdown could extend the correction, potentially testing the deeper $52 - $54 support band. * **Operational Strategy:** The recommended short-term approach is "buy on dips, avoid chasing rallies." A light long position (under 30% capital) could be considered if HYPE shows stabilization signals at the $64-$66 or $52-$54 support zones, confirmed by model signals. Strict stop-loss discipline is emphasized. **General Risk Management:** A strict trailing stop-loss protocol is advised: set an initial stop; move to breakeven at +1% profit; lock in profits progressively thereafter. *Disclaimer: All analysis is presented as the author's personal technical perspective and trading log, not as investment advice. Markets are complex and dynamic; risk control is paramount.*

Odaily星球日报Há 12m

Crucial Week of Contention: BTC Tests Support and HYPE's Key Level Battle | Special Analysis

Odaily星球日报Há 12m

AI Agents Also Need 'Credit Checks': ERC-8126 is Filling the Gap in On-chain Trust

The article discusses ERC-8126, a proposed standard designed to address the lack of trust and verification for AI Agents operating on-chain. While ERC-8004 provides AI Agents with a basic on-chain identity (answering "Who are you?"), it does not guarantee trustworthiness. ERC-8126 aims to fill this gap by establishing a verification layer (answering "Are you reliable?"). It standardizes how independent verification providers can assess an agent's associated risks across five key areas: Token/Contract Verification (ETV), Media Content Verification (MCV), Solidity Code Verification (SCV), Web Application Verification (WAV), and Wallet Verification (WV). These providers generate a standardized risk score (0-100) and proofs based on their checks, without acting as a single authoritative certifier. This allows wallets, marketplaces, dApps, and other agents to consume these risk signals—for example, to display warnings, filter listings, or make interaction decisions. The standard also incorporates concepts like Private Data Verification (PDV) and Zero-Knowledge Proofs (ZKP) to allow verification without exposing sensitive underlying data. Positioned alongside ERC-8004 (Identity) and ERC-8183 (Commerce for agents), ERC-8126 represents a step toward building a verifiable and accountable infrastructure for the emerging on-chain AI Agent economy, shifting trust assessment from purely user-based judgment to standardized, consumable signals.

marsbitHá 30m

AI Agents Also Need 'Credit Checks': ERC-8126 is Filling the Gap in On-chain Trust

marsbitHá 30m

Rented Conviction: How Much Real Money Is Behind the Bitcoin ETF Flows

Borrowed Belief: How much of Bitcoin ETF flows are real money? Weekly Bitcoin ETF flows, often interpreted as a measure of institutional conviction, are heavily influenced by a hidden arbitrage trade rather than genuine directional buying. A cash-and-carry arbitrage, where traders buy the ETF while simultaneously shorting Bitcoin futures on the CME to lock in a basis spread (the price difference between futures and spot), drives roughly half of the week-to-week flow volatility. This delta-neutral activity appears as ETF inflows but is unrelated to price views. Data shows a strong correlation (0.70) between weekly ETF inflows and increases in hedge fund short positions on CME futures, while Bitcoin’s weekly price returns have almost no explanatory power. However, this arbitrage activity dominates short-term *fluctuations*, not the cumulative *stock* of investments. Of the total ~$55 billion in net ETF inflows since launch, only about $1 billion currently represents net arbitrage exposure. The vast majority consists of steady, directional buying averaging around $400 million per week. The arbitrage trade has been unwinding for two years, with hedge fund short positions peaking near $14 billion in late 2024 and declining to ~$4.5 billion. Recent ETF outflows partly reflect this ongoing unwind as the basis compresses, not a loss of faith in Bitcoin. Thus, ETF flows overstate the *volatility* of belief, not its *level*. The headline number is more a gauge of arbitrage desk activity than conviction. For accurate interpretation, monitor the CME basis relative to Treasury yields and hedge fund net shorts—these reveal how much of the reported “demand” is truly directional.

marsbitHá 33m

Rented Conviction: How Much Real Money Is Behind the Bitcoin ETF Flows

marsbitHá 33m

Trading

Spot
Futuros
活动图片