Six months ago, Goldman Sachs chief executive David Solomon told listeners of the bank's own podcast that he found prediction markets "super interesting." By July 2026, his firm had banned its own employees from touching them. The reversal, first reported by Bloomberg on July 9 and confirmed across multiple outlets in the days that followed, marks one of the most pointed moves yet by a major Wall Street institution to build a compliance wall around a financial product category that has exploded in popularity — and, increasingly, in regulatory and legal scrutiny — over the past eighteen months.
The mechanics of the new policy are specific and, in places, unusually detailed for an internal compliance memo. Goldman Sachs has updated its personal trading rules to prohibit employees from placing bets on event contracts tied to specific companies — including Goldman Sachs itself — election outcomes, or the performance of any financial market. The ban extends further than most observers initially expected: it also covers contracts tied to the dates of ceasefires in active conflicts, the price of bitcoin, and the outcome of merger-related regulatory approval processes. Sports and entertainment betting remain permitted, a carve-out the bank appears to view as low-risk precisely because Goldman employees are unlikely to possess material non-public information about the outcome of a football match or an awards show, in the way they routinely do about companies, markets, deals and macroeconomic data.
The bank's language internally has been blunt. Employees have been told they must be vigilant to ensure their participation in any prediction market does not violate laws and regulations and does not appear improper — a standard that goes beyond simply avoiding actual insider trading to policing the mere appearance of impropriety, a notably conservative bar even by Wall Street compliance standards. The penalties attached to violations are meaningful rather than symbolic: repeated breaches of the policy can lead to termination of employment or closure of a trading account, and where a trade is deemed improper, the bank reserves the right to require employees to forfeit any profit exceeding $200, either back to the firm or to a charitable organisation.
The timing is not coincidental. The policy shift follows what has been described as the first event-contract insider-trading case involving a private-sector company. In May 2026, the Commodity Futures Trading Commission and the Department of Justice brought charges against a Google employee, identified in court filings as Michele Spagnuolo, accused of using non-public access to internal company data — specifically related to Google's "Year in Search" list — to place profitable bets on Polymarket, allegedly netting roughly $1.2 million. In a separate and arguably more alarming case, a US Army soldier was charged with using confidential government information about a January military raid in Venezuela to place bets on Polymarket, allegedly profiting more than $400,000 from access to classified operational details. Together, the two cases crystallised a risk that compliance officers across the financial industry had been discussing in the abstract for months: that prediction markets, structurally, create a direct financial incentive for anyone with access to sensitive information — whether corporate, governmental, or market-moving — to monetise that access in a venue that, unlike traditional securities markets, had until recently operated with comparatively light regulatory oversight.
Goldman is far from alone in responding. JPMorgan Chase has taken a notably softer approach, issuing what amounts to a cautionary nudge rather than an outright prohibition — urging employees to carefully weigh their decisions before trading on financial-sector-linked contracts, without formally banning the activity. At the other end of the spectrum, hedge funds Point72 Asset Management and Balyasny Asset Management have gone further than Goldman, imposing blanket bans on all personal-account prediction-market activity for their employees regardless of category, reflecting the generally more conservative posture hedge funds tend to take toward any activity that could create even a perception of trading on privileged information. Morgan Stanley, meanwhile, has folded prediction-market guidance into its broader code of conduct rather than issuing a standalone policy, a middle-ground approach that several compliance consultants have suggested may become the industry norm as firms calibrate their response to a fast-moving product category regulators themselves are still working out how to classify.
The regulatory backdrop explains much of the urgency. The CFTC's Division of Market Oversight issued a formal prediction-markets advisory on March 12, 2026, and has since published an advanced notice of proposed rulemaking seeking industry comment on whether new or amended rules are needed specifically for event contracts — the regulatory category under which platforms like Kalshi and Polymarket operate. The commission has separately proposed a new reporting rule for fully collateralized event contracts, effective July 1, 2026, tightening how such products are captured within the broader futures-data reporting framework the CFTC already uses for traditional derivatives. On the congressional side, the House Oversight and Government Reform Committee, chaired by Representative James Comer, launched its own investigation in May into whether users of prediction-market platforms are systematically trading on non-public or classified information — a probe that, if it uncovers additional cases similar to the Google and Army incidents, could accelerate calls for formal legislation rather than the current patchwork of agency guidance and voluntary industry self-regulation.
It is worth noting precisely what Goldman's ban does and does not cover. The prohibition governs personal trading by employees — it says nothing about the firm's own institutional interest in prediction markets as a business line, an interest Solomon had signalled as recently as January when he described active conversations the bank was having with platform operators about what Goldman's participation in the space might eventually look like. That distinction matters: banks routinely restrict employee personal trading in categories where the firm itself maintains institutional exposure, precisely because institutional activity is governed by an entirely separate and more rigorous compliance architecture — trading desks, information barriers, and regulatory reporting obligations that individual employees placing personal bets simply do not have access to. In other words, Goldman closing the door on staff betting on, say, the outcome of a Federal Reserve rate decision does not necessarily mean the bank has abandoned interest in eventually offering prediction-market-adjacent products to institutional clients.
The two platforms most closely associated with the controversy occupy meaningfully different regulatory positions, a nuance Goldman's blanket policy does not appear to distinguish between. Polymarket, which operates using crypto infrastructure and drew enormous retail and institutional trading volume around the 2024 US presidential election, has operated in a comparatively grey regulatory zone in the United States. Kalshi, by contrast, functions as a CFTC-registered designated contract market, placing it under direct federal derivatives oversight in a manner closer to a traditional futures exchange. Both the Google insider-trading case and the Army soldier case involved Polymarket specifically, which may explain why regulatory attention has concentrated there even as Goldman's internal policy, notably, makes no distinction between the two platforms and bans employee activity on both equally.
Reaction within the wealth-management and advisory community has been sharply divided. Some financial advisors have publicly welcomed the tightening, arguing prediction markets offer little genuine analytical value and function closer to speculative gambling than legitimate investment activity. One prominent wealth advisor described the entire category bluntly as sheer unadulterated gambling, arguing that with the sheer volume of established economic-data sources already available to professional investors, prediction-market pricing on "a myriad of random events" adds negligible informational value that couldn't be sourced more reliably elsewhere. Others in the industry take a more nuanced view, arguing prediction markets do genuinely aggregate distributed information in ways traditional polling and forecasting sometimes fail to capture — the debate that has made platforms like Kalshi and Polymarket objects of fascination for data scientists and political forecasters even as compliance departments treat them as a legal liability.
For India's financial-services ecosystem, the Goldman story carries relevance well beyond Wall Street curiosity. Indian-origin professionals occupy senior roles across every major US and global investment bank, and Global Capability Centres run by firms including Goldman Sachs, JPMorgan and Morgan Stanley in Bengaluru, Hyderabad and Mumbai employ tens of thousands of analysts, risk officers and compliance specialists whose personal-trading policies are typically harmonised with the parent institution's global rules, meaning a policy change announced in New York effectively lands on desks in India within days. Beyond the workforce angle, prediction markets themselves remain in an unresolved legal and regulatory position in India, where SEBI and the Ministry of Finance have historically treated betting-adjacent financial products with considerable caution, distinct from the more permissive regulatory posture the CFTC has extended to registered platforms like Kalshi in the US. As global banks tighten internal rules around event contracts, Indian regulators and compliance heads at India's own broking and asset-management firms are likely to be watching closely for cues on how a comparable framework, if one is ever proposed domestically, might eventually be designed.
What happens next largely depends on how the CFTC's rulemaking process unfolds over the coming months, and on whether the House Oversight Committee's investigation surfaces additional cases of the kind that triggered Goldman's policy shift in the first place. For now, Goldman's message to its roughly 46,000 global employees is unambiguous: whatever entertainment value prediction markets on finance, politics and geopolitics might hold, the compliance and reputational risk of an employee getting caught trading on information they should not have had access to has become, in 2026, simply too high a price to pay.
To understand why Wall Street's compliance departments moved so quickly on this particular issue, it helps to trace how rapidly prediction markets have grown from a niche curiosity into genuinely significant trading venues. Event contracts have technically existed within regulated US markets for more than two decades in various forms, but their scale exploded specifically around the 2024 US presidential election, when platforms like Polymarket and Kalshi saw trading volumes surge into the billions of dollars as both retail speculators and increasingly sophisticated institutional players used them to hedge or express views on political outcomes in ways traditional options and futures markets simply did not allow. That growth trajectory has continued largely unabated since, with contract categories expanding well beyond elections into corporate earnings surprises, Federal Reserve decisions, geopolitical flashpoints, and even individual company-specific outcomes — precisely the categories now closed to Goldman's own staff. The speed of that expansion is a significant part of why regulators have found themselves playing catch-up, issuing advisories and proposing rules for a product category that scaled faster than the traditional multi-year rulemaking process typically allows.
The compliance dilemma facing large banks is compounded by a structural feature of prediction markets that distinguishes them from most traditional securities: the direct, unambiguous link between a specific real-world event and a payout, with none of the diversification or aggregation that makes proving insider trading in, say, a broad equity index genuinely difficult. If a Goldman banker working on a merger deal places a large bet on a prediction-market contract asking whether that specific merger will receive regulatory approval by a specific date, the connection between privileged professional knowledge and personal financial gain is about as direct and legally exposed as insider trading gets — arguably more transparent, ironically, than trading the underlying stock itself, where an unusual trade can sometimes be lost among ordinary market noise. Compliance officers interviewed across the industry in the wake of Goldman's policy shift have suggested this structural transparency is, somewhat counterintuitively, part of why banks are moving to blanket prohibitions rather than attempting more surgical, case-by-case restrictions: with event contracts, there is frequently no ambiguity about what information an employee's bet was based on, which removes much of the grey area that would otherwise support a more permissive, judgment-based compliance approach.
For India's own rapidly growing financial-technology and fintech sector, the Goldman episode carries an additional dimension of relevance worth flagging. As Indian fintech platforms continue exploring adjacent product categories — from options trading apps to fantasy sports and now, in some cases, early-stage discussions around event-contract-style products — the compliance architecture large global banks are now rapidly building around prediction markets offers a preview of the kind of regulatory scrutiny any Indian platform experimenting in similar territory should expect to eventually face from SEBI and the Reserve Bank of India, both of which have historically taken a considerably more conservative posture toward speculative, betting-adjacent financial products than US regulators have shown toward registered platforms like Kalshi. Indian regulators watching the Goldman story, and the broader wave of US institutional bans it has triggered, are likely drawing their own early lessons about where the line between legitimate financial innovation and unregulated gambling risk needs to sit — lessons that could shape how any comparable product category is eventually treated, should one emerge, within India's own financial markets.
