A cluster of Polymarket accounts won 41 of 42 bets on whether KPMG-audited companies would beat earnings estimates, a 98% hit rate. Meanwhile, investors put more than $13 million into tax startup ComplYant, whose founder allegedly claimed to be a CPA. Both stories point to the same failure: trust without verification.
On Episode 505 of The Accounting Podcast, Blake Oliver and David Leary discuss the federal investigation involving the Polymarket bets, fraud charges against ComplYant founder Shiloh Luckey, AI-powered scams, accounting automation, and pressure on tax firms to improve pricing and client service.
Trust is the common thread. As AI takes over more routine work, accountants must prove their value through judgment, skepticism, verification, and a better client experience.
When no one verifies
The Wall Street Journal reported that a mystery trader or group made about $22,000 from bets involving 18 KPMG-audited companies, including Wells Fargo, Home Depot, and DoorDash. Blockchain forensics firm Bubblemaps linked 19 accounts through flows of digital funds, suggesting that one person or team may have controlled them. The accounts won 41 of 42 KPMG-related bets and 82% of bets involving companies audited by other firms.
The pattern isn’t proof of insider trading, and the Journal couldn’t confirm that the accounts belonged to a KPMG employee. Still, the Journal has reported that federal prosecutors are weighing charges against a KPMG employee suspected of betting on client earnings. “How could you know that these companies are going to beat their earnings or not unless you had some kind of information ahead of time?” Blake asked. KPMG said it has zero tolerance for trading on nonpublic client information.
The ComplYant case involves information that was publicly available but apparently went unchecked. Prosecutors charged Luckey with nine counts of securities fraud, three counts of wire fraud, one count of bank fraud, and two counts of money laundering. They allege that she falsely claimed to be a licensed CPA and inflated ComplYant’s revenue, subscriptions, and cash reserves while raising more than $13 million. The indictment also alleges personal spending and a $1.5 million check-kiting scheme. These are allegations, not proven facts. Since we recorded, Luckey has pleaded not guilty.
CPA licenses are publicly searchable. As David noted, a large funding announcement doesn’t prove investors performed careful due diligence. In both stories, serious problems emerged after people assumed someone else verified the facts.
AI raises the stakes for fraud prevention
That need for verification is more urgent as AI makes scams cheaper to run. The hosts cited reporting that AI makes fraud 4.5 times more profitable. A scheme that once required a room full of callers can now operate with a few automated agents on a server.
David pointed to Revolut, a neobank that reportedly released customer information after receiving a social-engineering request from a legitimate government email domain. Revolut’s own guidance tells customers to confirm such requests through official contact information. The same standard should apply inside companies: a familiar domain or convincing voice isn’t enough to establish identity.
Technology can strengthen the defense. KPMG bought a stake in Reality Defender, which detects fake voice and video in real time. Meanwhile, Polymarket’s public blockchain records helped outside analysts identify the suspicious betting pattern. But for technology to support trust, firms need to build it into effective controls.
Automation changes how accountants develop judgment
That same shift creates a training problem. KPMG’s TaxSim, developed with Centaurian AI, uses simulations to help entry-level accountants gain experience. Blake saw value in replacing repetitive administrative work with focused practice. David was more skeptical. If real work disappears, how much simulation replaces it? Blake asked who pays for that training. Firms can’t simply automate junior tasks and expect professional judgment to develop on its own.
KPMG is also working with OpenAI on conversational access to systems like ERP and CRM platforms. That could spare employees from difficult software interfaces, but it doesn’t remove responsibility for understanding the underlying data and controls.
Xero faced the same tension after sponsoring an influencer post that claimed connecting Xero to Claude replaced the management accounts she used to pay an accountant £800 a month to prepare. Accountants reacted angrily, and Xero removed the post and apologized. Its leaders said AI should handle routine work while accountants focus on expert judgment and advice. That distinction only matters if clients can clearly see the value of that judgment.
The bigger threat is a poor client experience
Blake and David tested AI on their own business returns. Blake used Claude Cowork with TaxAct for S corporation and partnership returns. David combined TurboTax, ChatGPT, and QuickBooks reports, asking the AI what to do at each step.
David valued the immediate back-and-forth. When he supplied an accrual-basis report instead of a cash-basis report, the AI flagged it. He didn’t have to wait days for another email or manage a long portal exchange.
Neither host claimed AI was error-free. They discussed mistakes made by professionals and tax software, including a return prepared on the wrong accounting basis and Blake’s mother being incorrectly marked as blind. David cited Christine Gervais’s advice to treat every AI answer like work from a first-year hire and verify it against the tax code. Human review still matters, but the possibility of an AI error doesn’t excuse a slow, burdensome process.
David summarized the problem with a mechanic analogy. When clients pay a professional, they shouldn’t have to manage the work themselves. “It’s not AI,” he said. “The threat is the experience for the client.”
The same pressure applies to billing. After IRS guidance warned that billing clients for time AI saved could be an unconscionable fee, Blake argued that hourly billing was the real issue. Firms should charge for expertise and responsibility, not hours that technology eliminates.
Closing the trust gap
These stories ask the same question in different ways: Can accounting professionals still deliver credible verification and judgment? AI makes fraud easier, but it also improves detection and service. Firms can succeed by combining strong controls with careful review, clear pricing, and processes that respect the client’s time.
Listen to Episode 505 of The Accounting Podcast for Blake and David’s full discussion.