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Stop Losing Money on Cleanup Work by Automating the Parts That Don’t Need You

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Cleanup and catch-up work is among the most in-demand services accounting firms can sell, and among the hardest to deliver profitably. That was the starting point for a recent webinar led by Megan Reid, a 15-year accounting veteran who started in Big Four, moved through private industry, and now works on the firm enablement team at Digits.

In the webinar, Megan demonstrated how AI-native accounting tools can transform cleanup engagements from time-intensive projects into scalable service offerings. She built a client file from scratch, imported raw PDF bank statements, and walked through an entire cleanup workflow in real time.

Why cleanup work kills profit margins

“Cleanup is obviously valuable work and it’s hard to scale,” Megan said, framing the core challenge clearly. New clients almost always arrive with some sort of mess to clean up. Maybe you have 18 months of uncategorized transactions or transactions that haven’t been posted from the bank feed. You want to take the engagement, but you know it’s going to be hard to make it profitable.

“We always uncover more skeletons in the closet than we think,” Megan noted during the demonstration. If you’re billing fixed fees, you get squeezed by unpredictable hours. Clients want fast turnarounds. Your teams are leaner. “You’re asked to do more with less,” she said.

“Business owners need that work to be done,” Megan pointed out. But the question is “whether or not your workflow lets you take them profitably.”

Breaking down a traditional cleanup shows where the hours go:

  • Gathering data
  • Importing it or connecting feeds
  • Categorizing tons of transactions
  • Reconciling accounts
  • Resolving exceptions
  • Making adjusting entries
  • Reviewing everything with your client
  • Delivering the final report

“In a typical 12-month cleanup or catch-up, you spend the majority of your time categorizing and reconciling transactions,” Megan explained. These tasks are also “the most repetitive, pattern-based parts of the job, which is exactly what AI is good at.”

From blank file to categorized transactions

Megan started her demonstration with a completely blank client file, essentially just an empty ledger. She then showed how to handle a common scenario in which a new client hands over a stack of PDF bank statements with no bank login credentials.

She dragged and dropped the first PDF bank statement directly into Digits. “It is extracting all that data from the bank statement, booking it and categorizing it as well,” Megan explained as the system processed the document.

The AI extracted transactions, identified vendors and customers (called “parties” in Digits), populated company logos and descriptions, attached website links, and categorized each transaction into the appropriate account. Megan noted the system pulls from models trained on “more than 800 trillion dollars’ worth of transactions.”

After uploading statements for June through October, hundreds of transactions flowed in. When processing finished, only 12 were flagged for review. “Instead of manually clearing bank feeds,” Megan said, “come here and look at the exceptions.”

These were transactions that required confirmation. Megan clicked into one from Swift Courier Services. The AI suggested “contractors and consultants.” She confirmed it with one click.

From there, the system natively learned from that categorization. It immediately found two similar transactions and offered to update them together. The exception list dropped from 12 to 8 in seconds.

Bank reconciliation without the manual work

Megan demonstrated three ways to get bank statements into the system for reconciliation. You can connect directly to banks like Mercury, Wells Fargo, Chase, and US Bank, which pull statements automatically via API. You can drag and drop PDF statements anywhere in the product. Or you can use email ingestion, where each client gets a unique email address to forward statements.

She uploaded the June statement by dragging it onto the reconciliation screen. The system read the PDF, extracted every line item, and verified each against the ledger. Megan explained that the system uses “pixel bounding boxes” to match statement entries to ledger entries.

June needed one manual step: adding a beginning balance entry that the system couldn’t infer without a connected bank account. Megan created the entry directly in the reconciliation screen. “Unlike legacy systems, where you may have to have three different tabs open and make changes and then come back and refresh, everything can be done directly in here.”

Then she uploaded July’s statement and navigated away. When she returned, it was done. “The statement was uploaded by me. The auto reconciliation was kicked off by Digits and even finalized by Digits,” she showed in the timeline view.

For larger cleanups, Megan recommended uploading multiple statements at one time. Handle any beginning balances in the first month, then subsequent months often complete automatically.

Review tools that surface what matters

Even with AI handling categorization, accountants still need to review and sign off. “It doesn’t replace the accountant. It just removes that tedious work so that you can focus on those judgment calls,” Megan emphasized.

She demonstrated several review approaches. The general ledger view shows all transactions organized like a trial balance, including assets, liabilities, equity, revenue, and expenses. You can filter by status, amount, source, department, or location. Bulk updates work on hundreds of transactions at once.

Megan said the vendors and customers views are her favorite. They each flag two critical items:

  • New vendors or customers: Any vendor (or customer) the AI sees for the first time in your selected period
  • Split categorizations: Vendors (or customers) whose transactions appear in multiple categories

“I just need to have eyes on things it has not seen before,” Megan explained. Even if the AI categorized with high confidence, you have final review and say on how it was categorized..

For transactions needing client input, the collaboration happens in one place. Megan showed how to comment on any transaction: “Hey client, what is this for?” The client receives an email with a link, can respond directly in Digits or reply to the email, and the response appears on the platform. “All the collaboration is centralized in one location,” she said, “instead of you having to manage a ton of emails and download Excel files.”

Delivering professional reports, not data dumps

The final step Megan demonstrated was creating custom reports. While the financials inside Digits update live as transactions flow in, cleanup engagements need a formal deliverable, a static document that locks the numbers in place.

Megan built one on screen. She added a cover page, used AI to draft an executive summary, embedded links to the client’s checklist, and configured the financial statements with period comparisons and trend lines. The system includes “hover to discover” insights that show period-over-period changes and what drove them.

When you need to make adjustments after sending a draft, you create a new version. “Any adjustments you’ve made in Digits will then update directly to this report,” Megan explained. Publishing the final version removes the draft watermark and notifies the client.

The platform tracks everything, including when you created the report, when you published it, when the client viewed it, and all comments from either party. You have a complete record of the deliverable and the conversation around it.

“We’ve done 12 months of cleanup in an hour and a half instead of days,” Megan concluded.

What this means for your firm

The key takeaways from Megan’s demonstration show how cleanup engagements can become profitable:

  • AI categorizes the vast majority of transactions automatically, flagging only true exceptions
  • Bank reconciliations can run automatically when you upload statements
  • The system learns instantly from every correction without rules to build or maintain
  • Your time shifts to reviewing anomalies, making judgment calls, and delivering polished reports

One practical consideration came up during Q&A. When asked about importing messy QuickBooks Online data, Megan confirmed that direct QBO migration exists but cautioned, “You maybe don’t want the AI to learn off of really messy data. You maybe just want to start fresh.” The system uses imported data for baseline training, so starting clean might make more sense for particularly messy files.

For firms trying to grow, this changes the economics of client acquisition. Every prospect with messy books becomes an opportunity rather than a capacity problem. When you can handle cleanup work profitably, predictably, and consistently, you can say yes to more engagements while maintaining margins.

Watch the full on-demand webinar to see Megan’s complete demonstration from blank file to published financials. If you have cleanup engagements in your pipeline right now, consider what your workflow could look like when the repetitive work is automated.

What 15 Years of Running an Accounting Firm Taught Marcus Dillon About Building Something That Lasts

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Imagine the managing partner of a $35 million accounting firm. Twenty-four partners. A hundred and fifty team members. And this managing partner still carries the largest book of business in the entire organization.

Now hold that image and set it next to another one. A husband-and-wife team in San Antonio running an $11.5 million firm. Three people at the top. Zero billable production hours between them. And by Marcus Dillon’s account, they’re “having a whole lot more fun than the people who are maintaining client work.”

Same profession. Radically different firms. And only one of those models is built to thrive in the future.

That contrast sparked a conversation between Marcus and Rachel Dillon on a recent episode of Who’s Really the Boss? The episode marks a milestone. Dillon Business Advisors is approaching its 15th anniversary, and the Dillons use the occasion to walk through what Marcus calls the “3.0” chapter of their firm. The last five years have brought reinvention, painful lessons, and hard-won clarity about what actually creates lasting value in an accounting practice.

After 15 years and three distinct reinventions, the Dillons believe the firms most likely to thrive in the next chapter of this profession build for enterprise value. That means creating role-based team structures instead of depending on irreplaceable individuals. It means developing real leadership beyond the founder. And it means maintaining enough flexibility to navigate a future where AI, private equity, and market consolidation reshape the rules faster than most owners realize.

Here are the three interconnected lessons from DBA’s journey through their third reinvention.

Building around roles, not people

For roughly six years, Dillon Business Advisors was stuck. Revenue hovered between $2 million and $2.3 million in what Marcus describes as a “yo-yo effect” of exiting clients, growing organically, exiting clients, and growing organically again. They were trying to shift from annual compliance touchpoints to monthly recurring advisory work, but the team that excelled at cranking out tax returns once a year wasn’t necessarily the team best suited to serve clients month after month with real-time advice.

“The business was moving that way, regardless of whether that team member was coming or not,” Marcus explains. And that created a problem no amount of hoping could solve.

The breakthrough came when Marcus and Rachel stopped trying to clone people and started building around roles.

DBA already had the client service manager (CSM) who handled day-to-day communication and bookkeeping. They also had the director-level advisory role at the top. But there was a gap between those two. The client controller or tax manager role wasn’t consistent. Marcus says they “experimented, screwed up, and scrapped different ideas” before landing on what became the team of three: a defined, role-based pod assigned to every client throughout the year.

The team of three model bases assignments on role, not on specific people. 

“We made some mistakes by trying to recreate or clone a person, and you just can’t do that,” Marcus explains. Over 15 years, he’s watched team members leave, partners come and go, and clients move on. “Nothing is forever anymore. If you’re building all of your decisions around taking care of the team you have today, that’s kind of shortsighted.”

Rachel offers a personal window into why this mindset shift was hard. Both her parents essentially worked for the same employer throughout their careers. “Staying 20, 30, or 40 years at a job isn’t the norm anymore,” she says.

Once DBA embraced role-based structure, two things happened. First, the firm could absorb turnover without chaos. Second, teams got remarkably efficient. The team of three created so much capacity that team members started asking for more work. Clients knew their team. The team knew their clients. Life was good, maybe too good. Because when DBA looked up in 2024, they’d already converted every annual client to monthly recurring, and they were entirely dependent on organic growth for new business.

But the structural foundation enabled something most small firms never achieve: a real leadership team beyond the founders.

Amy McCarty joined as Director of Operations at the end of 2023. Lezlie Reeves, who started as a CSM in 2020, rose through every level to become Director of Accounting and Advisory. In 2024, Angel Sabino transitioned from being DBA’s external IT provider to Director of Technology. Arin Neucks joined as Director of Tax and Financial Planning. Amy and Lezlie now hold phantom stock in DBA and share in decision-making as owners would.

Meanwhile, Marcus’s own production hours dropped to between 200 and 300 annually over the last two to three years. Rather than backfilling that time with more client work, he channeled it into consulting other firm owners, advising technology companies, and leading industry groups, work that, as he puts it, “gives me life.”

The discipline to stay out of operations was tough. Marcus admits that earlier in DBA’s history, he’d “pull a pin and throw a grenade in it just to rebuild it.” The result was predictable. “You have collateral damage. People get hurt, and they leave because you don’t allow them to do the job you hired them for.”

Building around roles sounds simple. But getting there required some expensive lessons.

The cost of reinvention

If the team of three was the structural breakthrough of DBA’s 3.0 chapter, the path to getting there was paved with decisions that cost real money. Some were strategically brilliant, some were painfully expensive.

Start with the audit practice. DBA exited it around the beginning of 3.0, freeing the firm to go all-in on monthly CAS and advisory. Revenue temporarily dropped in 2021. PPP and ERC consulting work softened the blow, but DBA performed that work exclusively for existing clients. “We didn’t do that for any external non-existing clients,” Marcus emphasizes. “We only took care of our own during that time.”

But the client exits didn’t stop there. Over seven years, DBA performed roughly one exit per year, and sometimes two. They shed complex, non-ideal QuickBooks Desktop clients who didn’t fit the monthly recurring model. The last cut might have gone too deep.

“That very last exit we probably could have done without,” Marcus reflects. The final group made up roughly $100,000 in revenue. They’d made it through multiple prior cuts. “Margins were high on those clients, even if they were annual-only touchpoints. They were so easy.”

During those transition years, DBA created a bonus pool shared with the entire team for every new monthly engagement signed, regardless of who worked on that client. The goal was rewiring how everyone thought about client relationships.

Then came the most expensive mistake of 3.0.

At the end of 2022, DBA changed its name and domain, dropping “CPA” from the branding. The rationale made sense. “CPA” directed too much tax-only traffic when the firm had evolved beyond compliance work. But the execution was catastrophic.

“We lost all of our credibility overnight from an SEO optimization, from a recognition standpoint,” Marcus says. The domain redirects (the technical plumbing that preserves search engine authority when you change web addresses) were botched. Traffic from Google searches “almost completely dropped off for more than a year.”

The worst part was DBA hired a consulting company to manage the transition and paid “hundreds of thousands of dollars. And it still didn’t go well.”

“Don’t take anyone’s word for it when they say you just have to give it some time,” Rachel warned. “That’s definitely not the case.” Recovery took three to four years.

The firm also evolved to fully remote operations during this period, opening hiring beyond Texas to anywhere in the US and even offshore. Two team members moving to Colorado helped push this transition. But going national meant growing up operationally, adding proper benefits, launching a 401(k) with profit sharing in 2020, and eventually moving to a PEO to handle multi-state compliance.

By 2024, with excess capacity from the efficient team structure but organic growth harder to come by, the leadership had to restructure and cut, or go back to market. They chose growth. DBA completed two strategic acquisitions in 2024, one at the end of January and a larger one on October 1. The October acquisition represented about 25% of DBA’s revenue, a cap Marcus set intentionally. “We wanted to retain DBAs’ culture, processes, and technology.”

Today, DBA exceeds $6 million in revenue. But with that scale comes bigger questions about the future.

Two types of firms, one uncertain future

With a leadership team that can run the firm without Marcus touching a tax return, the question shifted from survival to direction. Marcus has conversations with firm leaders across the spectrum that reveal patterns every firm owner needs to understand.

At a breakfast with the $35 million firm’s managing partner, Marcus heard a framework that crystallized his thinking. Two firms exist in today’s market: the legacy firm, where the balance sheet is essentially a snapshot of human relationships, and the enterprise-value firm, where systems, processes, and technology create value independent of any single person.

“That first firm will continue to diminish in value just because they’re not going to be relevant in this next chapter,” Marcus says. Relationships matter, but they alone aren’t enough when private equity, alternative ownership structures, and AI permanently reshape the landscape.

Marcus sees three types of firms emerging:

First, solo and micro firms powered by AI. As larger firms consolidate, team members leave and launch practices that leverage tools like Copilot and Cowork to run $300,000 to $1 million operations without traditional employees. “If you can get $300,000 to $400,000 or more worth of work done as a solo firm owner, by all means, great.”

Second, mid-size firms like DBA, that invest in teams, leadership, and technology and build something meant to outlast the founder.

Third, large rolled-up or PE-backed organizations with the budget to deploy technology at scale.

The parallel to other industries is instructive. DBA’s dental and veterinary clients went through consolidation first. Banking followed. “Independent banking is very hard and it has to be very intentional for them to exist,” Marcus observes. For independent medical practices, “you may not have the patient base you want. You may not be able to hire and pay the team you want.”

And then there’s AI, which Marcus frames as Pac-Man moving from the bottom up. “If you’ve got technology that’s coming for you and you’re just standing there, game over.”

The solution is continuous upskilling. “You can’t not train somebody because you’re worried they’re going to outgrow you and leave.”

This leaves DBA in a deliberate state of discernment.

Marcus spends time with firms of every size, learning what $10 million firms struggle with, how $35 million firms think about technology, and what happens when $250 million firms acquire smaller practices. Part of this is strategic intelligence gathering. But it also positions DBA to attract great clients and talent when they leave larger organizations.

The Dillons haven’t decided to merge, sell, take PE money, or stay independent. They’re building what Marcus calls “optionality.” The leadership team now plans in one- to three-year windows. As Rachel notes, even five years out is difficult to predict “because we don’t even know what the next six months, 12 months, or 18 months will bring.”

Marcus grounds it all in stewardship. “If I’m no longer the best single owner of this business, what does that look like?” He’s asking the question. He’s just refusing to answer it prematurely, or out of fear.

“It’s not a bad idea to pause and pray and wait for your decision to be the right one for you and at the right time,” he says. “Other friends are doing deals, don’t feel pressure to do your own and do a bad one.”

What 15 years of reinvention actually teaches

DBA’s journey distills into three lessons that apply whether you run a $1 million practice or a $100 million operation.

  1. Build around roles, not people. The team of three made DBA resilient enough to absorb turnover and efficient enough to create real capacity. If your firm collapses when one key employee leaves, you have a structural problem. Define the roles that make service consistent regardless of who fills them.
  2. Expect real pain on the path to enterprise value. DBA didn’t reach $6 million by making perfect decisions. They arrived by making intentional ones and refusing to let mistakes paralyze them.
  3. Independence requires more intentionality, not less. Standing still is a decision, and increasingly a bad one. Whether you stay independent, merge, or take investment, the question is whether you’re adding enterprise value daily, or performing tasks technology will soon handle better.

The Dillons share what they’ve learned while figuring out their own path. After 15 years and three reinventions, they’ve earned the right to take their time with the next decision.

Listen to the full episode to hear Marcus and Rachel walk through every chapter of DBA’s evolution, including the specific conversations happening right now about what this profession’s next chapter actually looks like.

Rachel and Marcus Dillon, CPA, own a Texas-based, remote client accounting and advisory services firm, Dillon Business Advisors, with a team of 15 professionals. Their latest organization, Collective by DBA, supports and guides accounting firm owners and leaders with firm resources, education, and operational strategy through community, groups, and one-on-one advisory.

Phar-Mor’s Inventory Was Just Merchandise Driving Around in Circles on Trucks

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In 1992, a professional basketball league folded overnight because something had gone catastrophically wrong at a discount drugstore chain in Youngstown, Ohio. When Phar-Mor went down, it took with it 25,000 jobs, $1.1 billion in investor money, and a basketball league with one bizarre rule: no players taller than 6’5″.

This wild story comes from Oh My Fraud, the true crime podcast where host Caleb Newquist digs into financial scandals with the kind of detail accounting professionals love. In this episode, Caleb unpacks one of the largest retail frauds in American history and how it started with something shockingly simple.

Picture a young CFO walking into his boss’s office with bad news about company losses. The boss takes the report, crosses out the real numbers with a pen, and writes in fake ones. Then, after doing this himself for four months, he hands the pen to the CFO and says, “Your turn.”

That’s how a $1.1 billion fraud begins.

 

The City That Needed to Believe

To understand how Phar-Mor fooled everyone, you first need to understand Youngstown, Ohio, because the two are inseparable.

For most of the 20th century, Youngstown was a steel town where mills ran 24 hours a day. The entire regional economy was essentially one giant bet that steel would stay relevant forever. Starting in 1977, during a period locals still call Black Monday, the mills began closing quickly. Tens of thousands of jobs vanished. Within a few years, the city lost a quarter of its population.

The mayor of Youngstown later described the city’s psychology this way: “You’re always insecure when you lose 5,000 jobs. It’s kind of a neurosis in a community where people assume the worst. Someone who has been beaten up so much expects to be beaten up again.”

Michael “Mickey” Monus walked into this beaten-down environment in 1982. A Youngstown native educated at Babson College, Mickey wasn’t naturally charismatic. Newsweek described him as someone who “seems to have been born without any natural grace. His large, fleshy face wasn’t brightened by warmth or an easy smile. He liked to dress casually, but still looked stiff.” A local columnist was even more blunt, calling Mickey “Unprepossessing.”

But Mickey had the ability to make people believe. And in a city desperate for hope, that was everything.

Power Buying and Phantom Profits

Mickey partnered with David Shapira, heir to the Giant Eagle supermarket empire, to launch Phar-Mor. The concept was simple: a deep-discount drugstore selling everything at prices so low they almost didn’t make sense. Mickey called it “power buying.” Stockpile goods when suppliers offer rock-bottom deals on huge volumes, then pass the savings to customers.

The growth was explosive. One store became two, then eight, within a year. By 1988, there were about 100 stores. By 1990, more than 200 stores were generating over $2 billion in annual sales.

Sam Walton, the legendary founder of Walmart, publicly stated Mickey and Phar-Mor were the only competition he genuinely feared. As board member Anthony Cafaro recalled, “Sam couldn’t figure out how Phar-Mor’s prices were so low. He could not understand it.”

There was a good reason Sam couldn’t figure it out. Phar-Mor had been losing money every single year since it opened, and almost nobody knew.

In the mid-1980s, Mickey hired Patrick Finn as CFO. Patrick was loyal, relatively inexperienced, and someone who found genuine meaning in accounting’s orderliness. As he later testified, “You could see yourself going after problems, challenging yourself, solving problems in accounting. Things are either right or wrong.”

Patrick found the wrong answer quickly. When he brought the losses to Mickey, his boss took the report, crossed out the real numbers with a pen, and wrote in good ones. Mickey did this himself for four months before turning the job over to Patrick.

“You knew you were doing something wrong, but you never understood how wrong,” Finn later reflected. “Give him time, and he’ll fix the problem.”

So Patrick gave him time. And the fraud grew.

Bucket Accounts and Driving Inventory in Circles

By 1988, the scheme had evolved into systematic inflation of inventory on the balance sheet. Patrick’s team created what they called “bucket accounts.”

After counting inventory at a store, the accounting team would prepare legitimate journal entries for the real books. Then they’d create fraudulent entries to inflate the inventory numbers and dump them into these bucket accounts. The fake entries had telltale signs, like round numbers, no journal entry numbers, vague account names like “accounts receivable, inventory, contra,” and zero supporting documentation.

At year-end, right before the auditors arrived, they’d empty the buckets and spread the fraudulent entries across individual stores, making sure no single location looked obviously wrong.

They kept the real numbers in a separate set of books. John Anderson, brought in from Youngstown State University to help maintain them, later described the culture. “Pat always had an aggressive approach to accounting. Call it aggressive or call it creative. That’s the way it was done ever since I remember.”

By 1990, when Stan Cherelstein joined as comptroller, John closed an office door, pulled out the subledger, and told him the financial statements were misstated by approximately $150 million. Stan stayed, rationalizing that they might be able to fix it through legitimate means. He also admitted to fearing that if he went over their heads, some harm would come to him.

The fraud kept growing, and to survive, it needed auditors who weren’t looking too closely.

The Watchdog That Never Barked

Coopers & Lybrand was one of the world’s most respected accounting firms when it won the Phar-Mor audit. It won with a very competitive bid, which meant a very low price and pressure to cut costs.

Instead of auditing inventory at every Phar-Mor store (there were more than 300), Coopers checked just four stores out of 300. They also told Phar-Mor management months in advance exactly which four stores they’d check.

Think about what that means. If you know Store A is being counted on Tuesday and Store B was counted last week, you load a truck with inventory from Store B and drive it to Store A. The auditors count a beautifully stocked store on Tuesday. On Wednesday, the truck takes everything back. As Caleb puts it, “Hundreds of millions of Phar-Mor’s reported inventory was just merchandise driving around in circles on trucks.”

In 1989, three years into serious fraud, Coopers & Lybrand signed off on financial statements showing Phar-Mor had earned a record profit. A company that had never been profitable was suddenly reporting record earnings, and the auditors said everything looked great.

Patrick couldn’t produce documentation for a single one of those fraudulent journal entries. The auditors kept signing off anyway.

When later asked about it, Coopers’ associate general counsel offered this defense: “An accountant is a watchdog but not a bloodhound.” Caleb counters the watchdog was asleep.

Meanwhile, warning signs kept getting ignored or suppressed.

Red Flags and Ripped-Up Memos

In November 1990, a secretary accidentally sent David the wrong financial report with the real numbers, not the fake ones. David called Patrick to his office, but Patrick didn’t panic. He said those were just preliminary numbers that needed adjustments. David believed him. When you have that much riding on something, you don’t go looking for problems.

Then came Charity Imbrie, Phar-Mor’s legal counsel. At a Las Vegas convention in 1991, she heard vendors complaining about unpaid bills and being pressured to support something called the World Basketball League. She wrote a confidential memo documenting her concerns and sent it to David.

He advised her to “rip it up.”

At the bottom of the memo, Charity noted that David said it was “particularly important to rip it up now because of pending financing.” The $200 million deal closed four weeks later. David stood to make more than $2 million from it.

By spring 1991, Phar-Mor was holding back $150 million it owed to vendors. Stan described the scene: “We had cabinets stuffed with held checks at the company. We couldn’t mail them because if we mailed them, the checks would have bounced.”

Vendors stopped shipping products. Shoppers started noticing empty shelves, a terrible look for a company whose whole promise was low prices on everything.

While the fraud machine was falling apart behind the scenes, Mickey was living a life that should have raised its own questions.

Basketball Leagues and Gold Wedding Dresses

Mickey drew a salary of about $500,000 a year, but he also took extra company money for home renovations, credit card bills, and an engagement ring. His second wedding at the Ritz-Carlton in Palm Beach featured a bride in an 18-karat gold mesh gown valued at more than half a million dollars. The dress came with two armed guards.

He had a suite permanently reserved at Caesars Palace. His associate Tom Zawistowski described the lifestyle: “Life was a game. You’ve got all this money coming through your hands, whether you own it or not. That’s for someone else to decide.”

Then there was the basketball league. In 1987, Mickey co-founded the World Basketball League with one bizarre rule: no player could be taller than 6’5″. Despite having Hall of Famer Bob Cousy as co-founder, real teams, and a TV deal, the league lost an estimated $13,000 per game. Mickey structured it so he owned 60% of every franchise. At its peak with 14 teams, that meant he was covering the majority of massive losses, and it was all bankrolled by Phar-Mor.

Back in Youngstown, Mickey built a 14,000-square-foot mansion with an indoor pool and basketball court. He was part of the ownership group pursuing what would become the Colorado Rockies. In Youngstown, he was bigger than life, a civic deity who could do no wrong.

Until an $80,000 check changed everything.

The Check That Brought Down an Empire

Edward DeBartolo Sr., the shopping mall developer and one of Ohio’s wealthiest men, noticed something odd: an $80,000 check from a Phar-Mor account to a travel agency for the World Basketball League. He tipped off the board. The board started pulling threads. The threads didn’t stop.

The collapse was swift:

  • July 28, 1992: Mickey demoted to vice chairman
  • July 31: Mickey, Patrick, and two executives fired
  • August 1: The World Basketball League implodes mid-season
  • August 4: Phar-Mor announces a $350 million charge against earnings
  • August 17: Bankruptcy filed. 25,000 jobs gone.

The community was divided. One radio caller said: “Al Capone, Dillinger, Monus. They’re all the same. He played Youngstown for a bunch of hicks from Mayberry.” Another defended him, saying, “The Monus family has done more good for this valley than any harm.”

The half-finished mansion sat abandoned behind police barricades, insulation exposed, birds moving in.

Justice, Sort Of

A grand jury indicted Mickey on 129 counts in January 1993. The first trial ended in a mistrial because one juror had been bribed by a Mickey associate. Both were charged with jury tampering.

The second trial in May 1995 produced the expected result: guilty on 109 counts. Mickey got 19.5 years, served ten. Patrick served 33 months. John Anderson and Stan Cherelstein, who knew everything and testified, served no prison time at all.

Coopers & Lybrand settled claims for hundreds of millions of dollars. The reputational damage contributed to their merger with Price Waterhouse, forming PricewaterhouseCoopers in 1998.

What This Means for Accounting Professionals

Caleb distills four crucial lessons from the Phar-Mor disaster:

  • Fraud snowballs. Patrick wasn’t hired to commit fraud. He made one small adjustment, then another, then he was maintaining fake books and helping truck phantom inventory between stores. Each step feels only slightly worse than the last until you’re $1.1 billion deep.
  • Audit procedures matter (a lot). Counting four stores out of 300 and telling management which four a field trip, not an audit. The procedures give fraud room to breathe.
  • Fishy journal entries are red flags. Round numbers, no documentation, no entry numbers, and vague account names are signs somebody is making things up.
  • Watch the lifestyle. When someone’s spending is completely detached from legitimate income, it’s worth questioning.

The Phar-Mor case shows what happens when pressure meets rationalization meets opportunity. The red flags were everywhere, from unexplained journal entries to vendors screaming about unpaid bills and a CEO whose lifestyle made no sense. Every procedural shortcut, unchallenged rationalization, and warning memo that gets ripped up creates space for fraud to grow.

Want to hear the full story with all the jaw-dropping details? Listen to the complete Oh My Fraud episode.

Why Are Big Four Firms Laying Off Partners When There Aren’t Enough Accountants to Go Around?

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The accounting profession is facing turbulence on multiple fronts. KPMG is laying off roughly 100 audit partners in the US, while the best artificial intelligence available still gets one out of every five accounting tasks wrong.

In episode 485 of The Accounting Podcast, hosts Blake Oliver and David Leary unpack these converging stories that show the challenges and opportunities facing the profession. From venture-backed firms abandoning their “automate everything” model to a heated controversy over CPE standards with NASBA, the episode paints a complex picture of an industry in transition.

The Hard Truth About AI’s Current Capabilities

A new benchmark study from DualEntry tested 19 AI models across 101 real accounting workflows, and the results are interesting. Claude Opus 3.5, the current darling of AI enthusiasts, achieved the best performance at 79% accuracy. GPT-4o from OpenAI came in slightly behind at 77%. For context, GPT-4 scored only about 40% on the same tasks. It’s progress, but still nowhere near the reliability accounting demands.

The tests covered transaction classification, journal entry creation, bank reconciliations, and month-end close procedures. As Blake pointed out, the problem compounds. “It’s not like you’re automating 80% of the work because you have to clean up that other 20% the AI messed up.” Those errors cascade through financial statements and create cleanup work that erodes efficiency gains.

David put it in relatable terms. “If you had a human employee and ten hours of the week their work was just wrong, you’d probably freak out.”

The gap between 79% and acceptable accuracy for unsupervised work remains enormous. AI can assist and accelerate, but it can’t yet operate independently in accounting.

Tech Firms Abandon the “Automate Everything” Dream

The accuracy issue explains why venture-backed accounting firms are abandoning their original models. Decimal, which raised significant capital and even acquired KPMG Spark’s client base, pivoted away from providing services directly. Instead, they franchise their technology stack to independent firms that handle the actual client work.

“You can’t have SaaS valuations and raise money when you’re a human service business,” David explained, listing the other casualties, including Bench, ScaleFactor, Visor Tax, and Botkeeper. “We’ve seen this over and over again.”

Pilot made a similar move about six months ago with its “local partners” program that lets small practices use Pilot’s technology rather than Pilot doing the work itself. The technology is valuable, but human expertise is still essential.

Meanwhile, traditional players are moving in. H&R Block’s new CEO wants to transform the company from a once-a-year tax relationship to a year-round partner offering bookkeeping, payroll, and business support. Collective is buying OpenLedger. Even a fractional HR provider Austin Alliance Group wants into the bookkeeping space.

This sparked an interesting debate between the hosts. When discussing whether AI will handle routine work while humans focus on advisory, David pushed back. “I think it’s the opposite. Humans will be more involved in the data entry and the compiling of data. AI is really good at just taking scattered numbers and data, unstructured data and summarizing it, which arguably is advisory.”

Blake disagreed, pointing to a real-world example. A San Francisco store let an AI agent named Luna make operational decisions. Luna understaffed during busy periods, over-ordered candles, and lost $13,000. “AI doesn’t have memory the way people do,” Blake explained. Without context and accumulated experience, AI struggles with strategic decisions.

Big Four Layoffs, Demotions, and Massive Fines

While tech firms pivot, the Big Four face their own challenges. KPMG cut roughly 100 partners from its US audit practice (about 10% of audit partners) after too few accepted voluntary early retirement. The firm calls it “multiyear rightsizing,” but as David asked, “Does audit demand ever actually decrease?”

The situation is similar in the UK, where KPMG and EY started demoting equity partners to salaried positions. “Getting to partner at a Big Four firm used to mean a job for life,” Blake noted. Now that security is disappearing.

PwC faces different troubles. They’re paying a $166 million fine related to their audit of the China Evergrande Group, the collapsed property developer accused of inflating revenue by $82 billion. PwC audited them for over ten years before resigning in January 2023. As David observed, they probably made far more than $166 million from the engagement.

PwC is also ending its fully remote option for US tax staff, requiring three days in the office starting July 2026. Going Concern speculates this might be a way to thin headcount without announcing layoffs. Remote workers either need to relocate or quit.

The NASBA Controversy: A Debate Over CPE Standards

One of the episode’s most heated discussions centered on a demand letter Blake received from NASBA regarding comments he made at an AICPA conference. While demonstrating how to use AI to create CPE courses, Blake suggested the traditional approach of creating learning objectives first, then content, was “backward.” He argued it made more sense to let experts teach, then create the objectives based on what they teach.

NASBA’s letter accused him of making “unfavorable, unprofessional, or inappropriate comments” and demanded he cease such remarks immediately.

“If there’s any place for a discussion about NASBA policies, it should be at a conference with 200 L&D people from all the big accounting firms,” David argued. The hosts expressed frustration that NASBA treats different pedagogical approaches as inappropriate rather than worthy of professional debate.

“The pendulum has swung too far towards regulation and too far away from learning,” David said, noting how CPE often becomes just checking boxes rather than actual education. Blake shared a copy of his response to NASBA on his blog. In it, he asks NASBA to explain why expressing a different educational philosophy constitutes unprofessional behavior.

Where the Shortage Hits Hardest

A new index from Sam’s List reveals which states face the worst accountant shortages. Nevada tops the list with just 1.75 accountants per 1,000 residents and 139 professionally prepared returns per accountant, the highest ratio in the study. Nevada’s accounting workforce also fell nearly 30% from 2019 to 2024.

“Sounds like it’s a state accountants don’t want to live in,” David observed. “Accountants probably don’t want that Vegas gambling lifestyle energy.”

While Nevada has the worst per-capita shortage, Texas needs almost 25,000 additional accountants. This puzzled the hosts, given Texas’s population boom from high-tax states. “Are the benefits just not that good, and accountants see through it?” David wondered.

On the flip side, Washington, D.C. has nearly 14 accountants per 1,000 residents, almost ten times Nevada’s rate. New York has a surplus of 27,000 accountants above the national baseline.

Looking Ahead

The picture emerging from these shows AI is transforming accounting but not replacing accountants. The 79% accuracy ceiling, the pivot of tech-first firms, and the Big Four’s struggles all point to the need to find the right collaboration between humans and AI.

For firm leaders, the franchise and partnership models emerging from companies like Decimal and Pilot may offer a more sustainable path than pure automation. For individual practitioners, the message is encouraging. While AI raises the floor on routine tasks, human judgment, experience, and adaptability remain irreplaceable.

Listen to the full episode of The Accounting Podcast for the complete discussion, including more details on the NASBA controversy, state shortage data, and whether Kentucky’s elimination of the 150-hour rule signals the beginning of the end for that requirement nationwide.

The Accounting Profession’s Favorite Performance Metrics Are Now Dangerously Misleading

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PwC Australia cut partners by 35% and staff by nearly 40% since 2023, yet partner income went up 6%. Meanwhile, the IRS says it just had its “most successful filing season in history” with 25% fewer employees. Fewer people are doing more work than ever. But the accounting profession’s core systems for measuring performance, deciding who to hire, and tracking technology investments were built for a different world.

In a recent episode of The Accounting Podcast, hosts Blake Oliver and David Leary talk about a profession transforming from the inside out. From IRS staffing cuts and Big Four workforce reductions to outdated metrics and licensing bottlenecks, we’re seeing technology race ahead while the infrastructure lags.

Tax Season Success Story (with a Catch)

IRS CEO Frank Bisignano told the Senate Finance Committee that the 2025 filing season was remarkably successful despite the agency losing about a quarter of its staff. The IRS received more than 134 million individual returns, 98% of which were filed electronically. Over 90% of filers got refunds in under 21 days, and the average refund jumped 11% to over $3,400.

The agency credited technology upgrades and AI for the performance boost. Using AI and data analytics to identify underreporting, the IRS sent 500,000 letters that prompted corrections, generating $250 million in additional collections. Enforcement revenue was up 12%, and amended return processing improved from six weeks to just three days. Five noncompliance cases alone brought in $2 billion.

“Just five cases and $2 billion,” Blake noted. “That shows there are some real whales out there when it comes to not paying your taxes.”

But David pointed out an interesting wrinkle. There’s still no confirmed IRS commissioner. Bisignano is serving as CEO without congressional approval, yet Congress seems to have accepted this arrangement with little pushback.

Managing by an Outdated Scorecard

For decades, accounting firms have relied on metrics known as LUMBAR: Leverage, Utilization, Margin, Billing rate, and Realization. These metrics made sense when firms billed by the hour and success meant maximizing billable hours. But as AI compresses work time and firms shift to fixed fees and advisory services, these metrics become misleading.

Douglas Slaybaugh argued in Accounting Today that firms need to track different categories entirely. Instead of hours and billing rates, he suggests measuring:

  • Value creation, like advisory revenue as a share of total revenue
  • Automation rates
  • Redefined leverage, like revenue per employee rather than staff-to-partner ratios
  • Organizational health, including “regrettable turnover,” or losing people you wanted to keep
  • Client relationships

Blake was blunt about why traditional metrics fail. “If you go over or under on a job based on a job profitability calculation, which is based on hours, it doesn’t actually change anything in the firm because your staff costs are fixed.” When staff are salaried and clients pay fixed fees, being “over budget” on hours is meaningless. “We get so in the weeds,” he added. “We lose the forest for the trees.”

David pushed further, comparing it to Apple before Steve Jobs returned. The company had separate profit-and-loss statements for every product, optimizing each individually while missing the bigger picture. Jobs collapsed it all into one P&L, recognizing Apple as an ecosystem. “Why do you need all these metrics?” David asked. “Focus on the big picture of your firm.”

The shift is already happening at big firms. Client accounting services is the top growth driver for Top 100 firms for the third straight year, with 85% of firms reporting CAS growth. These services now include cash flow forecasting, budgeting, and strategic finance. That work doesn’t fit hourly billing models, yet many firms still try to manage these engagements with traditional utilization targets.

Licensing Rules as a Talent Bottleneck

Current CPA licensing creates what Jack Castonguay of Hofstra University calls a one-way street: firms can hire accountants and train them in AI, but they can’t easily bring in AI experts and train them in accounting.

“The US licensure model almost forces us to start with accountants and teach them AI skills,” Jack wrote in Bloomberg Tax. “It’s good to have accountants who are well versed in AI, but it would be better to also have AI experts trained in accounting. We should create space for both.”

Jack delivered a sharp observation about recent reforms. “We took away the 150-hour moat around the profession, but ultimately built a wall higher for non-accounting majors seeking to become CPAs.”

Blake agreed strongly. “If you can learn accounting theory on your own and pass the CPA exam, why do we require you to go take all these courses? The CPA exam is supposed to test the knowledge. And if you got the knowledge in another way, why do we care?”

The problem plays out in real life. A viewer shared that, despite having a business degree with an accounting minor, Arizona’s requirements and the need for CPA sign-offs create additional barriers for those with non-traditional backgrounds, such as military service.

There’s some progress. Maryland and Nevada joined roughly 30 states adopting alternative CPA pathways that require a bachelor’s degree, two years of experience, and passing the exam, without the 150-hour rule. But David expressed frustration. “We just got past the 150-hour rule, and we’re going to be on this debate and treadmill now for the next five years.”

Meanwhile, big firms aren’t waiting. Beyond PwC Australia’s dramatic cuts, Deloitte US slashed benefits for non-client-facing staff, halving parental leave from 16 to 8 weeks, cutting PTO by five days, and eliminating the $50,000 adoption and surrogacy benefit.

“What if this is just a way to get people to quit so you don’t have to lay them off from AI later on?” David wondered. The timing makes sense. While 51% of workers said they’d quit over return-to-office mandates in 2025, that number has crashed to just 7% in 2026. Workers are scared, and employers know it.

Betting on AI Without Measuring Results

A Thomson Reuters survey of 1,500 professional services respondents across 27 countries revealed only 18% track AI’s return on investment. Forty-two percent don’t measure at all, and 40% aren’t sure whether they do.

“Pretty much 80% aren’t tracking the return on their AI spend,” David said.

Those who do measure focus on the wrong things. Seventy-seven percent track cost savings, 64% track employee usage, but only 26% track client satisfaction, 23% track revenue growth, and just 17% track new business generation.

“They’re not tracking the correct metrics in their firms,” David noted. “This is not an accounting firm problem. This is professional services.”

The risks of poor AI implementation are real. Deloitte faces investigation in Newfoundland and Labrador after a resident discovered its $1.6 million healthcare report contained AI-generated fake citations. This is at least the third Big Four AI incident.

“They’re selling AI consulting services,” David said, “and then they prove they can’t do it themselves.”

The measurement problem extends beyond AI. Annual recurring revenue (ARR), the metric driving virtually every subscription company’s valuation, has no GAAP definition or standardized calculation. Companies define it however they want. A startup CEO recently made headlines for simply making up ARR numbers.

“If I were in charge of accounting standards, SaaS metrics is the first project I would have FASB do,” Blake said. “It’d be the best thing we could do for tech companies.”

The Path Forward

The accounting profession faces a challenge. The technology works, but the supporting infrastructure hasn’t caught up. Firms still manage by metrics that don’t reflect value creation. Licensing rules block the tech talent firms desperately need. And most organizations aren’t even measuring whether their AI investments pay off.

PwC Australia’s CEO, Kevin Burrowes, put it bluntly: “The future is fewer people doing the same amount or fewer people doing more.” Firms that don’t rebuild their internal systems to match this reality risk falling behind in a rapidly transforming profession.

For the full conversation, including discussions about Representative Ilhan Omar’s accounting disclosure error and more details on all these developments, listen to the complete episode.