What a Lie Costs

Part 7 of 8 in a series on lies and deception at work.

One lie can cost more than the harm it hides. What the research says about broken trust, endless checking, fraud and the hidden price of suspicion at work.

You’ve been given $6. You can keep it, or pass it to a stranger in another room. If you pass it, it triples to $18, and the stranger decides how much to send back.

Before the first round, a note arrives from the stranger promising to send you $12. You pass. You get nothing back. Before the second round, another note: “Let’s cooperate. I’ll really return $12 this time.” You pass again. Nothing.

That was how the game began for half of the 262 people in a study published in 2006 by Maurice Schweitzer, John Hershey and Eric Bradlow of the Wharton School. The stranger didn’t exist. Everyone played against the same script: nothing back for two rounds, then an even split of $9 in every round after that. The other half of the participants got the same treatment without the notes. One group was robbed. The other was robbed and lied to.

Both groups began to trust again once the partner started behaving. They didn’t end up in the same place. Those who had only been let down largely recovered. Those who had also been lied to never fully did, even with a promise, an apology and a steady run of fair play afterwards.

The same money went missing in both groups. What people couldn’t get past was the lie.

This essay is about that gap. Discussions of what lies cost at work usually start with fraud, because fraud comes with figures, and I’ll get to them. But the bigger cost of a lie is rarely what it takes. It’s what everyone has to do afterwards.

The lie, not the loss

The detail of the Wharton study is worth a closer look.

After the second round, some participants got a written apology from their partner. Others got a promise to send back $9 every round from then on. Some got both, and some got nothing. The apology made no measurable difference, though the authors wondered whether a fuller one might have. The promise sped recovery up, but prior deception blunted it. For people who’d been lied to, a promise was just another note, and notes were what had robbed them.

The researchers also added up the money. The liars did better in the first two rounds and worse afterwards. Over the long run, the two players together earned about a quarter less after deception than after the same bad behaviour without it. The lie didn’t just move money from one player to the other. It shrank the pot.

The study has limits. The participants were mostly students aged 19 to 22, playing an anonymous stranger. Everyone got to see the partner’s later good behaviour, which the authors admit favoured recovery, and they expected a lie inside an established relationship to do more damage, not less. At work, someone caught lying often doesn’t get the chance to prove they’ve changed. If anything, the study flatters liars.

The reason the lie does more damage is easy to see. A partner who takes the money might have misread the game or needed the money. A partner who promises to pay you this time, and doesn’t, has told you what they’re like. Taking the money can be a one-off. A lie is information about the future.

What trust saves

In 1972, the year he won the Nobel Prize in economics, Kenneth Arrow wrote that “virtually every commercial transaction has within itself an element of trust”.

Work is full of small transactions like that. A colleague says the file has gone to the client. Someone says they’ve tested the fix. You take their word, and you save the time it would take to check. Across a working week that adds up, and trust starts to look less like a feeling and more like an efficiency. In the first essay I argued that believing people by default is usually the right call. This is a large part of why: it’s cheap.

A lie ends the saving. From then on, you check.

Maurice Schweitzer, from the Wharton study, came back to this in 2015 with Emma Levine, a different Levine from the Tim Levine in earlier essays. They built a game around exactly that choice, called Rely-or-Verify. One player sends another a message saying whether the money in a jar of coins is odd or even. Relying on an accurate message earns the most, and relying on a false one earns nothing. Or the second player can pay 50 cents to check, which guarantees them $1 either way.

Before playing, participants learned how their partner had behaved in four earlier rounds of another game. Some partners had told the truth every time, even when it cost the other person money. Others had told kind lies that helped the person they were told to. Faced with an honest partner, 57% relied on the message. Faced with a kind liar, 37% did.

The other half of the experiment is what makes it interesting. When participants instead decided whether to hand money over to the kind liars, they trusted them more than the honest partners, 57% to 40%. People saw the kind liars as well-meaning and trusted their intentions. They just didn’t trust their word.

The kind lie

The researchers’ own example of a kind lie is telling a colleague they gave an excellent presentation when they didn’t. I’ve told that one. At a company conference, as I admitted in the fourth essay, I told someone their talk was good when it was full of holes. On this evidence it made me look kind and made my opinion worth less. The next time I tell someone their talk was good, they have no way of knowing whether I mean it.

It didn’t stay kind for long. Senior staff praised the talk and seemed to think it was good. A fair number of other people saw the holes. They talked about its shortfalls and inaccuracies, and about whether the person who gave it should be in the job at all. I believe the presenter got wind of what was being said, and it affected them. In the end, time proved the presentation was flawed. By then, nobody cared.

So the person I was being kind to paid twice. They didn’t get honest feedback when it could still have helped, and they got the verdict anyway, second-hand, as gossip. The truth doesn’t go away when you’re kind about it. It goes round the side, as the fifth essay showed.

We may overestimate what the truth would have cost. In a 2018 study, Emma Levine and Taya Cohen asked people to be completely honest in every conversation for three days, while others predicted what that would be like. The real experience was more pleasant than people expected and did less harm to their relationships.

Checking the histogram

The screen on the back of a camera lies. It’s bright and flattering, and it will tell you a shot is fine when the highlights are burnt out. So you check the histogram instead, every time, even though it’s slower.

That’s what a colleague becomes once you’ve caught them lying. You still work with them. You just check everything they show you.

This is where the bill really runs up at work. Every figure from that person gets re-run. None of it appears in a budget, and very little of it is the liar’s time. It’s everyone else’s.

I’ve paid that bill myself. At the company where the audit reports were changed, which I described in the second essay, trust between the IT team and some of the senior staff had gone. After meetings with them, I sent follow-up emails setting out what had been agreed, with my manager copied in. I wouldn’t start the work until someone emailed back to confirm, and sometimes I had to chase them for it. As far as I know, the whole IT team did the same. The cover-your-arse emails were the IT director’s idea.

It all took time, and it slowed down everything we did. But trust had been broken, and with those people we felt we had to cover ourselves.

The checking spreads. When rounded figures turn up in one set of reports, the people who find them start to wonder what else has been rounded. One lie lowers the value of everything else that comes from the same place.

The part you can count

Now the figures.

Occupational fraud is the lie with a price tag: people using their jobs to cheat the organisation that employs them. The Association of Certified Fraud Examiners published its first report on it in 1996 and now publishes one every two years. The 2026 edition covers 2,402 cases in 143 countries. The median case cost $104,000, and the average was nearly $1.5 million. A handful of enormous cases pulled the average up.

You’ll often see a bigger number from the same report: that organisations lose about 5% of their revenue to fraud each year. Treat that one carefully. It’s what the fraud examiners estimate, not something anyone has measured. It may well be too low, since undiscovered fraud can’t be counted, but it’s an informed guess.

The more useful finding is about time. A typical fraud ran for 12 months before anyone caught it. Frauds found within six months had a median loss of $40,000, while those that ran for more than five years had a median loss of more than $1.1 million. A lie that works keeps working, and it grows.

David Welsh, Lisa Ordóñez and their colleagues found the same pattern in miniature. In four multi-round studies published in 2015, small ethical lapses made larger ones more likely later. People got there by gradually talking themselves round, a process psychologists call moral disengagement. The rounded sales figures I described in the fourth essay were a cousin of this. Each rounding was small. Over time they added up to a gap big enough to show against the company’s actual income.

The price of being caught rarely matches the gain. When US regulators acted against Wells Fargo in 2016 over accounts its staff had opened without customers’ permission, which came up in the fourth essay, the bank’s own analysis found around $2.4 million in fees charged on the accounts it had identified. The bank paid $185 million in penalties that year. In 2020 it agreed to pay $3 billion more to settle criminal and civil investigations.

One more figure from the fraud report matters for this series. The most common way frauds came to light was a tip, in 43% of cases, and more than half of those tips came from employees. The main thing standing between an organisation and its liars isn’t software. It’s honest staff willing to say something.

The cost you can’t invoice

Fraud is the cost of lying that shows up in the accounts. At work, the larger cost shows up in people, and it’s harder to price.

In 2002 Kurt Dirks and Donald Ferrin combined 106 samples from four decades of research on trust in leaders. People who trusted their managers were much more satisfied with their jobs and more committed to their employers, and less inclined to be thinking about leaving. The link with how well they did their jobs was weaker. These are correlations, not proof, and satisfied people may simply trust more easily. They still point the same way as everything else here.

Sandra Robinson’s research gets closer to cause and effect. She studied the psychological contract: the unwritten deal between employee and employer, made up of what each believes the other has promised. In a 1994 study with Denise Rousseau, more than half of a group of recent graduates said their employer had broken that deal within two years. In 1996 she followed 125 newly hired managers over two and a half years. Those who felt their employer had broken its promises lost trust in it. As trust fell, so did their performance and their willingness to go beyond the job, and they became less likely to plan on staying.

Not every broken promise is a lie. A promise made at interview that nobody meant to keep is.

Then there’s the cost of people leaving. In 2014 Oxford Economics, in a report for the insurer Unum, estimated the average cost of replacing a UK employee at £30,614. Most of that was lost output while the new starter spent around 28 weeks getting up to speed. The figure is old, it was paid for by a company that sells income protection, and it varies a lot between jobs, so take it as a rough scale rather than a price.

The people who leave over a lie aren’t a random sample, either. As I described in the sixth essay, those who can see through a story and can’t live with it are often the first to go.

I saw what one of those “everyone’s happy” reports from the fourth essay was covering. In that department you could feel the atmosphere as soon as you walked into the room. Performance suffered. Company revenue dipped a little, and the staff there earned less commission. It went on until a new manager took over.

The truth about that department didn’t go up to the directors. It came to the IT office. People from that team would come in to let off steam. We had an unwritten rule, “what’s said in IT stays in IT”, and they came to us because they trusted us. It was somewhere they could tell the truth.

The company paid for that team’s low morale in revenue and commission. The report upstairs had said everyone was fine. The truth hadn’t disappeared. It had just stopped travelling upwards.

The cost of suspicion

If lies are this expensive, the obvious answer is to watch everyone more closely. In the first essay I said suspicion has costs of its own. Here they are.

In 2006 the economists Armin Falk and Michael Kosfeld ran a laboratory game in which one player, the employer, could impose a minimum performance requirement on the other before they chose how much to contribute. Most players contributed less once a minimum was imposed. Many of those who cut back said the control felt like a signal of distrust and took away their choice. Employers who trusted got more, on average, than employers who controlled.

One team of researchers has since repeated the experiment four times, with 476 people. They found the same reaction, but usually not strong enough to make control a bad deal for the employer. That’s a fairer summary than the original: distrust has a price, but it doesn’t always outweigh what control buys.

Monitoring has a stranger cost. In 2023 Chase Thiel and colleagues published research suggesting that closely monitored employees can end up breaking more rules, not fewer. Their explanation is that monitoring takes away people’s sense of being in charge of their own conduct, which makes it easier to shift the moral responsibility elsewhere. If the system is watching, behaving well becomes the system’s job. The effect was weaker where people felt their organisation treated them fairly.

I’ve been on the watching side of this. In an IT role I was asked whether the systems could show how productive staff were, which I described in the third essay. The logs could show who edited which file and when. They couldn’t show who was honest.

The National Research Council’s 2003 review of the polygraph, also discussed in the third essay, warned that screening everyone for lies can lower morale and productivity, and drive away the skilled people an organisation most wants to keep.

Suspicion doesn’t catch more liars. As I argued in the first essay, it punishes the nervous and the awkward. If the guess in the fourth essay is right, the most prolific liars are the plausible ones who sail through. What suspicion does reliably is tell honest people they’re assumed to be otherwise.

Who pays

Go back to the Wharton game. The liar came out ahead for two rounds and behind for the rest. The person lied to paid in every round they held back. The pot shrank for both.

Work spreads the bill more widely and less fairly. The person who tells the lie often gains for a while. The colleague who was lied to pays in time spent checking. The honest people around them pay too, because once a lie has been found it’s hard to know whose word to take. The organisation pays in fraud and in people: the ones who leave, and the ones who stay but stop offering anything extra.

The usual response is to make lying more expensive, with more checks and closer monitoring. The evidence here suggests that route carries a bill of its own. The other route is to make the truth cheaper, so the person with bad news, or one sale short of a target, can say so without it costing them. The fourth essay and the sixth looked at why the truth gets expensive at work. The last essay in the series asks what’s fair when it comes to catching people out.

Of all these costs, the one I’ve felt most is the checking. Every confirmation email I sent and every reply I chased was time taken from the job I was paid to do, because someone else hadn’t told the truth. The most damaging cost I’ve seen, though, is the one nobody measures: the truth stops reaching the people who could act on it. When staff would rather tell the IT office than their own managers, the company is running on the wrong information. Again and again, I’ve seen honest people pay for lies far more than liars do.

Sources and further reading

Arrow, K. J. (1972). Gifts and exchanges. Philosophy & Public Affairs, 1, 343–362.

Association of Certified Fraud Examiners (2026). Occupational Fraud 2026: A Report to the Nations.

Consumer Financial Protection Bureau (2016). Enforcement action: Wells Fargo Bank, N.A.

Dirks, K. T. & Ferrin, D. L. (2002). Trust in leadership: meta-analytic findings and implications for research and practice. Journal of Applied Psychology, 87, 611–628.

Falk, A. & Kosfeld, M. (2006). The hidden costs of control. American Economic Review, 96, 1611–1630.

Levine, E. E. & Cohen, T. R. (2018). You can handle the truth: mispredicting the consequences of honest communication. Journal of Experimental Psychology: General, 147, 1400–1429.

Levine, E. E. & Schweitzer, M. E. (2015). Prosocial lies: when deception breeds trust. Organizational Behavior and Human Decision Processes, 126, 88–106.

National Research Council (2003). The Polygraph and Lie Detection. National Academies Press.

Oxford Economics (2014). The Cost of Brain Drain. Report for Unum.

Robinson, S. L. & Rousseau, D. M. (1994). Violating the psychological contract: not the exception but the norm. Journal of Organizational Behavior, 15, 245–259.

Robinson, S. L. (1996). Trust and breach of the psychological contract. Administrative Science Quarterly, 41, 574–599.

Schweitzer, M. E., Hershey, J. C. & Bradlow, E. T. (2006). Promises and lies: restoring violated trust. Organizational Behavior and Human Decision Processes, 101, 1–19.

Thiel, C. E., Bonner, J., Bush, J. T., Welsh, D. T. & Garud, N. (2023). Stripped of agency: the paradoxical effect of employee monitoring on deviance. Journal of Management, 49, 709–740.

Welsh, D. T., Ordóñez, L. D., Snyder, D. G. & Christian, M. S. (2015). The slippery slope: how small ethical transgressions pave the way for larger future transgressions. Journal of Applied Psychology, 100, 114–127.

Ziegelmeyer, A., Schmelz, K. & Ploner, M. (2012). Hidden costs of control: four repetitions and an extension. Experimental Economics, 15, 323–340.