# The Stakes Change at Funding
> A prop firm evaluation pass is measured while a breach costs a fee. Funding changes what a breach costs, so the first funded weeks need their own reading.
**Published:** 2026-10-26  
**Reading time:** 9 min read  
**Tags:** prop-firms, funded-accounts, prop-firm-evaluation, trading-psychology, choking-under-pressure
A prop firm evaluation pass shows how a trader handled the evaluation: a profit target, loss limits, often a deadline, and a fee as the most they could lose. Funding changes those conditions. The target usually goes, and so does any deadline. The trader's own money at risk is still only what they have paid in fees. A breach can now cost more: an account they earned, and payouts that are real money. In one study of large rewards, researchers found that in tasks that need thought, performance can fall at the largest stakes: in their field experiment in rural India, people who could earn close to a month's average spending from a single game reached the top performance level in 6.3% of games, against 25.6% for people offered a hundredth of that. More pay helped on a task that needed only effort. A pass is a measurement taken under the old conditions, so read the first funded weeks in your own records.

## What a pass measures

[An evaluation](/glossary/prop-firm-challenge) is built to filter. It sets a profit target and [loss limits](/glossary/daily-loss-limit), often a deadline, and many firms add [consistency rules](/blog/the-consistency-rule-problem), so that the traders who pass have shown they can follow a plan. A pass is real information. It shows how this trader behaved while a breach cost the fee and the next step was a funded account.

It is easy to read a pass as proof of discipline. It is a measurement, and a measurement holds for the conditions it was taken under. The question for a firm is how much of the pass carries over once those conditions change. Funding changes them in more than one direction.

## Before and after the pass

Take one trader at one firm and look at three things.

| | During the evaluation | After the pass |
|---|---|---|
| The trader's own money at risk | The fee | The fees already paid |
| Profit target (and any deadline) | Applies | Usually gone |
| What a breach costs | The attempt | The account, and the payouts it could pay |

**Own money at risk.** The trader puts no trading money of their own into a funded account; what they have at risk is what they paid in fees. At some firms the funded account is still simulated, and what becomes real is the payout. This is the strongest point in the view that a funded trader has little of their own at stake.

**The target and the clock.** A funded account usually has no profit target to reach. At firms whose evaluation runs to a deadline, the clock stops too.

**What a breach costs.** Before the pass, a breach ended an attempt. After it, a breach ends an account the trader earned, and the payouts it could have paid. Getting back usually means a new evaluation.

The first does not make the trader's position harder, the second makes it easier, and the third makes each decision weigh more. The researchers below varied something close to the third: how much a good result paid, using games and arithmetic rather than trades.

## The large-stakes experiments

Dan Ariely, Uri Gneezy, George Loewenstein and Nina Mazar tested what happens when the reward for doing well is large ([*Review of Economic Studies*, 2009](https://doi.org/10.1111/j.1467-937X.2009.00534.x); the figures below are from the paper's 2005 working version, see Sources). Their main experiment ran late in 2002 in a rural town in India. Eighty-seven people played six games of creativity, concentration and motor skill, and the researchers assigned each of them at random to one of three payment levels: 4, 40 or 400 rupees for a "very good" result in each game, and half that for a "good" one. At the top level, a "very good" result in one game paid close to the average monthly spending of one person in rural India, which was 495 rupees.

People offered 400 rupees reached the "very good" level in 6.3% of games. People offered 40 rupees reached it in 22.2% of games, and people offered 4 rupees in 25.6%. The group with the most at stake reached the top level about a quarter as often as the group with the least. They also earned less of the money on offer to them: 19.5%, against 35.4% for the smallest payment and 36.7% for the middle one. The difference between the low and middle groups was not statistically significant. The gap between those two groups and the top one was.

A second experiment, with 24 students at MIT, paid each student at a low and a high level: for adding numbers, up to $30 at the low level and up to $300 at the high one. The higher pay made them worse at adding numbers and better at pressing two keys in turn, a task that needed only effort. The published paper's own summary: "With some important exceptions, very high reward levels had a detrimental effect on performance."

## Choking under pressure, and our reading

Psychologists call this kind of drop choking under pressure. Roy Baumeister's 1984 paper defined it as "performance decrements under circumstances that increase the importance of good or improved performance" ([*Journal of Personality and Social Psychology*](https://doi.org/10.1037/0022-3514.46.3.610)). His experiments used skill tasks, and the games in India were not trades.

Our reading, which neither paper tests, is that a trading decision sits with the tasks that need thought, and that funding raises the importance of each one. From a pass taken while a breach cost a fee, a firm learns less about the funded weeks than the clean result suggests. The other two can pull the other way: the target has usually gone, and the trader's own money is no more at risk than it was. Traders can differ in which effect wins, and you cannot read which from the pass, because it was taken before any of them applied.

The same reading changes what a firm can conclude from an early breach. The trader who breaks a funded account in its first weeks is the trader who passed, and who kept to the firm's loss limits for the whole evaluation. A firm that answers with more rules, or [more teaching about the rules](/blog/the-education-gap), is teaching that trader something they had already shown they knew.

## Checks your own records can run

Your records already hold the test. Three checks need no new data.

- **Breach rate by account age.** For each week since funding, divide that week's breaches by the funded accounts still open at its start. If the first weeks carry a higher rate than the weeks after, that period is a risk window of its own.
- **Each trader against their own evaluation.** The evaluation is a [behavioural baseline](/blog/prop-firm-trader-retention-playbook): normal position size, trades per session, how quickly the trader re-enters after a loss. Drift from that baseline in the first funded weeks is the change the pass could not measure.
- **Contact in those weeks.** List every contact your firm has with a funded trader, by day since funding, up to the first payout. [Our July post](/blog/the-expensive-silence) looks at how quiet that stretch can be.

The evaluation has [its own effect on behaviour](/blog/the-evaluation-produces-what-it-filters-for), and these checks do not untangle it. The first two show whether traders in their first funded weeks behave as they did in the evaluation, which is the question firms use a pass to answer. If they do, the pass carried over at your firm, and this argument does not apply to your book. If the first weeks carry a higher breach rate instead, those are the weeks to stay in touch, and the third check shows how much contact they get now.

## Where a coaching call fits

Discentra is designed to place [a coaching call](/use-cases/prevent-tilt) when a warning sign appears in the firm's own trade data, such as [a larger order within a minute of a loss](/glossary/revenge-trading), whether the account is a week old or a year old. The call is meant to reach the trader in [the minutes after a loss](/blog/how-long-does-tilt-last), before the next order, and to ask what their own plan says about that moment. It does not tell them to stop, never invites a trade or a deposit, and cannot block an order. If a call turns up distress, Discentra is designed to alert a named person at the firm. Coaching, not financial advice.

## Limits of this research

Neither paper measured traders or trades. In India the participants were villagers playing games; at MIT they were students adding numbers and pressing keys; Baumeister's experiments used skill tasks. The samples were small: 87 people across three payment levels in India, and 24 students at MIT. More money helped where a task needed only effort, so the finding is about tasks that need thought. Nothing here measured a funded account.

## Sources and notes

- **The large-stakes study**: Dan Ariely, Uri Gneezy, George Loewenstein and Nina Mazar, "Large Stakes and Big Mistakes", *Review of Economic Studies* 76(2), 2009, pages 451-469 ([publisher's record](https://doi.org/10.1111/j.1467-937X.2009.00534.x)). The quotation is from the published abstract, [read on RePEc/IDEAS](https://ideas.repec.org/a/oup/restud/v76y2009i2p451-469.html) on 25 October 2026. We read the figures (6.3%, 22.2% and 25.6%; 19.5%, 35.4% and 36.7%), the 87 participants, the payment levels, the 495-rupee comparison and the MIT results in the earlier version of the paper, [Federal Reserve Bank of Boston Working Paper 05-11](https://www.bostonfed.org/-/media/Documents/Workingpapers/PDF/wp0511.pdf) (2005), and did not check the published article's tables.
- **An independent review**: Emir Kamenica, "Behavioral Economics and Psychology of Incentives", *Annual Review of Economics* 4, 2012, pages 427-452 ([publisher's record](https://doi.org/10.1146/annurev-economics-080511-110909)), lists paying too much among the ways incentives can backfire, and choking among the explanations.
- **About a quarter as often**: 6.3 divided by 25.6 is 0.246.
- **Choking under pressure**: Roy F. Baumeister, "Choking under pressure: Self-consciousness and paradoxical effects of incentives on skillful performance", *Journal of Personality and Social Psychology* 46(3), 1984, pages 610-620 ([PubMed record](https://pubmed.ncbi.nlm.nih.gov/6707866/)). We quote the definition from the paper's abstract.
- **Our reading**: applying these findings to prop firm evaluations and funded accounts is our inference. Neither paper measured traders, accounts or breaches.
## Frequently asked questions

### What does a pass in a prop firm evaluation measure?

How a trader handled the evaluation's conditions: a profit target, loss limits, often a deadline, and a fee as the most they could lose. That is real information, taken before funding changed what a breach costs: an account the trader earned, and payouts that are real money. A firm can see whether the pass holds by comparing each trader's first funded weeks with their own evaluation: position size, trades per session, and how quickly they re-enter after a loss.

### Can larger rewards make people perform worse?

In tasks that need thought, they can. In a field experiment published in the Review of Economic Studies in 2009 (the figures here are from its 2005 working-paper version), people in rural India who could earn close to a month's average spending from a single game reached the top performance level in 6.3% of games, against 25.6% for people offered a hundredth of that. At MIT, higher pay made students worse at adding numbers and better at pressing keys, a task that needed only effort. The experiments measured villagers and students, not traders.

### Why can pressure make skilled people perform worse?

Psychologists call it choking under pressure. Roy Baumeister defined it in 1984 as performance falling in circumstances that make good performance matter more, and his experiments produced it with competition, a cash incentive and an audience. His explanation, for practised skill tasks, is that pressure turns a person's attention onto a task they usually perform without thinking about it. The experiments were not about trading.

### How can a prop firm check whether breaches cluster early in a funded account?

For each week since funding, divide that week's breaches by the funded accounts still open at its start, and compare the first weeks' rate with the weeks after. Then compare each funded trader with their own evaluation: position size, trades per session, and how quickly they re-enter after a loss. If the breach rate or the drift is higher in the first weeks, that period needs its own attention, whatever the pass said.


---

This is a Markdown mirror of [https://discentra.ai/blog/the-stakes-change-at-funding](https://discentra.ai/blog/the-stakes-change-at-funding). Provided for LLM citation. © Discentra Ltd. Coaching, not financial advice.