Bad apple
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The JC’s amateur guide to systems theory™
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Bad apple
/bæd ˈæpl/ (n.)
One of those mischievous human imps occupying unobserved crevices in the great steampunk machine who, by their human frailty, ruin the best-laid plans of the machines.
On the conventional wisdom, bad apples are the sole remaining fly in the ointment separating us from the sunlit uplands of financial services utopia that our patient labours have earned. Once the last bad apple has been rooted out all will be well in perpetuity.
It’s not clear what we’ll all then do, but this is but a quibble.
The JC ponders human nature and wonders whether we should be quite so credulous. For bad apples gonna be bad.
Perhaps we would be better worrying less about curing humans of their nature, and more about neutralising its unwanted effects.
There will always be bad apples, and they will always seek out, find and exploit zero-day flaws in the system. We should expect this, because it is in their — our —nature. what which is This is what bad apples do.
Bad apples will find zero-day vulnerabilities exactly where the system least expects them, and is therefore paying least attention: ostensibly harmless, sleepy backwaters. LIBOR submissions. The accounting department. The Delta-one index swaps desk. In a family office.
Leaving it to “the system” to detect and destroy bad apples — by policy attestation, outsourced compliance personnel in Manila reading from playbook, “A.I.-powered” software applications — is the Bond villain’s preferred method of despatching Bond: tying him up and leaving him unattended while a nasty-looking but plainly fallible clockwork machine counts down from a thousand.
These risk control systems often trip up peaceable, but ignorant, citizens as they go about their quotidian day. Wised up bad apples have already worked out the flaws and work-arounds.
How to spot a bad apple
The regrettable thing about bad apples is their habit of looking like boring functionaries, and sometimes even good guys, right up to the moment they reveal their rottenness.
This is another way of saying a bad apple that doesn’t look like a bad apple, and that no one believes is a bad apple, isn’t really a bad apple.
It won’t really due to say we must be better at spotting bad apples — thereby spreading by association the stigma of bad appledom on those who failed to spot. Why did they not notice perfidy going on around them? Are they on commonly stupid, or or have their bullshit detectors been somehow disarmed?
Might they have been disarmed by process?
To test this hypothesis consider what happens to those who do call bullshit.
But who the bad apples are depends on who is asking, and, critically, when.
Often, the people who look like heroes — NASDAQ chairmen, visionary innovators, star traders —before the fact only start to look like bad apples after it. And vice versa.
Before and after fact: a play in two acts
Quiz time: taking the information supplied about who everyone thought was the hero, or bad apple, before a celebrated financial markets catastrophe, fill in who you think it might have turned out to be after the event.
| Incident | Before | After | ||
|---|---|---|---|---|
| Hero | Bad Apple | Hero | Bad Apple | |
| Enron | Jeff Skilling Ken Lay Andrew Fastow |
Fortune Journalist Bethany MacLean Short-seller Jim Chanos |
_______ | _______ |
| Madoff | Bernie Madoff Fairfield Sentry The SEC |
Option Trader Harry Markopolos Barron’s Journalist Erin Arvedlund |
_______ | _______ |
| Barings | Nick Leeson Peter “not terribly difficult” Baring |
Er... | _______ | _______ |
| Archegos | Bill Huang Co-heads of PB, everywhere |
Junior credit officer | _______ | _______ |
| FTX | Sam Bankman-Fried Caroline Ellison |
Matt (So it’s a ponzi scheme?) Levine | _______ | _______ |
| WireCard | Markus Braun Jan Marsalek BaFin |
FT Journalist Dan McCrum Internal lawyer Pav Gill Short-seller Matthew Earl |
_______ | _______ |
The JC’s view: the “bad apple” concept is not a good one if the virtue of one’s applehood is only apparent in hindsight.