Book Review - Lying for Money
The optimal amount of fraud is not zero
This is the sentence that will stay with me the longest. In his book, Dan Davies explains how different types of fraud work, arguing that fraud essentially always boils down to a betrayal of trust.
But whose trust in whom? It depends on the type of fraud, naturally. Some of them, like the so-called “Long Firm,” are straightforward. Get some people to trust you, let them invest in your business, and then disappear. Simple, and understandable.
But there are more types of fraud than you can imagine. Another type of scam is very well known: Forgery. Fake a certificate, a degree, or even money. And here things get a little weird. Who is directly harmed? At first glance, as strange as it seems, no one. But Dan Davies argues that something insidious is happening here. A forgery abuses the trust put into the institutions providing the original certificate.
For most day-to-day occurrences, it is simply unfeasible to double and triple check every single document. Is this really a valid passport? Did that person really work there?
At some point, we have to trust that certified papers are, in fact, real. And forgeries abuse exactly that trust.
The book continues to explain historical and modern frauds. We learn of made up countries, pyramid schemes, and insider trading. But the book always asks “How was this possible”, “Why did people trust this fraudster” and “What could we have done differently”.
And to the last question, the answer often is “The optimal amount of fraud is not zero”. Because we have to trust some institutions. Not out of kindness or naivety, but because otherwise, everything would grind to a standstill. We would get bogged down in triple and quadruple checks of everything, there would be no credit, no investment. The chance of being defrauded is a risk people have to be willing to take.
All in all a thought provoking and fun book! Strongly recommended.
Questions to myself:
Can we generalize “The optimal amount of X is not zero?” and under what conditions?
If reducing X causes increasing numbers of externalities and prohibitively many expenses, it might often not be worth it, and single instances of X should not be seen as problems, but as the cost of doing business.
Examples:
- Cheating in school
- Cheating is bad, but reducing cheating to zero can become extremely difficult
- Reducing cheating to zero might, for example, stop schools from using modern curricula, or electronic exams1
- It is probably enough to strongly discourage cheating
- Computer Security(?)
- Depends on the type of data you are using
- There is never a truly safe system
- Putting too high an emphasis on security can ironically decrease security2 or stop people from getting any work done