Fraud rings often cluster ethnically not due to predisposition, but because they require extreme levels of trust for co-conspirators to remain loyal under threat of prison. This leverages pre-existing high-trust networks like family and community, an extreme version of how legitimate businesses also hire from trusted circles.

The absurd plots and bad grammar in phishing emails are a feature, not a bug. They efficiently screen out discerning individuals, ensuring that scammers only waste their time interacting with the recipients most likely to fall for the con from the outset.

Smart investors who are experts in their niche often display profound ignorance when commenting on adjacent fields, such as the legal mechanics of an M&A deal. This reveals the extreme narrowness of true expertise and the danger of overconfidence for even the most intelligent professionals.

Sophisticated fraudsters exploit socio-political tensions by strategically deploying accusations of racism. This tactic is used to deter investigations, shame government actors into compliance, and secure a "free pass" to continue stealing hundreds of millions of dollars.

As Charlie Munger taught, incentive-caused bias is powerful because it causes people to rationalize actions they might otherwise find unethical. When compensation depends on a certain behavior, the human brain twists reality to justify that behavior, as seen in the Wells Fargo fake accounts scandal.

Viewing fraud as its own form of infrastructure, with its own "APIs of evil," provides transferable lessons. By understanding how fraudulent systems are built and operate, we can gain insights to better architect and secure the legitimate, critical infrastructure in our lives.

Instead of a moral failing, corruption is a predictable outcome of game theory. If a system contains an exploit, a subset of people will maximize it. The solution is not appealing to morality but designing radically transparent systems that remove the opportunity to exploit.

Large-scale fraud operates like a business with a supply chain of specialized services like incorporation agents, mail services, and accountants. While some tools are generic (Excel), graphing the use of shared, specialized infrastructure can quickly unravel entire fraud networks.

A defender's key advantage is their massive dataset of legitimate activity. Machine learning excels by modeling the messy, typo-ridden chaos of real business data. Fraudsters, however sophisticated, cannot perfectly replicate this organic "noise," causing their cleaner, fabricated patterns to stand out as anomalies.