Predicting the future of fraud
If you can think of new types of fraud and assess their likely success rates, you can predict which will flourish.
We are not paying enough attention to how to defend against fraud. That is: against existing fraud. When it comes to likely future fraud, we are pathetic. It is hardly an exaggeration to say that nothing is done at all.
What? How can we protect ourselves against things we do not even know about? Does that make sense? Yes, it does.
It is possible to predict the likely trends in fraud. Some trends depend, quite simply, on very evident developments. Do you see more cellphones out there? Then you should worry about mobile malware. Do you think email spam will be eradicated soon? Then you should suspect a rise in unwanted messages, distributed using SMS and voice, and by malware.
Other likely trends are simply a matter of human ingenuity among fraudsters. What new tricks and variants of old tricks will they develop? Those that are successful will become common. If you can think of new types of fraud and assess their likely success rates, you will be able to predict which ones will flourish.
It is important to predict the likely trends in fraud. If you can predict what will hurt in a few years, you have time to prepare yourself. If you represent a financial service provider, that might mean limiting your liability. If you develop technology, you may be able to build the product that everybody soon will need. To protect themselves. And if you represent government, you may have time to develop laws and policies to limit the financial incentives for criminals. No matter who you are, knowing the likely future is helpful.
Now, predicting the likely future does not have to be difficult. Let me give you an example of a type of fraud that does not yet exist, but which I hope to convince you is not so unlikely.
Fraud typically depends on a combination of psychological vulnerabilities and technical or systemic weaknesses. Unrealistic optimism is an example of a psychological vulnerability. Poor spam filters is a technical vulnerability. An example of a systemic vulnerablity is the fact that fraudulent checks may appear to have cleared before they eventually bounce. (This is due to what computer scientists call a "time-out", which means that if the check does not clear within a certain time, then the bank will tell you that it cleared and let you access the money … but of course ask for it back when the check eventually bounces.)
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