Detecting attacks, anomalous behavior, and fraud are tasks for machine learning systems
It has been proven that systems that use machine learning can detect anomalies with high accuracy.
I centralize all my purchases on one credit card. A few weeks ago, I was having dinner at home when an unknown purchase appeared in the app, and I promptly blocked the card. I reported the purchase with the hope of a refund.
So far, no response has been given by the bank, as it seems to be the modus operandi of some financial institutions today. But this is beside the point.
You may have experienced a similar situation recently. Did you also notice the suspicious activity in time to take action? Good. If not, the following example may sound even scarier than it looks to me.
Consider a hypothetical situation: You know your entire family's budget, and all their financial transactions are notified on your cell phone. You may judge some of the purchases as odd or a waste of money, but how do you know if one of these suspicious transactions should not be reported?
Upon identifying the purchase, a natural process would be to contact your family member to verify. It may be tiresome, but it seems like a reasonable solution (within this absurd…