I don't know any of the details, but this seems like a good use of data mining:
Mr Tancredi said Verisign's fraud detection kit would help "decrease the time between the attack being launched and the brokerage being able to respond".
Before now, he said, brokerages relied on counter measures such as restrictive stock trading or analysis packages that only spotted a problem when money had gone.
Verisign's software is a module that brokers can add to their in-house trading system that alerts anti-fraud teams to look more closely at trades that exhibit certain behaviour patterns.
"What this self-learning behavioural engine does is look at the different attributes of the event, not necessarily about the computer or where you are logging on from but about the actual transaction, the trade, the amount of the trade," said Mr Tancredi.
"For example have you liquidated all of your assets in stock that you own in order to buy one penny stock?" he said. "Another example is when a customer who normally trades tech stock on Nasdaq all of a sudden trades a penny stock that has to do with health care and is placing a trade four times more than normal."
This is a good use of data mining because, as I said previously:
Data mining works best when there's a well-defined profile you're searching for, a reasonable number of attacks per year, and a low cost of false alarms.
Another news article here.
