Before an e-business can spot and stop on-line fraud, however, it has to know what to look for. This commonly starts by developing a set of rules describing a fraud profile. A fraud profile summarizes the data characteristics that one would expect to find in questionable transactions. There are several common-sense rules that experienced fraud specialists look for in detecting and deterring this type of crime in the terrestrial business environment. They include orders with the following red-flag conditions:
Multiple or single orders that fall just under the "review threshold" level
Shipping addresses matching current or former employee's addresses
All orders with different shipping and billing addresses
Any returns, rejects, and for-credit orders
All P.O. box address orders
These fraud rules can be coupled with models created with data mining software to detect and deter on-line fraud by e-businesses. As in the past, these types of tools gave merchants the ability to search quickly through millions of records in a matter of seconds in order to identify transactions in real or near real time that have the characteristics associated with fraudulent activity. Through the development of these common-sense rules and the use of predictive models created with data mining tools, merchants have the ability to reduce their losses and double-check certain orders before shipping them out.