Some require knowledge of infrastructures, such as transferring nonexistent funds from one account to another and withdrawing the cash before banks catch on. Others require coordination, such as groups of people who resell real estate to one another at inflated prices and then borrow against the resulting equity. Fraud is a particular problem in the health care industry, in part because it's easy for both patients and doctors to submit false insurance claims. And rings of physicians can collaborate to submit false claims or fraudulently refer patients to one another. Government agencies fall victim to vendors who submit multiple invoices, inappropriately increase prices, or fail to deliver goods or services for which they are paid.
Similar abuses occur in the private sector.
The point is that fraud affects everyone, notes SAS' Milley. It also costs consumers in higher credit card fees, citizens in higher taxes, businesses in higher insurance costs. It's in every organization's interest to take a proactive stance in uncovering and preventing fraud. Data Mining Defenses Uncovering fraud can be a tedious, labor-intensive process. Traditionally it has involved time-consuming investigative work, supported by simple computer functions such as flagging insurance claims that exceed a certain limit.