Yesterday I mentioned a small analytic project we are doing for a retail customer around money laundering. Joel Gary commented and linked to an article in his local press about the rise of anti-fraud analytic companies in his neck of California.
Money laundering is a big issue in the UK, not necessarily because it is a major problem, but more because of its political focus. This manifests itself in two ways: the need to establish that you are who you say that you are when we you open a bank account (see here & here) and need to track large cash transactions both in the banking world and at stores. Somewhere there is conception that cash is not a legitimate form of currency; cash is the proceeds of crime (be it drug dealing or VAT (sales tax) avoidance) It is also the way which people without bank accounts and credit cards trade, and often the main part of the daily finances of all those cornershops that sell the odd carton of milk and a newspaper to passers by. So tracking potential laundering in retail transactions is not that clear cut; we need to detect the crime from the “noise”
Looking at fraud – we have two significant strands with credit cards; falsely obtain cards from providers by using stolen ids, which was the main focus in the San Diego Union Tribune piece Joel cited – that is fraudulent applications. The second is where a legitimate card is hijacked (stolen, cloned, or just the details used on the web) Here we need to develop techniques to verify the fraud at transaction time. Goodness know how much the banks are doing to achieve this.
But fraud is not restricted to credit card finance. Fraudulent return of goods is also costing retailers money. Again we need systems that can be used at point of sale to indicate whether the refund is valid. And this needs to happen quickly: the customer should not feel they are being questioned, and the extra transaction time should not slow the sales process too much.