Shrinkage in the retail sector has tended to be relatively easy to detect and quantify. However, not so easy to identify and resolve is the issue of invisible losses, which fall outside the scope of traditional security measures.
These losses can add up to multiple millions for retailers, says Paul van der Merwe, Director of Business Intelligence company Knowledge Integration Dynamics (KID). The following are examples of invisible losses:
* Stolen merchandise can be presented at a till with a fake receipt (or in many cases no receipt at all) for a cash refund.
* Till operators can conduct totally fictitious refunds - usually to their own staff card or credit/debit card. They note down a product number that can be entered into the till for the transaction. The card number is often manually entered in the belief that this avoids suspicion.
* 'Sweethearting': the process of offering special discounts to family members and/or friends. Till operators apply substantial discounts to the product, over-ride a product price or key a product in as a much cheaper item (such as selling a leather jacket, but only charging for a pair of socks).
"Another developing trend in invisible losses is the use of staff cards or credit/debit cards for a transaction as a way of attempting to avoid being spotted by a cash loss at the till," van der Merwe says. All of this adds up to a significant headache for companies trying to prevent or reduce the scope of retail theft.
However, sophisticated computerised loss prevention solutions can provide some of the answers. "Advances in technology are providing an efficient mechanism for the analysis of existing EPoS (electronic point-of-sale) data to identify patterns and trends that are likely indicators of fraudulent activity," says van der Merwe. "However, a proactive approach is required to prevent fraud. This presents a great challenge to retailers.
"For example, fraud investigators have to sift through rivers of EPoS data that flood the retail office, searching for trends that identify potential fraud. An automated loss prevention system that synthesises this information into usable data would help. Such a system effectively supports fraud analysts by identifying suspect transactions and allowing them to analyse more details regarding transactions. Also, when implementing an effective loss prevention programme, it needs to be remembered that perpetrators take steps to cover their tracks by constructing transactions that appear to all intents and purposes to be entirely legitimate."
Therefore, van der Merwe says, a good loss prevention scheme should look at the identification of fraud indicators as well as controls to prevent perceived fraud. "Insight is the ultimate asset which technology can provide - the ability to filter, analyse and synthesise diverse information to detect new patterns and inter-relationships," he concludes.
For further details contact Paul van der Merwe, KID, (011) 787 8802, e-mail: [email protected]
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