Previously, Paul Lloyd-Smith and I focussed on highlighting the disconnection between loss at the point of sale and the back office/finance/business areas.
SAP’s UK expert on GRC for Retail, Paul Lloyd-Smith identifies with the growing trend in the industry to improve controls. He has also seen a trend whereby technology helps improve and update the effectiveness of controls at the point of sale, but notes that this has often left the back office to fend for itself.
The back office is often seen as a cost to the business, resulting in the controls relying upon management trust of the employees to do the right thing. Whilst trust is important we repeatedly see that it only takes one unethical individual to create a devastating impact.
The back office functions are fast becoming the soft underbelly of the retail pig. Only last week we saw £3million worth of equipment being removed from the Jaguar/Land Rover manufacturing plant in the West Midlands. Was this an inside job?” If so, were there indicators of suspicious behaviour that could have raised the alarm ahead of this event?
Regardless of the source of the fraud, technology is now helping retailers to put effective controls in place, both on the point of sale and within back-office functions. In regard to the point of sale, using the internet of things (IoT) and integrated monitoring, it is possible to track higher value items in a much more granular manner. For example, it is possible to identify when stock moves from the shelf to a different location as well as correlating that with a scan of the barcode to prove that it’s declared at the checkouts. If the scan does not happen before the item moves towards the exit, alerts are generated.
Also, regarding the back office, technology solutions are becoming far more sophisticated in their evaluation of business transactions. SAP solutions can handle mass transactional data, especially where SAP HANA is the database. This allows customers to understand both known and unknown patterns to highlight potentially suspicious behaviours within their systems. This could be through suspicious payment transactions, undesirable business partners or outliers in tolerances from historical trends. SAP Fraud Management also embraces machine learning to automatically calibrate alert thresholds as well as using predictive analytics to predict future areas of interest. This all helps investigation teams to ask questions around what might be the next area of attack or to question what’s around the corner.
In a future blog, we’ll try to do just that by predicting what we think the next biggest threats are for the retail sector.
