A growing global and digital environment can create organisational challenges to developing a fraud prevention and detection strategy. Geographically and technically diverse platforms resulting from market expansion or mergers and acquisitions impact an organisation’s ability to manage fraud risk from a single integrated framework. Understanding some of the key technology and data considerations can help companies to create a long term strategy for an effective fraud risk program.

While the drive to control IT costs can impact management’s ability to implement a sophisticated, often expensive, enterprise-wide real-time reporting system, manual processes are prone to errors which can result in even greater losses, fines and sanctions. A seamless, integrated fraud analytics program provides executives and leadership with a consolidated prevention, detection, response and reporting mechanism. There are a number of key technology and data considerations, some of which are discussed here, including data warehousing, data loss and transformation, fraud model validation, and the role of visualisation in the investigative process.

Many organisations choose to utilise traditional structured data warehouses to aggregate and analyse key business process information for fraud. Once operational business data has been standardised and mapped into a common data model within the warehouse, organisations can more readily identify trends and anomalies across lines of business and geographies from a centralised point. For example, once overseas sales data has been mapped into the warehouse and foreign currencies are converted, unusually steep product discount percentages, taking into account volume discounts, may more readily be detected as a potential kickback scheme requiring review.

Jan-Mar 2015 Issue