Risk modelling of food fraud motivation - 'OutSmart' intelligent risk model scoping project

Last updated:
10 February 2014
Following the detection of horse meat in beef products, the project will consider food fraud risk with a focus on anti-fraud tools and intelligence gathering from both the food and financial sector. It will develop a framework that will be tested by evaluation by stakeholders.
Study Duration: June 2013 to September 2014
Contractor: NSF International
Project Code: FS102067

Background

The rising trend in globalised food trade is creating both complexity in the supply network and an increased opportunity for food fraud. As a consequence, the food industry is under pressure from food fraudsters. It was reported in 2011 (see external sites link) that organised crime is switching to food fraud from other illegal activities, because detection methods are less developed. Intelligence gathering to fight food fraud is being addressed internationally through a number of government-led initiatives but industry intelligence goes currently largely untapped. Furthermore, supermarket retailers and large food companies/manufacturers are finding the scale of food fraud detection and the range of products potentially affected challenging.

Research Approach

An outline evidence-based risk assessment and motivation analysis framework has been proposed to help identify the potential likelihood of food fraud by product category. The current ‘model’ examines these three main factors:

  • the potential profit a fraudster can make
  • the potential difficulty for the fraudster of making a viable substitution (opportunistically and technically)
  • the likelihood of detection by food businesses or regulators

Obviously fraudsters are more likely to target high value, easy to implement and difficult to detect adulterations/substitutions.

The intention initially is to create measurement indices for each of the three key factors: profit, difficulty and detection, such that food groups/categories can subsequently be grouped/mapped on the framework into high and low risk categories enabling better targeting of surveillance measures and supply network controls. The proposed framework of factors that motivate fraud will be tested through discussions with stakeholders.

The proposed risk model scoping project and the literature and research element will examine the potential for additional factors and summarise known information on fraud.

Results

Additional Info

Dissemination

Published Papers