Abstract:
Worldwide latest food fraud incidents have emphasized the need to reinforce food fraud prevention across the global supply chain, which again is essential not just to protect public health, but also to regain weakened consumer trust in foods, in an economic context where entrepreneurs and regulators acknowledge that confidence is the cornerstone of efficient and productive economies. Unfortunately, current food safety and quality management systems were not initially intended to prevent fraud. Prevention of food fraud involves a particular approach: it must take into account vulnerability assessments and formulate a food fraud mitigation plan, that needs to be continuously updated, being correlated with national and international context on this subject and the fact that food fraud typically appears when the opportunity and the motivation of food crime are strong and the probability of being detected as well as the penalties are
minimal. The central objective of this paper was to develop a functional analysis tool starting with a pre-existing "NSF Fraud Security Model" version, designed to support the large reputable food retailers and authorities in the prediction of potential for fraudulent activity in a variety of products. This case study, focused on three key strategic elements: the prediction, prevention and management of the food fraud mitigation plan in accordance with Guidelines for Implementation of the GFSI recognized schemes. The outcome of this project is a functioning prototype, a concept built over the past 2 years via collaborative sessions with project team members and tested for input from industry and
regulatory representatives. This analysis provides a framework for evaluating the role of science and technology in identification, mitigation, and then prevention.
