Food fraud is an interdisciplinary phenomenon that poses a potential threat to consumers and a challenge to food companies. Given the increase in the number of adulteratifjons in recent decades, food companies are forced to take passive and active measures. In this master's thesis, we’ve developed a system for assessing the vulnerability of raw materials to fraud, focusing on the risk factor “History of fraud. In order to quantify the factor, we created a database of detected cases of food fraud. We collected data on food fraud, transformed it into an appropriate format and arranged it into a structured database. We analyzed the database, checked the impact of the Russian-Ukranian
conflict and the COVID-19 pandemic on the trend in the number of food fraud cases and checked the share of food fraud cases by food groups. We then placed the database in the food fraud risk assessment model, where it served as the basis for the risk factor “Fraud history”. We also determined and quantified the risk factors “Nature of raw material”, “Sophistication of analysis”, “Supply chain” and “Economic factor”. We linked these risk factors into a matrix for assessing the vulnerability of raw materials to food fraud. The best source for the database was the European Commission’s KC-FFQ (Knowledge Centre for Food Fraud and Quality) website, which provided us with free,
high-quality data on food fraud. The number of food fraud cases between 2017 and 2024 is increasing. We have detected a connection between the Russian-Ukranian conflict, the COVID-19 pandemic and the growth in the number of counterfeits. Using criminological theory and the BRCGS standard, we have managed to create a food fraud risk assessment model, which is quantified, easy to use, fast to update and has the desired responsiveness.
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