The EC Monthly Reports of Agri-Food Fraud Suspicions reports are a useful tool for estimating fraud incidents, signposted on FAN’s Reports page. The March 2025 report was added earlier this week and can be found here.
FAN has produced this rolling 3-month graphical analysis. We have excluded cases which appear to be unauthorised sale but no intent to mislead consumers of the content/ingredients of a food pack (e.g. unapproved food additives, novel foods), excluded unauthorised health claims on supplements, and we have excluded residues and contaminants above legal limits. We have grouped the remaining incidents into crude categories. Our analysis is subjective but intended to give a high-level overview. One consistent stand-out is unlicenced production, trade or import in high risk foods, often backed up by forged documentation. Although the details behind the reports are not public, allegorical evidence is that these cases are not just "grey market" trade to small shops and market stalls. Much of the suspicious trade enters mainstream markets.
As with all incident collation reports, interpretation must be drawn with care. This EC collation is drawn from the iRASSF system – these are not confirmed as fraud, and the root cause of each issue is usually not public. There are important differences in the data sources, and thus the interpretation that can be drawn, of these data compared to other incident collations. For example:
- JRC Monthly Food Fraud Summaries (which underpin the infographics produced monthly by FAN member Bruno Sechet) - these are unverified media reports, rather than official reports, but hugely valuable in giving an idea of which way the fraud winds are blowing
- Official reports (as collated from commercial databases such as Fera Horizonscan or Merieux Safety Hud, which underpin FAN's annual Most Adulterated Foods aggregation) - these are fewer in number and give a much more conservative estimate of fraud incidence, and may miss some aspects which have not been officially reported
- Verified reports (where the root cause has been scrutinised and interpreted by a human analyst, for example the FoodChainID commercial database) - these are also few in number, less suitable for drawing overall trends, but give specific insight and information.
If looking at trends over time, you must also be wary of step-changes due to the introduction of new data sources. For example, Turkey's public "name-and-shame" database of foods subject to local authority sanctions went online in January 2025 and has resulted in an apparant increase in incident reports from Turkey.
