The importance of using risk-based approaches to plan and conduct regulatory inspections is well known. Indeed, risk-based inspections and enforcement measures are more efficient than randomly assigned checks and more realistic than “100% coverage” given limited resources. They also tend to be significantly more effective. Risk analysis helps regulators prioritise their activities so as to efficiently manage costs, time and as evidenced in the COVID-19 pandemic - health and safety. On the other hand risk assessment requires greater accuracy. A promising prospect is the use of data management systems as well as increased use of Artificial Intelligence and Machine Learning. This report evaluates the functioning of data-centric tools developed to assist Italian inspectorates plan their activities in regulatory areas such as operational safety and health, and food safety. It also reviews the challenges and potential difficulties in using such methods, and lays out next steps for future developments.
For further information, please contact Florentin Blanc, OECD Regulatory Policy Division.