On 27 September 2021, the OECD published the Data-Driven, Information-Enabled Regulatory Delivery report, prepared by the Directorate for Public Governance (GOV). The latter was authored by Florentin Blanc, Senior Policy Analyst, Margarita Escobar and Tiziano Lattisi, consultants.
The report is divided into the following chapters: 1) Data-driven approaches towards risk-based regulatory delivery, 2) Applying machine learning techniques to inspections, 3) The RUPC system and the RAC engine in the Autonomous Province of Trento, and 4) Lessons learnt.
Based on the work done by the OECD in Italy, the report looks over on how data analysis techniques and information management technologies may support more effective regulatory inspections by improving risk assessments, targeting, and coordination.
The first chapter highlights the need for regulatory delivery (supervision, inspections, enforcement) to be digitally enabled to increase its effectiveness and efficiency.
Indeed, it is stated as a Data-Driven Public Sector achieved through data governance, with data used to plan, deliver and evaluate activities, can help policymakers become more efficient and transparent.
The report highlights as «regulators seeking to incorporate risk-based approaches still encounter roadblocks in terms of insufficient data generally and inadequate data management tools specifically. While using some risk analysis is more efficient than no risk analysis at all, data-related roadblocks have made it more difficult to identify risk factors».
The project of the OECD, called Rating Audit Control, has the goal to make regulatory inspections more targeted and risk-based. Working in four regions, the work aims at improving inspection planning by making better use of existing data and systems and, where possible, improving these systems in terms of risk integration.
The second chapter focuses on the practical use of IT to improve inspections in Lombardy and Campania Regions. The report represents the work done for the GISA system in Campania, and the OHS in Lombardy. For example, amongst the other peculiarities described in the report, Campania is developing, with the support of the OECD, a self-certification tool. Indeed, the aim is to provide an audit tool for self-control through an electronic form of the checklist for dairy processing facilities. In Lombardy, for instance, the goal was to predict non-compliance through several factors, such as historical records, by using machine learning.
In the third chapter, the RUCP system and RAC engine developed in the Autonomous Province of Trento are represented. The report explains the use of scorecards on data-based risk analysis. The system architecture of the RAC engine is clearly defined: both the risk calculation process and the risk assessment and with examples and risk matrix models.
In the last part of the report, there is a representation of the critical challenges to the digital approach to regulatory delivery. For instance, issues related to data integration and the interval of update of risk classes. The report states as «legal and administrative hurdles also place hindrance on the development of IT tools», and «IT systems need to fillip the real goals of regulatory delivery – risk management and reduction, to ensure a meaningful protection of key elements of the public welfare – then just weeding out non-compliant actors».
The report concludes by mentioning the OECD toolkits and frameworks to be potentially used to solve the current concerns.
Luca Megale
is a PhD Student at LUMSA University of Rome
and tutor of the European Master in Law and Economics - EMLE (Rome term).