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Access to data and data processing, including the use of machine learningtechniques, has become significantly easier and cheaper in recent years.Nevertheless, solutions that can be widely adopted by regulators for marketmonitoring and inspection targeting in a data-driven way have not beenfrequently discussed by the scientific community. This article discusses theneed and the difficulties for the development of such solutions, presents aneffective method to address regulation planning, and illustrates its use toaccount for the most important and common subject for the majority ofregulators: the consumer. This article hopes to contribute to increase theawareness of the regulatory community to the need for data processing methodsthat are objective, impartial, transparent, explainable, simple to implementand with low computational cost, aiming to the implementation of risk-basedregulation in the world.

Risk-based regulation for all: The need and a method for a wide adoption solution for data-driven inspection targeting