Evaluation Metrics and Method for Planned Regulatory Inspection Targeting

Access to data and data processing, including the use of machine learning techniques, has become significantly easier and cheaper in recent years. Nevertheless, the same criticisms made to the process of regulatory inspection targeting until the early 2010s remain to this day. This article discusses...

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Bibliographic Details
Published in:IEEE access 2024, Vol.12, p.19911-19923
Main Authors: Ribas, Celso H. H., Bermudez, Jose C. M.
Format: Article
Language:English
Subjects:
Applied signal processing
consumer policy
Data processing
Flow theory
graph signal processing
Inspection
inspection planning
inspection targeting
Machine learning
Measurement
Monitoring
Regulation
Regulators
regulatory inspection
Signal processing
Telecommunications
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Summary:Access to data and data processing, including the use of machine learning techniques, has become significantly easier and cheaper in recent years. Nevertheless, the same criticisms made to the process of regulatory inspection targeting until the early 2010s remain to this day. This article discusses important aspects concerning regulatory inspection targeting. Inspired by the Service Quality Theory and by the Central Flow Theory, this work proposes a novel parameter for ranking the performances of inspectable entities and shows how to calculate it using a graph signal processing framework. The new approach leads to the proposition of novel evaluation metrics and to a risk-based method for planned regulatory inspection targeting. Statistical simulations illustrate the application of the proposed method to the telecommunications domain. The obtained results evidence a superior performance of the proposed method when compared to other methods, and its potential to be widely adopted by regulators across policy domains and national contexts.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2024.3361395