Optimizing Public Service Delivery through AI and ML Driven Predictive Analytics: A Case Study on Taxation, Unclaimed Property, and Vendor Services

Abstract

Pursuing the mission of the best government has been a key priority across countries and centuries. One of the main roles in addressing these ambitions has been ‘better regulation’. More recently, in a variety of countries and under different output schedules, including ‘better legislation’ and ‘better government’, the dimensions have been expanded. For instance, under better regulation, the first critical component (pre-approval) is related to the creation of laws and subordinate legislation, seeking to ensure their quality (better law making, BL). The second (post-approval), in turn, regards the application of laws and regulations in a way that their objectives are achieved without imposing burdens that are not justified, involving actions to remedy market failures, taking into account considerations of good governance and transparency, with a comprehensive approach concerning the legislative process, and in particular concerning ex ante and ex post evaluation activities, as emphasized in the IA guidelines, CBA guidelines, and those of WM. This is expected to provide the necessary information to identify the most efficient and effective policy options and to monitor compliance and impacts over time, or, more broadly, the ex ante assessment system (ExAS).