DIRECTIONS FOR INNOVATIVE ANALYTICAL AND STATISTICAL TECHNOLOGIES IMPLEMENTATION AS A TOOL FOR CORRUPTION COUNTERACTION IN THE STATE

Abstract

The article is dedicated to the problem of implementing innovative analytical and statistical technologies as a tool to counteract corruption in the state. Innovative analytical and statistical technologies are broadly defined as a set of methods and tools based on the use of mathematical and statistical methods of data analysis to detect useful dependencies and regularities in data, improve decision-making efficiency, and detect anomalies in various fields of activity. More narrowly, they are defined as the process of using the most advanced data analysis methods to detect complex dependencies and useful regularities in data. Based on the content analysis of thematic publications, 4 directions were identified: 1) the direction of developing methodological tools; 2) the direction of analyzing secondary sociological data; 3) the direction of creating automated systems for natural language analysis and visualization of spatial data; 4) the direction of implementing machine learning and artificial intelligence technologies for identifying subjects of corruption relations and/or obtaining statistically substantiated confirmations of the presence/absence of corruption. It is determined that the most significant direction is practice-oriented studies, where testing of the relevant theoretical models and methodological tools takes place, and precedents are created for the use of the results of analytical and statistical studies as part of the evidence base of fraud or corruption. It is determined that a direct example of applying innovative analytical and statistical technologies as a tool for corruption counteraction from a political science perspective is electoral forensics. Within electoral forensics, two groups of methods are distinguished. The first group originates from the theory of numbers and refers to the frequency characteristics of numerical data of electoral statistics. The second group of methods relies on the search for anomalies in the relationships between different parameters of the electoral process, for example, turnout level and winning candidate support level. The main criterion used to detect electoral corruption is the discrepancy between the real (documented) election results and the normative (model) ones.