System analysis of genre-event typology of financial information without prior training

Abstract

System analysis of genre-event typology of financial information without prior training

Musin I.R.

Incoming article date: 17.10.2025

A comprehensive method of system analysis and processing of financial information is proposed without prior training in five complementary taxonomies (genre, type of event, tonality, level of influence, temporality) with simultaneous extraction of entities. The method is based on an ensemble of three specialized instructions for a local artificial intelligence model with an adapted majority voting algorithm and a two-level mechanism for explicable failures. The protocol was validated by comparative testing of 14 local models on 100 expertly marked units of information, while the model achieved 90% processing accuracy. The system implements the principles of self-consistency and selective classification, is reproduced on standard equipment and does not require training on labeled data.

Keywords: organizational management, software projects, intelligent decision support system, ontological approach, artificial intelligence