Forensic Classification of Criminal Offenses in the Field of State Financing of Budget Programs

Abstract

The article explores the theoretical and applied foundations of the forensic classification of criminal offenses in the field of state financing of budget programs. In the context of full-scale armed aggression against Ukraine, the maximum concentration and rational use of state resources have become critical for ensuring the country’s defense capabilities. During this period, unlawful encroachments on budget funds acquire signs of particular public danger, destabilizing the financial system and posing threats to national security. Analysis of official statistics indicates an upward trend in the number of offenses within the sphere of state administration and defense; however, the effectiveness of their investigation requires improvement through the intensification of scientific research in the field of forensic methodology. The research results allow for the conclusion that the traditional division of crimes by the generic object, inherent in the doctrine of criminal law, is of secondary importance for forensic methodology. Instead, the foundation for developing effective investigative algorithms is forensic classification, which serves as a methodological framework for the systematization of specific investigative techniques. The author identifies and details key classification criteria: the mode (technology) of commission, the characteristics of the subject (the perpetrator), and the circumstances (context) of the offense. Particular attention is paid to the intellectual nature of the methods of committing crimes in the sphere of state financing of budget programs, which manifest in complex, multi-episode schemes involving manipulations of tender documentation and digital data. It is proven that the specificity of budget program implementation lies in continuous documentary recording, which transforms approaches to evidence handling: the key information carriers become not only paper documents but also digital footprints.