A Stochastic Model of the Repressive-Preventive Impact on Crime: from Intuition to Calculations

Abstract

The authors analyze the use of new digital technologies for automated collection, analysis and assessment of large volumes of data on crime, its key factors and the effects of crime countraction efforts with the goal of a gradual transition from the intuitive method of crime counteraction to the calculations-based one. The hypothesis of the study is that a continuous multi-source monitoring of quantitative crime indices, factors and the effects of crime counteraction efforts will make it possible not only to optimize budgetary expenditure on fighting crime, but also to find effective solutions for other practical problems of crime counteraction efforts (specifically, problems of evaluating and compensating the inflicted damage, problems of reducing the number of ungrounded changes in criminal, criminal procedure and penitentiary legislation). A specific modern feature of the state policy of combating crime is that digital technologies make it possible to develop and implement a stochastic model of repressive-preventive impact on crime with the use of criminal law, criminal procedure and penitentiary measures. It is suggested that the use of the stochastic model of repressive-preventive impact on crime should be viewed as a necessary condition for the development and adoption of national and regional programs of crime counteraction financed by the federal and regional budgets. The authors believe that the introduction of the stochastic model of the repressive-preventive impact in the practice of crime counteraction should be conducted in several stages. At the first stage, the federal law and the Act of the RF Government shoud determine the conditions of a mid-term experiment on the territories of some subjects of the Russian Federation, which will ensure a continuous monitoring, including the collection, processing and analysis of statistical data, results of population and experts’ surveys on the condition and dynamics of grave and especially grave crime, its factors and the effects of state efforts to counteract such crimes. At the final stage of the introduction of a stochastic model of the repressive-preventive impact on crime in the practice of state governance, the authors suggest creating an automated federal system of multi-source monitoring of indexed crimes (these are the crimes most «sensitive» for achieving the goals of national security and ensuring public order, which require non-stop monitoring), their key factors and the results of counteracting them. Key expected results from the introduction of this stochastic model and a continuous mlti-source monitoring into the practice of crime counteraction should be the optimization of budgetary expenses on criminal prosecution, the reduction of the number of inmates, the reduction of the number of changes introduced into the Criminal, Criminal Procedure and Penitentiary Codes of the Russian Federation.