The main objective of the FINCRIME project is to present on the basis of algorithms a real-time analysis of as many components of economic and financial crime as possible and to predict the evolution of the risks induced by them at international level, with a focus on European Union member countries.
The central pillar is the Artificial Intelligence structure developed in order to determine the causes and effects of direct and indirect risks for sectors of activity included in the list of critical infrastructures, as they are defined and classified according to the legislation.
The results are offered in the form agreed to the institutions with responsibilities in the field, to the project partners and to the general public.
The Machine Learning Platform
The modules will be able to perform an analysis to determine the most influential factors, determinants, of economic and financial crimes.
There may be underlying relationships between micro-crime and macro-crime, which are difficult to observe without the application of specific indices, such as the Gini index and the gaining of information. In order to obtain the lowest possible degree of deviation, the mechanisms are entrained in the test environment, using the same data sets for different batches.
If the returned test error proves to be mathematically satisfactory, the system can be exploited in the production environment, in a basic web platform.