Preventive monitoring of all taxpayers in order to detect tax evasion trends in time, but also to prevent the non-accumulation of unpaid debts to the public, the new project of AADE, which will be based on artificial intelligence, foresees.
The Tax Authority puts the plan for the assignment to consultation Advanced Business Intelligence System Supply Contract (BI) and data analysis (Data Analytics).
According to the announcement, the project to be implemented within the framework of the National Recovery and Resilience Plan "Greece 2.0", concerns the supply of an analysis and data mining system for statistical and quantitative analysis, footnotes, etc., which will lead to the better exploitation of AADE data.
It's a artificial intelligence and machine learning system which will include techniques with which data will be processed and extreatment information from large data sets in order to make predictions about future events.
First, historical data is used to build a mathematical model which captures important future trends.
The generated prediction model is then used on current data to make predictions what will happen in the future or to suggest actions that will achieve the best results Results.
Track all
The basics characteristics that will include the data analysis and mining system are the following:
- The diaconnection with the information systems of the control: Provision of data for the implementation of indirect technical controls and audit cross-verifications
- Data analysis for audit targeting purposes: Extraction and analysis of AADE data in conjunction with data from external sources (worldwide web, social networks, open data, etc.) for the most efficient update of risk analysis in the targeting and prioritization of controls, in agreement with and to achieve the goals of AADE's strategic and operational plan
- The timely detection of tax evasion incidents: Real-time detection of suspected tax evasion and smuggling incidents
- The discovery of dynamic relationships between taxpayers: As it has been proven by applications of other European countries, it is a very important step for the detection of fraud and tax evasion
- Taxpayer classification: Categorization of the expected behavior of taxpayers, e.g. strategic defaulter, possibility of tax evasion, etc.
- Taxpayer profiling: Finding non-obvious similarities between taxpayers as they emerge after demographic, economic and behavioral analysis of the entire population of taxpayers. It is used in risk assessment and other use cases
- Risk assessment and risk assessment: Assessment of taxpayers for non-payment risk.
- The forecast of income and debts: Forecast of income and debts in total and by taxpayer or by DOU, by geographic region, by profession, or any other dimension based on the historical data of the behavior of taxpayers.
Additional features of the new AADE system are:
- Flexibility in connectivity as it will have access to all data (structured, semi-structured, unstructured) of AADE as well as external sources with the aim of their pre-processing, integration, transformation and exploitation.
- The ability to generate statistical and interactive reports business intelligence for all data and information to business users.
- Real-time data processing in order to achieve real-time reporting, decision making and action based on them and immediate application updates.
