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Support for vigilance to prevent fraudulent practices in contribution compliance
The enormous amount of data a public agency manages offers a challenge of setting up an active, preventive approach to fraud and irregularities detection. We need to overcome the limit of traditional approach and procedures used for investigation so far. The new intelligence is a possible answer.
Support for vigilance to prevent fraudulent practices in contribution compliance

The recent experience at the National Employment Accident Insurance Institute (Istituto Nazionale per l'Assicurazione contro gli Infortuni sul Lavoro (INAIL)) is to seek irregularities and frauds related to the same economic entity that closes one business and reopens it with a different shape (company name, attributes, employees, etc.). This frequent behavior of entrepreneurs contributes to fraud and other irregularities.

Leaving behind the traditional reactive model of investigation and intelligence, INAIL is now looking ahead by making use of a proactive and preventive model, leveraging the specific relationship resolution analysis technology adopted, which allows INAIL to obtain high added value information for investigations. This more dynamic approach enhanced INAIL’s capacity to fight against both, fraud with regard to contribution collection and other irregularities. A preventive outcome is also forecasted, as entrepreneurs are supposed to change this fraudulent behavior once INAIL has achieved good results from its actions, and as a result, hopefully return to regularity.


Full text:
2Italy-INAIL3.pdf 104,38 kB

Publication year: 2010
Implementation year: 2009
Темы: Compliance and contribution collection
Organization: National Employment Accident Insurance Institute
Страна: Italy

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