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Archimede

Archimede

Certified intelligence against frauds

Project

Archimede is the innovative prevention model, based on the continuous auditing and monitoring of processes through data-driven analysis and advanced algorithms.

IImplemented together with INAIL, Archimede brings applied AI to the prevention and fight against fraud in the Public Administration, by identifying anomalies and risks in advance on a national scale, making audit planning more targeted, with a direct impact on the use of public resources.

Archimede has established itself as a leading solution in the public administration sector, achieving full compliance with the international standard ISO 42001:2023 for the responsible adoption of AI. This achievement is complemented by a significant recognition: the project was awarded the prestigious ComoLake Award 2025, confirming its innovative value and tangible impact.

Opportunity

The adoption of strategies aimed at effectively identifying and combating errors, evasion, and fraud (EEF) is increasingly essential to ensure that those who pay insurance premiums respect the rules and to protect beneficiaries’ right to receive requested benefits, in accordance with the principles of fairness, transparency, and regulatory compliance.

To respond to this challenge, it was necessary to:

  • identify a new paradigm for preventing and combating fraud
  • adopt a proactive, centralized, and data-driven model
  • improve audit planning capabilities and optimize the use of public resources.

Solution

Almaviva has implemented an innovative prevention model, based on the continuous auditing and monitoring of processes through data-driven analysis and advanced algorithms. ​

Archimede AI platform automatically identifies anomalies and irregularities using risk indicators and advanced predictive models: an interoperable and standards-compliant approach that enhances the quality of controls and strengthens transparency, integrating continuous feedback from auditors to improve algorithms and processes.

Automated data analysis

and risk classification using machine learning techniques (rule-based engine, clustering based on supervised and predictive engines)

Reporting management system

for abnormal situation verification and handling by audit and supervisory functions

Investigation support platform

with advanced tools, including graph analysis, advanced detection criteria, interoperable solutions for evidence verification, and continuous refinement of algorithms

Other