- Antonio Simeone
- Jan 22
- 1 min read
Updated: Jan 26
The theoretical and methodological framework underlying the Econometric Accelerator has been published in January 2026 in Milano Finanza (https://www.milanofinanza.it/news/dall-econometria-all-e-conometria-ecco-come-l-intelligenza-artificiale-e-la-matematica-non-lineare-cambiano-202601100950166126 or download here the PDF
one of Italy’s leading financial newspapers, which highlighted the project’s contribution to the evolution of econometrics through the integration of artificial intelligence and complex systems science.
To date, the banking and financial sector has primarily adopted artificial intelligence for defensive and operational applications, such as credit assessment, fraud prevention, and compliance-related processes. By contrast, the application of AI to advanced predictive systems remains largely underexploited, despite being the area where the most significant economic, informational, and strategic benefits can be achieved.
The Econometric Accelerator was conceived to address this gap by redefining economic forecasting as a dynamic, multi-model, and continuously evolving process, capable of integrating structured data, alternative indicators, and qualitative signals with high informational velocity. In doing so, the project moves beyond a static and purely defensive view of risk analysis, toward a new generation of decision-support systems designed to operate in environments characterized by structural uncertainty, rapid regime shifts, and complex interdependencies.
