Futurescape

From the integration of historical data and knowledge, we identify intelligent predictors synthesized by ML to delineate future economic scenarios and to track and analyze significant trajectories over time.

Vai
SYRTO
Predict, Cluster, Analyze.

In 2013 a team of researchers from the universities of Brescia, Venice, Amsterdam, Paris and Athens is selected and funded by the European Union under the 7th Framework Program to carry out a three-year project to inspect systemic risks in Europe after 2007 and 2010 crises. This is how SYRTO was born. Six years later, it became a university spin-off. In 2021, HI brought to the project its formalized company building methodology and its HIKU software, with the aim of continuing the research and implementing a predictive software tool on economic trends. 

The product

SYRTO is a software that identifies intelligent predictors synthesized by ML on the basis of company balance sheet data. It is addressed to enterprises, to validate budgets and test the resilience of the value chain; to banks, to analyze the trajectory of companies over time and measure credit risk; to investment funds, to evaluate intervention strategies. SYRTO is applicable to a wide range of domains, but at this stage it focuses mainly on manufacturing, a fundamental pillar of Italian entrepreneurship.  

How it works

SYRTO’s identification of significant indicators is applied to the prediction of a company’s budget data in the future, to the identification and aggregation of the business model of the companies on the market, and to the evaluation of the company’s performance compared to its competitors.

These actions are implemented with the help of ML in three modules. A predictive ML engine takes into account multi-level data and information by generating a vector of indicators that can be trained to be meaningful over time, and have a high predictive capability. A dimensional reduction ML engine is able to identify the trajectories of companies by operating a transformation of balance sheet data and predictors, implementing a valid tool for analyzing the company in relation to the market. Finally, the ML Analytics module allows you to find similarities in company performance over time.