More and more companies, including start-ups, need to know, with as much detail as possible, how their business is performing based on actual information at a given point in time and project possible growth trends, see how they compare with what they believe to be their main competitors, and better understand market positioning and opportunities. These aspects are increasingly critical, especially in view of a period in which it will be more and more difficult to collect money from investors who will increasingly look not only at companies’ ability to break even, but above all at their real growth potential.
From this idea, Syrto was born, which is the evolution of an international academic research project called Systemic Risk Tomography and funded by the European Union with a call for proposals worth a total of €2.47 million, aimed at visually representing the level of systemic risk. In 2019, Syrto Srl was born from that project, as a spinoff of the University of Brescia, under the leadership of Roberto Savona. Syrto works to transform academic results into a practical and innovative business idea: to make balance sheet data simple and visual. Syrto shows the evolution of companies, enriching them with the forecast for their future, within its Radar, which becomes the tool for communicating financial knowledge. At the helm of this transformation from research to software product sits Massimo Fariello, CEO of Syrto and previously chief of R&D and chief strategy officer of Altair Engineering, an American company listed on the Nasdaq in 2017.
Syrto, also making use of artificial intelligence, aims to revolutionise the field of financial analysis, making it accessible and understandable thanks to advanced technologies such as neural networks, machine learning and knowledge graphs. This tool makes it possible to predict the future performance of companies for up to three years, compare them with competitors, visualise their health, and analyse suppliers and the market. The platform not only speeds up market analysis but also facilitates lead generation and the assessment of risk and excellence of companies. Syrto is distinguished by its visual approach, which makes economic and financial information easy to understand even for those without specific financial expertise. The intuitive user experience simplifies workflows and, thanks to a competitive price, makes financial analysis affordable for all companies, improving their efficiency and business management. The solution is provided in Saas mode and costs between EUR 2250 and EUR 4500 depending on the version.
Syrto’s core team (pictured) of 15 people reflects the company’s innovative approach not only in technology but also in organisational management. “We have chosen a horizontal organisational model, where each team member, regardless of their function, has goals related to business success rather than to their own department,” says Fariello.
Syrto aims for significant growth in the coming years, with the goal of reaching 200 customers by the end of 2025 and break-even by 2026. To support this ambitious development plan, the company plans to recruit new talent through a talent pool in cooperation with the Politecnico di Torino, the University of Brescia and the University of Cagliari. Validation of the product on the market is progressing with the acquisition of 40 paying customers between June and November, including Banca Sella, Banca Valsabbina, Gruppo Cherubini, BTL, BCC Agrobresciano, Siderweb, and Equiter. In July, a capital increase of EUR 580,000 was deposited, with Zest among the investors, which is now fuelling development in view of the next investment round, which will be around two million euros.
The interest of banks
It is precisely banking institutions that are proving to be ideal customers and definitely interested in Syrto’s potential because the tool allows them to optimise the financial analysis of Italian companies in order to reduce the evaluation time in both the credit granting and monitoring phases. Banks can count on a platform that integrates balance sheet data with the aim of identifying and assessing the actual operations and health of companies, significantly reducing time and uncertainty in the evaluation process.
“Banks need advanced tools to analyse companies quickly and thoroughly; Syrto is designed for this purpose,” explains Savona, chairman of Syrto and full professor of Economics of Financial Intermediaries at the University of Brescia. “Our software offers banks a tool for analysing individual companies and sectors, carrying out comparisons with market competitors to better identify and interpret the dynamics assumed by companies.
Syrto enables banks to analyse the temporal evolution of each company’s economic-financial indicators in a matter of seconds, allowing a dynamic and detailed evaluation of the customer portfolio. Thanks to machine learning, the platform provides forecasts on the future performance of companies for up to three years, improving the effectiveness of financing decisions. This innovative approach makes it possible to observe not only individual company data, but also market trends on a national and regional level, providing a detailed view of growing sectors and emerging opportunities.
For banks, managing and analysing large amounts of company data is a complex challenge. Syrto makes this process faster by optimising the analysis of company balance sheets. Banks have access to a system that determines traditional and advanced metrics elaborated thanks to the research activities capitalised by the European project and now readapted and innovated thanks to a team involving several Italian universities (University of Cagliari, Bocconi, Bologna, Brescia, Turin), which allows them to accurately assess companies that are already customers or in the process of being investigated, or potential customers. “With Syrto, banks obtain a summary view of the direction taken by companies towards areas that may be of risk or value creation, identifying the explanatory factors and the correlative levers of action,” adds Savona. “In the context of credit granting and monitoring procedures, the evaluation and pre-assessment processes of companies are automated. As part of the analysis of potential customers, companies can be visually identified through a series of indicators referring to intrinsic value, risk characteristics, ability to generate operating margins, and company size’.
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