Our current solution is based on software developed by Professor Michele Modina, founder of 110 Laude, which has been subjected to continuous enrichments over time. The software is used, through a license agreement, by up to 1000 Italian MSMEs and networks of credit brokers.
110Laude’s research interests mainly concern the management of the investment and financing techniques focused on the relationship between banks and firms, particularly for MSMEs. In the light of the introduction of new assessment model credit, 110 Laude integrates existing credit risk predictive models with multiple hard and soft information through the use of machine and deep learning techniques.
With the aim of pursuing its goal of bringing innovative solutions in the fintech sector to the market 110Laude has developed strong in-house expertise in technology with a particular focus on cross-platform application development, API software, artificial intelligence models, and machine and deep learning techniques.
University of Molise, Department of Economy (www2.dipeconomia.unimol.it) The BIFE Laboratory - Bifelab (www.bifelab.it) FYNAID (www.fynaid.com)
ESRC Impact Acceleration Account, 2021. Project title: SME credit risk assessment: The role of market and accounting information. Rotary Club, 2021. Innovative start up award.
“Cooperative credit banks and sustainability: Towards a social credit scoring”, Zedda Stefano,
MODINA Michele, Gallucci Carmen (2024), Research in International Business and Finance, vol. 68
“Diagnosing default syndromes: early symptoms of entrepreneurial venture insolvency”, MODINA
Michele, Zedda Stefano (2023), Journal of Small Business and Enterprise Development, vol. 30, no. 1,
p. 186-209
“Predicting SMEs’ default risk: evidence from bank-firm relationship data”, MODINA Michele, Pietrovito
Filomena, Gallucci Carmen, Formisano Vincenzo (2023), Quarterly Review of Economics and Finance,
p. 254-268
“Trade credit and firm investments: empirical evidence from Italian cooperative banks”, Filomeni
Stefano, MODINA Michele, Tabacco Elena (2022), Review of Quantitative Finance and Accounting, 1-
43
“Financial ratios, corporate governance and bank-firm information: A Bayesian approach to predict
SMEs’ default”, Gallucci C., Santulli R., Modina M., Formisano V. (2022), Journal of Management and
Governance