Intelligenza artificiale

QBT develops algorithms and calculation software in the fields of Fintech, Proptech and Legaltech.
This experience has increased our know-how, consolidating our ability to develop management software that we custom-design, in order to always propose the best technological solution to the customer's specific needs.
Through painstaking research and development, we have also explored new areas, becoming a benchmark in the field of Artificial Intelligence, and in particular in Natural Language Processing and machine learning.
All our research activities proceed in close collaboration with universities and research centres, which form the natural network of QBT's expertise.


Over the years we have gained a strong experience in the development of algorithms and software in the sector financial (Fintech) and in particular in the sector of non- performing loans of both a mortgage and unsecured nature, risk analysis, valuation of asset real estate (Proptech)is in the field legal (Legaltech).

We have approached the development of our products both through techniques traditional and through the experimentation of new research areas in particular through the use of behavioral models and agent simulation models.

QBT manufactures, on behalf of its customers, products and services white-label or in house, investing in the projects we believe in, which arise from research and development.

NPE Service e Webservice

Fintech: NPE Service e Webservice

QBT has developed a method of valuing and forecasting the cash flows deriving from the credit recovery activity in dispute of nature Secure is Unsecured for UTP and NPL credits: the valuation process takes into account the type of credit, ie guaranteed and unsecured, and generates a forecast of the recoveries of the relative timing.

The algorithm is based on a complex mix of technologies:

  • purely algorithmic calculation
  • statistic analysis
  • agent simulation
  • complexity analysis


We are able to offer our customers different solutions based on different needs and the quality and

quantity of available data.

The inputs of the algorithm can come from data entry activities on management software specially developed and tailored to the needs of the Customer or from massive traces extracted from the Customer's systems.

The results can be produced in a raw format for further processing in the form of sheets excel or aggregated and reinterpreted with tool business intelligence.