Implementing an anti-fraud and security system to detect anomalies that characterized international telephone traffic: this is the focus of the research and development project born from the collaboration between VueTel, a company specialized in international telecommunications in wholesale voice and data services, and the Department of Engineering of the University of Perugia.
What VueTel and the University of Perugia are carrying out through their collaboration is the possibility of producing tools for business intelligence based on Data Analysis and Machine Learning (machine learning), technologies at the basis of Big Data analysis for the creation of computer systems and advanced algorithms. In particular, with Data Analysis it is possible to extract data and create patterns that human analysis is not able to identify; Machine Learning is based on algorithms capable of classifying and finding anomalies in the data that they are able to learn from human behavior. It is a technology widely applied in the whole IT field and often overlaps with computational statistics, a discipline that has the purpose of dealing with the development of predictions through the use of a computer.
These tools are already used to intercept telephone fraud, including some that directly affect end users, who are able to empty the telephone account.
The technology that VueTel has developed is capable of detecting and blocking fraudulent attempts, thus guaranteeing a superior quality of service.
“Machine learning today is increasingly applied to the most diverse disciplines of industry and services and basically represents a set of methods that allow a machine to arrive at a specific behavior, without having been specifically programmed – underlines Emanuela Bevilacqua, CTO Voice of VueTel. It is an automatic learning closely linked to pattern recognition, which allows a machine to make a ‘decision’ autonomously, compared to a given analysis made on that pattern. ”
The level of results obtained is significant. VueTel continues to invest in this direction, incorporating know-how and extending this approach also in the commercial and finance sectors.