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Nowadays, many businesses are resorting to data mining techniques on their data, to save costs and time, as well as to understand customers’ needs. Analysing such data can leader to higher profits and higher customer satisfaction. This paper presents a data mining study that is applied on millions of transactional records collected for a number of years, by a leading virtual credit card company based in Malta. In this study, 2 machine learning techniques, namely Artificial Neural Networks (ANN) and Gradient Boosting (GBM), are analysed to identify the best modelling framework that predicts the churning behaviour of this company’s customers. Apart from helping the marketing department of this firm by providing a model that predicts churning customers, we contribute to literature by identifying the minimum amount of customer activity needed to predict churn. In addition, we also analyse the “cold start” problem by performing a time-series experiment based on the few data available at the beginning of the customer purchase history., peer-reviewed

Once information is stored on the Blockchain, it cannot be altered retroactively. This immutability makes Blockchain technology an ideal candidate to secure learning achievements and educational credentials. Keeping data trustworthy, secure and manipulation-proof has become an increasing issue in education due to the rise of digital learning environments, which often combine learning experiences, testing procedures and educational credential management. Currently, most digital learning environments safeguard their data using traditional safety systems (e.g. password protection), which in turn are not Blockchain-based, but controlled by a centralized authority. While these centralized systems provide a certain level of security against unauthorized access from outside the system, manipulation from within the system cannot be excluded. Users with high enough access rights (teachers, administrators, system managers) can still add, change or delete entries. This becomes an even greater problem when learning achievements are to be reflected in fair and transparent credit systems, and especially when these educational credits are to be valid across different institutions or even countries. Due to their ability to store data in a decentralized, transparent and manipulation-proof way, Blockchain-based technologies can provide solutions to this problem. The aim of this paper is to describe the status quo of Blockchain technologies in the educational sector, including the expected merits and drawbacks., peer-reviewed