Background: Accurate route planning is a core challenge in logistics, particularly for small- and medium-sized enterprises that lack access to costly geospatial tools. This study explores whether usable distance matrices and routing outputs can be generated solely from geographic coordinates...

With the use of technology-enhanced learning platforms and an abundance of available educational data, it is possible to analyze student learning behavior and solve problems, improve the learning environment, and make data-driven decisions. A virtual learning environment effectively provide...

In the rapidly evolving field of automotive finance, managing risk is crucial for maintaining financial stability and security. Machine Learning (ML) tools have demonstrated significant potential in enhancing the predictive capabilities of risk management models, enabling more accurate...

Detecting fraud is complex, requiring analysis of vast data over time, making it resource-intensive for human investigators. This chapter explores key forms of financial fraud, including those involving corporations, banks, and insurance sectors. It provides a thorough evaluation of various...

Machine learning has rapidly transformed various sectors, and the stock market is no exception. Traditionally dominated by human intuition and fundamental analysis, stock market forecasting has increasingly integrated sophisticated algorithms and data-driven for every scenario. In the stock...

Artificial Intelligence (AI) is rapidly transforming science by accelerating discovery, automating research tasks, and enabling new paradigms of investigation. The growing role of AI in science has placed it high on the European political agenda, including the commitment to establish an AI in...

Public engagement (PE) in research and innovation (R&I) is key for creating research processes that are inclusive, democratic and impactful. Across Europe, governments are promoting strategies to integrate PE into R&I governance, ensuring research aligns with citizen's needs. Consequently,...

Customer churn is a recurring problem in bank marketing, and there are several machine learning approaches that can help. This paper compares two of them: a Multilayer Perceptron (MLP) neural network and logistic regression. We used the UCI Bank Marketing dataset, which has 41,188 client records...

This is a slightly revised version of the purposely provocative keynote presented at the FDR library for the Levy Institute Summer Seminar on Money, Finance, and Public Policy. References have been added.