Banks generally use credit scoring models to assess the creditworthiness of customers when they apply for loans or credit. These models perform significantly worse when used on potential new customers than existing customers, due to the lack of financial behavioral data for new bank customers....

Unemployment rates provide information on the economic development of countries. Unemployment is not only an economic problem but also a social one. As such, unemployment rates are important for governments and policy makers. Therefore, researchers around the world are constantly developing new...

In dem vorliegenden Beitrag wurde ein auf Künstliche Intelligenz gestütztes Kon- zept zur Bewertung und Optimierung der Transportplanungsqualität für die Stahl- und Metalllogistik ausgearbeitet und seine Praktikabilität mithilfe methodischer Untersuchungen nachgewiesen. Somit soll die...

Deception and media manipulation have always been an integral part of wartime propaganda. But never before has it been so easy to create high-quality fabrications of images as well as sound and video recordings. The tendency to react emotionally to these media opens up a whole new possibility...

Täuschung und Medienmanipulation sind seit jeher fester Bestandteil der Kriegskommunikation. Nie zuvor aber war es derart einfach, qualitativ hochwertige Fäl­schungen von Ton-, Bild- und Videoaufzeichnungen zu erstellen. Die menschliche Neigung, emotional auf diese Medien zu reagieren,...

Technological change co‐determines agri‐environmental performance and farm structural transformation. Meaningful impact assessment of related policies can be derived from farm‐level models that are rich in technology details and environmental indicators, integrated with agent‐based...

Accurate, real-time measurements of price index changes using electronic records are essential for tracking inflation and productivity in today's economic environment. We develop empirical hedonic models that can process large amounts of unstructured product data (text, images, prices,...

In this paper we intend to substantiate the usefulness of Deep Learning, especially feedforward neuronal networks, in the prediction of business failure. This methodology provides very good results in terms of predictive performance when large sample sizes are available. Therefore, we have...

We propose how deep neural networks can be used to calibrate the parameters of Stochastic-Volatility Jump-Diffusion (SVJD) models to historical asset return time series. 1-Dimensional Convolutional Neural Networks (1D-CNN) are used for that purpose. The accuracy of the deep learning approach is...

Deep learning-based predictive quality enables manufacturing companies to make data-driven predictions of the quality of a produced product based on process data. A central challenge is that production processes are subject to continuous changes such as the manufacturing of new products, with...