Second-hand car markets contribute to billions of Euro turnover each year but hardly generate profit for used car dealers. The paper examines the potential of sophisticated data-driven pricing systems to enhance supplier-side decision making and escape the zero-profit-trap. Profit maximization...

Deep learning has substantially advanced the state-of-the-art in computer vision, natural language processing and other elds. The paper examines the potential of contemporary recurrent deep learning architectures for nancial time series forecasting. Considering the foreign exchange market as...

Customer scoring models are the core of scalable direct marketing. Uplift models provide an estimate of the incremental benefit from a treatment that is used for operational decision-making. Training and monitoring of uplift models require experimental data. However, the collection of data under...

The paper proposes an estimator to make inference of heterogeneous treatment effects sorted by impact groups (GATES) for non-randomised experiments. Observational studies are standard in policy evaluation from labour markets, educational surveys and other empirical studies. To control for a...

The shift of human communication to online platforms brings many benefits to society due to the ease of publication of opinions, sharing experience, getting immediate feedback and the opportunity to discuss the hottest topics. Besides that, it builds up a space for antisocial behavior such as...

This study provides a formal analysis of the customer targeting decision problem in settings where the cost for marketing action is stochastic and proposes a framework to efficiently estimate the decision variables for campaign profit optimization. Targeting a customer is profitable if the...

Deep learning has substantially advanced the state of the art in computer vision, natural language processing, and other fields. The paper examines the potential of deep learning for exchange rate forecasting. We systematically compare long short- term memory networks and gated recurrent units...

Financial statement fraud is an area of significant consternation for potential investors, auditing companies, and state regulators. Intelligent systems facilitate detecting financial statement fraud and assist the decision-making of relevant stakeholders. Previous research detected instances in...