We propose an approach to calibrate the conditional value-at-risk (CoVaR) of financial institutions based on neural network quantile regression. Building on the estimation results we model systemic risk spillover effects across banks by considering the marginal effects of the quantile regression...

A daily systemic risk measure is proposed accounting for links and mutual dependencies between financial institutions utilising tail event information. FRM (Financial Risk Meter) is based on Lasso quantile regression designed to capture tail event co-movements. The FRM focus lies on...

The importance of startups for a dynamic, innovative and competitive economy has already been acknowledged in the scientific and business literature. The highly uncertain and volatile nature of the startup ecosystem makes the evaluation of startup success through analysis and interpretation of...

The paper examines the potential of deep learning to produce decision support models from structured, tabular data. Considering the context of financial risk management, we develop a deep learning model for predicting whether individual spread traders are likely to secure profits from future...

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 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...

The paper estimates banks’ total factor efficiency (TFE) as well as TFE of each production factor by incorporating banks’ overall risk endogenously into bank’s production process as undesirable by-product in a Global-SMB Model. Our results show that, compared with a model incorporated with...

With growing economic globalization, the modern service sector is in great need of business intelligence for data analytics and computational statistics. The joint application of big data analytics, computational statistics and business intelligence has great potential to make the engineering of...

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...

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...