We use BERT, an AI-based algorithm for language understanding, to decipher regulatory climate-risk disclosures and measure their impact on the credit default swap (CDS) market. Risk disclosures can either increase or decrease credit spreads, depending on whether disclosure reveals new risks or...

The severity of extreme weather events is increasing due to climate change, giving rise to physical climate risk. However, physical climate risk is not only driven by the severity of individual hazards, but also by the interdependence of those hazards. This paper establishes bounds for the...

We examine the quantification of operational risk for banks. We adopt a financial-economics approach and interpret operational risk management as a means of optimizing the profitability of an institution along its value chain. We start by defining operational risk and then propose a...

We introduce an adaptive importance sampling method for the loss distribution of credit portfolios based on the Robbins-Monro stochastic approximation procedure. After presenting the subtle construction of the algorithm, we apply our adaptive scheme for calculating the risk figures of a typical...

In this paper, we study the economic benets from using credit scoring models. We contribute to the literature by relating the discriminatory power of a credit scoring model to the optimal credit decision. Given the Receiver Operating Characteristic (ROC) curve of the credit scoring model, we...