The transformation of credit scores into probabilities of default plays an important role in credit risk estimation. The linear logistic regression has developed into a standard calibration approach in the banking sector. With the advent of machine learning techniques in the discriminatory phase...

We apply machine-learning techniques to construct nonlinear nonparametric forecasting models of consumer credit risk. By combining customer transactions and credit bureau data from January 2005 to April 2009 for a sample of a major commercial bank's customers, we are able to construct...

This paper proposes a framework for deriving early-warning models with optimal out-of-sample forecasting properties and applies it to predicting distress in European banks. The main contributions of the paper are threefold. First, the paper introduces a conceptual framework to guide the process...

This paper proposes a framework for deriving early-warning models with optimal out-of-sample forecasting properties and applies it to predicting distress in European banks. The main contributions of the paper are threefold. First, the paper introduces a conceptual framework to guide the process...

The global crisis of 2008 caused both liquidity shortage and increasing insolvency in the banking system. The study focuses on credit default contagion in the Central and Eastern European (CEE) region, which originated in bank runs generated by non-performing loans granted to non-financial...

This paper presents a novel approach to investigate and model the network of euro area banks' large exposures within the global banking system. Drawing on a unique dataset, the paper documents the degree of interconnectedness and systemic risk of the euro area banking system based on bilateral...

The transformation of credit scores into probabilities of default plays an important role in credit risk estimation. The linear logistic regression has developed into a standard calibration approach in the banking sector. With the advent of machine learning techniques in the discriminatory phase...

We develop quantitative methods to support financial product analysis-redesign required by the Carbon Equivalence Principle (CEP) to achieve financial net-zero and thus carbon net-negative positions. We then apply the CEP analysis-redesign to project finance for power generation across a range...

In this paper, we study systemic non-financial corporate sector distress using firm-level probabilities of default (PD), covering 55 economies, and spanning the last three decades. Systemic corporate distress is identified by elevated PDs across a large portion of the firms in an economy. A...

Banks representing 40% of global banking assets are members of the Net-Zero Banking Alliance (NZBA) who commit to net-zero carbon in their portfolio impacts by roughly 2050. Here we present methods for steering their derivative portfolios based on the mitigation cost (benefit) of CO2-equivalent...