Publications

Our Regulation Outlook delves into the evolving EU regulatory landscape, exploring the key uncertainties that are poised to influence decision-making processes, market dynamics, and strategic planning throughout the year.

Our focus in this paper is to develop decision making models using a range of advanced machine learning techniques. We explore three different methodologies to measure the discriminatory power between good and bad borrowers using a credit card portfolio dataset. The main hypothesis is that advanced modelling techniques lead to more efficient estimates and higher discriminatory power.

Grant Thornton has constructed a Physical Risk Quantification Framework in its effort to support financial institutions in identifying and measuring their Climate & Environmental (C&E) Risks. In this publication, we present our methodology, implementation, and key benefits of the framework.

Over the last few years the ECB have published a series of guidance and best practice publications in the Climate and Environmental (C&E) risk area. These publications and best industry practices indicate that while banks have made progress in incorporating climate-related risk, there is a high level of inconsistency in certain practices and also areas for improvement.

How Grant Thornton can help you to estimate scope emissions for companies that do not report these metrics and incorporate these into banks’ Climate & Risk Quantification framework.

How Grant Thornton can help you understand the challenges surrounding the implementation and validation of machine learning techniques in IRB models.