Credit risk management in banks and insurance companies

Abstract

This thesis aims to analyse the ways in which credit risk is managed and modelled in banks and insurance companies. The structure of this research is divided into four chapters. The first part aims to introduce the main features and parameters for the credit risk analysis, such as the probability of default of bond issuers and their joint correlation, the Loss Given Default (LGD), the Exposure at Default (EAD) and the computation of the main quantities of interest for the determination of the capital requirements, with a particular focus on how banks and insurance companies must comply with their respective EU regulatory frameworks, i.e. Basel III for banks and Solvency II for insurers. In Chapter 2, different approaches to model default correlation and the most widespread used models for credit risk management are discussed and compared. Particular emphasis is given to the CreditMetrics, KMV, CreditPortfolioView and CreditRisk+ models, of which this thesis provides an extensive explanation of their basic versions. The third chapter proposes an in-depth comparison of the features that make insurance companies differ from banks, with a specific focus on the insurance industry and the compliance with Solvency II. The last part of this paper encompasses a case study based on the development and application of a credit risk management model using Matlab programming software.