Credit rating agencies’ (CRA) increasingly important role in financial markets and the real economyhas resulted in new regulatory requirements with respect to backtesting of their credit rating models.The European Union and the European Securities and Market Authority (ESMA) have developed acomprehensive set of statutory laws, including three basic attributes of a rating system that need to beregularly monitored by credit rating agencies operating in the EU: Descriptiveness, calibration qualityand historical robustness. ESMA requires that CRAs establish internal review functions responsiblefor validating the credit rating process. This paper provides a set of methodologies and statistical tools,which when properly implemented enables a credit rating agency to become compliant with ESMA’srequirements from a quantitative validation perspective. The methodologies and statistical tools areimplemented on two case studies which use credit rating data gathered from a Nordic CRA (NCR)and a Norwegian savings and loan bank. The credit rating model employed by the bank displayedboth descriptiveness, satisfactory calibration quality and good historical robustness. The NCR datawere insufficient to draw any conclusions with regard to the credit rating process.