Expected credit loss is a probability-weighted estimate of credit losses during the expected life of a financial instrument. The estimation method requires point-in-time (PIT) projections of probability of default (PD), loss given default (LGD), and exposures at default (EAD).

Most credit instruments have a quantifiable risk of default. Accounting for credit risk in the entire portfolio of instruments must consider the likelihood of future impairment and is commonly measured through expected loss and lifetime expected credit loss. To comply with IFRS 9 or CECL, risk managers need to calculate the expected credit loss on the portfolio of financial instruments over the lifetime of the portfolio. Credit and regulatory risk teams quantify the expected loss using:

• Asset classification, through statistical and machine learning methods
• Macroeconomic modeling
• Scenario generation and scenario analysis
• Instrument pricing and risk sensitivity
• Stochastic modeling of default and recovery
• Automated reporting, reflecting point-in-time model and data selection

For more information, see Statistics and Machine Learning Toolbox™, Financial Toolbox™, Financial Instruments Toolbox™, Risk Management Toolbox™, and MATLAB Report Generator™.