Expected credit loss impairment: early recognition vs. income volatility

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A new accounting principle, the so-called International Financial Reporting Standard (IFRS) 9, requires banks**to recognize expected credit losses in a forward-looking way. One way of implementing IFRS 9 is based on**leveraging models used in the context of managing regulatory capital. This way applies particularly to CWB**Financial Group, which is currently transitioning its approach of managing regulatory capital. However, IFRS 9**asks for different treatments of loans depending on whether or not their credit risk has significantly increased**since initial recognition. Therefore, the implementation of IFRS 9 needs a definition and measuring of what**constitutes a significant increase in credit risk. Finding a suitable statistical way to identify loans with**significantly increased credit risk is the topic of this proposed project. While credit risk should be recognized**early, defining a significant increase too widely leads to income volatility and too high estimations of credit**risk. Using methods from applied statistics and time series analysis, the goal of this project is to find a suitable**classification that takes the trade-off between early recognition of credit risk and income volatility into**consideration.