Model Risk Management
Over 90% of financial professionals agreed that model risk management is increasingly crucial in building a robust risk management culture.
The statistic above was from a poll conducted in a webinar – Model Risk Management, co-organised by Deloitte and IBFIM. With the vast increase number of models in banks internally, the importance for a robust model risk management has never been higher. Being unprepared to address model failures in a timely manner is worse than actual model failure.
During the webinar, our modeling specialists - Dr Chee Wei Yen and Yah Qi Wen discussed how the COVID-19 pandemic has caught many businesses off guard including the performance of the statistical models built on a wide range of purposes. As most of the models were built using data from a benign period of economy, these models were not able to handle the sudden disruption. This is especially true for predictive models that rely on macroeconomic movements and trends. Hence, the presence of volatility may result in extreme cases of model error with overestimation or underestimation of the actual experience.
With that said, what are the building blocks for a sound model risk management framework? Read our paper and learn more about the future of Model Risk Management that incorporates Machine Learning to the framework.