Jacob Grotta, Managing Director at Moody’s Analytics explains,
“You can’t rely solely on well-respected models anymore. You need to understand why that model is applicable for your use, its relevance against other models, how it was built, and its pros and cons. Transparency in the modeling process is critically important.”
Model Risk Management (MRM) is a framework that combines sound governance principles with end-to-end documentation in the design, development, validation and deployment of new models in the business. It is an essential part of the model development process, particularly in financial and life sciences institutions where the cost of failure in meeting regulatory standards is severe.
An additional benefit of good model risk management practices is that it supports the development of reproducible results and reusable models through ensuring that all development is version controlled with documentation standards that provide certainty on how and why models were developed. This is important in ensuring that models remain accurate, appropriate and viable throughout their entire life cycle.
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451 Research Report - Domino Data Adds Model Management Framework to Data Science Platform