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One of the main goals of MRM is to ensure that models are **accurate and reliable**. This involves a rigorous process of testing and validation to verify that models are producing accurate results and are not subject to significant errors or biases. To achieve this, it's essential to use high-quality data, to choose appropriate modeling techniques, and to carefully evaluate the model's performance. Another goal of MRM is to **mitigate potential risks**. This involves identifying and assessing potential risks associated with the use of the model and developing strategies to minimize those risks. This could include implementing controls to prevent data breaches, creating backup plans to deal with unexpected events, or developing procedures to correct errors. Finally, MRM helps to **comply with regulations**. Many regulations require organizations to properly manage the risks associated with the use of models. MRM helps to ensure that the organization is meeting its regulatory obligations. This involves understanding the applicable regulations, implementing the necessary controls, and documenting all the activities to demonstrate compliance.
