MRM Raptor
Why automate test interpretation?
Model use at large banks is growing by more than 20% each year, according to IDC. As financial institutions use more, highly-complex models to drive major decisions, they expose themselves to more model risk and mounting regulatory pressures.
From SR 11-7 to CP6/22, regulatory bodies are forcing model risk management (MRM) teams to improve model governance, actively prevent model misuse and deterioration, and address the potential negative consequences.
In response, MRM teams are not only revisiting their workforce strategies but also exploring new technologies and automation. However, most products in the market attempt to automate the entire MRM workflow, which requires heavy integrations with your data, algorithms, and environment.
Our experts built MRM Raptor to automate a common bottleneck - test interpretation and documentation - without interfering with your existing modeling environment.
Apply low-touch automation. We don’t interfere with your modeling processes, testing environment, or underlying datasets.
Accelerate and scale your model review capacity. Auto-interpret test results and generate documentation up to 40% faster with just a few clicks.
Standardize your reporting. Easily import your templates and taxonomy for uniform reporting.
Automate Test Result Interpretation
With frequent model reviews, quants spend long hours pouring over test results and collating insights. It's extremely repetitive and time-consuming, leaving their core skillsets underemployed. Our product automatically interprets test results. We set it up so you can continue to execute tests within your own environment and send relevant results to MRM Raptor via an API. This helps scale model review capacity, without upending established processes.
Auto-Generate Standardized Documentation
Manual documentation can be inconsistent and miss the mark on specific regulatory requirements. MRM Raptor automatically generates technical content to populate your templates. It's designed to be extremely configurable and agile, so you can easily update new templates, import your taxonomy, and generate standardized documentation. Once a report is produced, analysts can use our visual editor to collaborate on any final adjustments before sending it off to internal audit and regulators.
Get Guidance from MRM Experts
Beyond MRM Raptor, clients look to us for guidance on their broader automation strategies. Sometimes, the first step is process reengineering, and we have MRM teams who can enhance and scale your existing workstreams. Others are looking to implement and optimize automation technology. With decades of experience in MRM, our experts can guide you along your automation journey.
Industry Insight
Managing Financial Risk in Models
While data can certainly be used to keep financial organizations informed and reduce their exposure to risk, it is important to consider what sort of data is most useful and what is the most effective way of gathering and using it. Not all data or all data management systems are equal.
Related Resources
Optimize your outcomes.
RiskMinds Discussion Highlights: Implementing a Risk-Based Approach to Model Risk Management
The recent pandemic significantly stressed the model tiering approach presenting a clear to need for a model risk management system.
SR 21-8: Rationalizing Model Risk Management for BSA/AML Models and Systems
The recently issued interagency statement SR 21-8 is a non-binding guidance note with very useful and practical suggestions on how banks can juggle resources between SR 11-7 and AML/BSA compliance.
Financial Crime and Risk Management— Separate Origins, Converging Practices
The traditional types of risk such as credit and market risk are about losses and are able to be quantified. It may not always be easy to mitigate risk, but the first step is to gather data and make calculations that provide a basis for decisions about whether any given business is worth doing.
Combating Financial Crime Through Model Risk Management
Models are complicated things, and the principles of model governance, implementation, and use are there to make sense of them, make them explainable, and confirm that they work. Let’s take a closer look at how financial institutions currently do that and check our recommended practices for robust financial crime prevention, detection, and reporting.
Related Industries
Additional Industries.
Investment Banks
Corporate & Commercial Banks
Asset & Wealth Management
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