Unreachable data in your model inventory? - Introducing the Reporting module
A good model inventory effectively steers internal risk model lifecycles and tracks performance and operations lifecycles (modelOps), and having a solid model inventory is becoming more and more of a necessity for banks and financial institutions.
Model inventories, however, are not without their issues. One of the most common concerns we hear from customers is, in fact, the most obvious - availability of the dynamic information maintained by the model inventory to other systems. Simply put, data from the model inventory needs to be readily available for different purposes and in different formats. Nobody wants to input and maintain structured information that is then locked away from the corporate ecosystem.
The unique information maintained by the model inventory is a combination of manually entered model metadata, automatically calculated figures sourced from various MRM algorithms, statuses of countless connected workflows assigned across the entire organization, and inputs from external systems for model operations. A good model inventory should work as a single source of truth for the entire model portfolio state.
The corporate information system is typically a composition of many systems fulfilling various internal or regulatory tasks. These systems are often built in many technologies and include in-house developed scripts and small apps which, ideally, should all have access to the information maintained in the model inventory.
How does MGS solve this organizational roadblock?
To help make this important data easily available to 3rd party systems, we introduced the Reporting module for our MGS platform. Users can access all model-related data available in MGS using a real time interface compatible with well-known BI reporting tools like PowerBI, Tableau, and even MS Excel. This allows users to read specific variables or process statuses, perform joins, and carry out other data related operations. This interface also allows integration with 3rd party components built in languages like python or R.
Reporting can also be problematic for data protection. Access to the data must sometimes be granted to teams or systems which don't regularly have access. To help keep your information safe, MGS can define access to specific data on a granular level, even within the reporting module.
So, you want to build an MRM dashboard or an overview of all the ML model's production deployment status sourced directly by the real time data? Or maybe simply save & send lists of regulatory model key attributes and risk scores in Excel format? We can show you how to do it using our MGS Reporting module.
MGS reporting capabilities in action:
Using the reporting module gives an easy way to use tools that you already know and plug MGS into your data pipelines.
Contact us for more information how to setup your automated model monitoring and portfolio status reporting in MGS.
Author: Martin Podolinský
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