Model Management and Governance - By Martin Butler

Using predictive models

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Executive Summary:

To some degree, we're living in a world where we are cursed with our own success. Financial institutions have seen tremendous benefits from analytics, and as a result, they are using predictive models on an increasingly broader scale, to measure capital reserve requirements and manage complex customer decisions. But do more models equal more problems? The greater complexity and number of predictive models in use makes it even more difficult to track and manage model performance, not to mention comply with regulatory requirements.

In Martin Butler's white paper, "Model Compliance and Governance" you will learn how, through a strong model management framework, you can comply with regulatory requirements – as well as reduce your risk and grow your business.

The same model tracking, monitoring and documentation practices required for regulatory compliance also enable institutions to evaluate and refine model performance in ways that control losses and boost portfolio profitability.

A model management platform also needs to facilitate integration, making sure to include activities such as optimization, business rules management, and decision-making. All of this will help you:

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  • Reduce regulatory overhead. Spend less time on audits and more time developing new models. Address regulatory requirements easily through workflows and documentation.
  • Avoid poor decisions caused by degraded models. By automating the validation, tracking, and monitoring of existing models, you can receive early identification of model degradation—and making your best decisions.
  • Deploy models quickly. With reduced regulatory overheard, the environment is better managed and you can dedicate more resources to the task. Also, FICO has tools available to port models from one language to another; the one used in development environment might not be the one used in production. Without these tools, significant delays and extra costs are almost a given.
  • Consider all your options. Model management is a prerequisite for optimization and reporting. By offering more sophisticated modeling and simulation, what-if scenarios can be tested and analyzed through prescriptive analytics.

Save time. Save money. Keep your teams focused on business requirements, and not overloaded by compliance workloads. Learn more about how effective model management can do that for you. Download "Model Compliance and Governance - White Paper" by Martin Butler.