Model Risk Management with SAS

SAS

• Editore: SAS Institute
• Anno: 2020
• ISBN:
  9781970170658
• Argomento: Computer Science
• Categoria: Data Processing

Cut through the complexity of model risk management with a guide to solutions from SAS!

There is an increasing demand for more model governance and model risk awareness. At the same time, high-performing models are expected to be deployed faster than ever. SAS Model Risk Management is a user-friendly, web-based application that facilitates the capture and life cycle management of statistical model-related information. It enables all stakeholders in the model life cycle — developers, validators, internal audit, and management – to get overview reports as well as detailed information in one central place.

Model Risk Management with SAS introduces you to the features and capabilities of this software, including the entry, collection, transfer, storage, tracking, and reporting of models that are drawn from multiple lines of business across an organization. This book teaches key concepts, terminology, and base functionality that are integral to SAS Model Risk Management through hands-on examples and demonstrations. With this guide to SAS Model Risk Management, your organization can be confident it is making fact-based decisions and mitigating model risk.

Chapter 1: Introduction to SAS Model Risk Management

Overview

Regulatory Environment

Design Principles

Example

Model Risk Dashboard

Model Governance Overview Dashboard

Operational Environment

Summary

Overview

In this chapter, you will be introduced to SAS Model Risk Management. Model governance and model risk management is getting increasingly demanding. The number of models is rising based on both regulatory and business demands. The amount of input data is growing and getting more complex. And on top of that, the authorities are placing stricter demands on the organization’s ability to keep the overview and make fact-based decisions around the governance of models and the mitigation of model risk.

SAS Model Risk Management enables all stakeholders in the model life cycle – developers, validators, internal audit, and management – to get overview reports as well as detailed information in one central place. Not only does the solution ensure that the model validation team can easily provide quick replies to questions and inspections from the authorities, but it also provides business benefits through better overview and higher efficiency in the model life cycle.

With SAS Model Risk Management, there are two key focuses that drive our product. The first is delivering efficiencies and other benefits to modeling teams. We know that banks spend a tremendous amount of resources on their models. Having a solution that helps organizations work more efficiently is one of the key business drivers behind the solution. The other, of course, is reducing the risk associated with those models.

SAS Model Risk Management goes above and beyond legacy and operational risk approaches. It is driven by robust qualitative and quantitative components. Combined with the integration with the entire SAS modeling infrastructure, the product allows all of those components to work in a much more efficient way.

Regulatory Environment

When we look at what is currently happening in the banking industry, we can clearly see that banks are being challenged on multiple fronts simultaneously. First, there is an increasing demand for more model governance and model risk awareness. This is coming from both the business side, pushing for high utilization of models in banks’ decision-making, and also from the regulatory side where the recent guidelines have put banks under unprecedented scrutiny. At the same time, banks are pushed to faster model deployment and increased model performance. Lastly, in peril, banks are required to build new models. A very good example of this is the IFRS 9 impairments.

According to some senior model risk managers, IFRS 9 will have a significant impact on banks’ MRM processes. Compared to the current impairment regime, IFRS 9 will have more financial impact and will require more impairment provisions, which will have to be recalculated more often to capture the changes in credit quality. The impairments calculation will be more complex, will require the collection of more data, and will require the development of more models. IFRS 9 principles offer more alternative interpretation that will define the new methodology behind these new models. All of this work will require much more internal cooperation between risk and finance. And everything will have to be accepted by the statutory auditor. Therefore, robust governance around all this new data – models, interactions, and calculations – will be crucial. The impact of IFRS 9 should not be underestimated when thinking about the future of banks, model risk management, and model risk governance processes.

IFRS 9 is just one piece of the puzzle in all these developments, though. The SAS Model Risk Management solution is designed to address not only the current challenges that banks are facing now, bu...