The Risk Enabled Enterprise® Model Risk Management

<p>The Risk Enabled Enterprise^® is a two-year research initiative from Chartis, in collaboration with IBM, that looks at the enablers of enterprise risk management (ERM). Our research identified four strategic initiatives that firms can use to become “risk-enabled” across organizational structure and process,&nbsp;people and culture, and data and systems. This report, covering model risk management, is the first of four to examine these initiatives and identify best practice practical implementation.</p>

<p>Today, model risk management has become a major issue for financial institutions. These organizations increasingly depend on models to estimate risk, inform decision-making, to drive operations and strategy, and to set their future direction. As the business environment becomes more complex, and&nbsp;as regulatory scrutiny increases, it has never been more crucial for financial institutions to ensure their models are robust and fit for purpose. This is where the concept of model risk arises.</p>

<p>For this report, Chartis set out to understand the issues organizations face in managing model risk, and the strategies and best practices that can be implemented to address this increasingly important area. Our research included an online survey of 142 professionals working in a wide range of sectors&nbsp;around the world, as well as in-depth follow-up interviews with 25 survey respondents. We also held discussions with subject matter experts from IBM (to learn more about IBM’s approach to Model Risk Management, visit ibm.com/SmarterRiskAnalytics).</p>

<p><strong>Highlights from the report include:</strong></p>

<ul>
<li>Few firms have a comprehensive model risk management program: Only 12% of organizations have a comprehensive model risk management program, although 46% say it is a high priority or their highest priority. Firms need an organizational structure that supports end-to-end model risk management, and ensures that senior management is kept aware of model risk.</li>
<li>Regulatory pressure is driving increased interest in model risk: Compliance requirements were cited as a driver of model risk management by 59% of respondents. But these requirements have pigeon-holed model risk management into being viewed as a compliance-based cost burden rather than as a potential driver of strategic goals. Model risk management programs can support strategic goals, particularly the integration of disparate processes and systems and improved links between risk and performance, however, these broader benefits have often become lost in the drive to comply with prescriptive model risk requirements</li>
<li>Data is a major challenge: Poor quality data and insufficient data are viewed as the two most significant sources of model risk. 72% of respondents said they view poor quality data as an important or very important source of risk. Firms need to set up a dedicated model inventory system and develop dedicated model risk management technology tools and systems to assess model risk.</li>
<li>Organizational and structural challenges to model risk management: Integration between risk and finance systems represents a key priority. Firms also require strong leadership and dedicated education and training plans to establish model risk management programs. In addition, they need to make the links between model risk and remuneration strong and clear.</li>
</ul>

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• Topics
• HPC/Calculation/Processing
• Model Management & Validation
• Technology
• Risk & Data Technologies
• GRC and Operational Risk
• Data management
• Data integrity
• Big Data