Regulatory Stress Testing and Econometric Modeling

Banks of all sizes are making substantial commitments of resources to comply with new stress testing standards. Regulators expect banks to develop stress testing programs consistent with the complexity, risk exposures, and business activities of the institution.

For clients that need to comply with the data, modeling and reporting aspects of the Dodd-Frank Act’s stress testing provisions, MountainView provides customized solutions to match each client’s unique circumstances and needs. We will follow industry accepted practices to design and implement your DFAST compliance program.

As further detailed below, our approach to meeting your stress testing needs addresses data management, peer identification and benchmarking, advanced modeling and analytics, and model risk assessment and validation. We provide our clients with a consolidated reporting package detailing our findings that is designed to inform your strategy and decision-making.

Data Management

Your risk management, accounting and regulatory processes must be underpinned by complete, accurate and timely data. Issues which emerge in midstream process stages can have severe consequences on the integrity of your final results or jeopardize your project timelines.

With this in mind, MountainView’s stress testing process commences with in-depth discussions with your management team regarding the data and systems architecture, combined with extensive evaluations of data structure, reliability and suitability.

Our goal is to develop for you a robust stress testing framework incorporating the advantages of both portfolio level (top-down) and position level (bottom-up) approaches. We aggressively pursue in-depth modeling when unique, complex or substantial risk exposures are present, even if your internal data is inadequate for a typical bottom-up analysis.

Peer Identification and Benchmarking

Peer analysis is an essential component of your stress testing process because it helps to ascertain if your performance is exceptional and it can provide a reasonable substitute in situations where your internal data is limited or unreliable. For example, structural breaks in your data can be caused by acquisitions, divestures and changes in your business strategy, data collection or reporting practices.

MountainView uses both quantitative and qualitative methods to identify suitable peers and incorporate peer data into the stress testing process.

Advanced Modeling and Analytics

For any given statistical problem, there’s no singular, perfect regression model that can be applied. Therefore, MountainView’s analytical framework is designed to reduce model risk and uncertainty by incorporating a variety of disparate techniques for feature selection and model specification.

We utilize a proprietary analytical tool that is designed to create a more transparent, efficient and error resistant modeling process. MountainView’s tool is designed to help:

  • Streamline the retention of supporting documentation and analytical annotations
  • Ensure that your results are repeatable
  • Play an instrumental role in your model validation and training

MountainView uses several other modules to create ALM model inputs for certain PPNR items and to collate ALM outputs for populating FR Y-16 regulatory submission forms. When feasible, we attempt to integrate our systems with your existing IT infrastructure in order to avoid creating model or process silos.

Model Risk Assessment and Validation

MountainView will use your ALM model as the core system for retaining starting balances and generating cash flow projections. This will ensure that we correctly model your cash flow dynamics and interactions across financial statement items or time horizons in an integrated manner. Using your ALM model also allows us to provide you with a comprehensive view of all of your financial accounts and supports other important calculations such as risk-weighted assets, estimates of OTTI, capital rations, liquidity measurements and operational risk impacts.

MountainView uses effective challenge methods, sensitivity analysis and validation techniques at every state of the process that are designed to ensure high integrity and accuracy of results.

As a part of MountainView’s model risk and assessment activities, we provide you with extensive documentation for all assumptions, alternatives considered, decisions, rumination and rationale developed at every stage of the stress testing process. The level of detail we provide in our analyses is accompanied by succinct commentary regarding the principal results, conclusions, key limitations and how outcomes can inform your business strategy.