Many of the models we validate on behalf of our clients are developed and maintained by third-party vendors. These validations present a number of complexities that are less commonly encountered when validating “home-grown” models. These often include:

  1. Inability to interview the model developer
  2. Inability to review the model code
  3. Inadequate documentation
  4. Lack of developmental evidence and data sets
  5. Lack of transparency into the impact custom settings

Notwithstanding these challenges, the OCC’s Supervisory Guidance on Model Risk Management (OCC 2011-12)1 specifies that, “Vendor products should nevertheless be incorporated into a bank’s broader model risk management framework following the same principles as applied to in-house models, although the process may be somewhat modified.”

The extent of these modifications depends on the complexity of the model and the cooperation afforded by the model’s vendor. We have found the following general principles and practices to be useful.

model validation for vendor models

Vendor documentation is not a substitute for model documentation

Documentation provided by model vendors typically includes user guides and other materials designed to help users navigate applications and make sense of outputs. These documents are written for a diverse group of model users and are not designed to identify and address particular model capabilities specific to the purpose and portfolio of an individual bank. A bank’s model documentation package should delve into its specific implementation of the model, as well as the following:

  • Discussion of the model’s purpose and specific application, including business and functional requirements achieved by the model
  • Discussion of model theory and approach, including algorithms, calculations, formulas, functions and programming
  • Description of the model’s structure
  • Identification of model limitations and weaknesses
  • Comprehensive list of model inputs and assumptions, including their sources
  • Comprehensive list of outputs and reports and how they are used, including downstream systems that rely on them
  • Description of testing (benchmarking and back-testing)

Because documentation provided by the vendor is likely to include very few if any of these items, it falls to the model owner (at the bank) to generate this documentation. While some of these items (specific algorithms, calculations, formulas, and programming, for example) are likely to be deemed proprietary and will not be disclosed by the vendor, most of these components are obtainable and should be requested and documented.

Model documentation should also clearly lay out all model settings (e.g., knobs) and justification for the use of (or departure from) vendor default settings.

model validation Testing results should be requested of the vendor

OCC 2011-12 states that “Banks should expect vendors to conduct ongoing performance monitoring and outcomes analysis, with disclosure to their clients, and to make appropriate modifications and updates over time.” Many vendors publish the results of their own internal testing of the model. For example, a prepayment model vendor is likely to include back-testing results of the model’s forecasts for certain loan cohorts against actual, observed prepayments. An automated valuation model (AVM) vendor might publish the results of testing comparing the property values it generates against sales data. If a model's vendor does not publish this information, model validators should request it and document the response in the model validation report. Where available, this information should be obtained and incorporated into the model validation process, along with a discussion of its applicability to data the bank is modeling. Model validators should attempt to replicate the results of these studies, where feasible, and use them to enhance their own independent benchmarking and back-testing activities. 

Developmental evidence should be requested of the vendor

OCC 2011-12 directs banks to “require the vendor to provide developmental evidence explaining the product components, design, and intended use.” This should be incorporated into the bank’s model documentation. Where feasible, model validators should also ask model vendors to provide information about data sets that were used to develop and test the model.

Contingency plans should be maintained: OCC 2011-12 cites the importance of a bank’s having “as much knowledge in-house as possible, in case the vendor or the bank terminates the contract for any reason, or if the vendor is no longer in business. Banks should have contingency plans for instances when the vendor model is no longer available or cannot be supported by the vendor.” For simple applications whose inner workings are well understood and replicable, a contingency plan may be as simple as Microsoft Excel. This requirement can pose a significant challenge, however, for banks that purchase off-the-shelf asset-liability and market risk models and do not have the in-house expertise to quickly and adequately replicate these models’ complex computations. Situations such as this argue for the implementation of reliable challenger models, which not only assist in meeting benchmarking requirements, but can also function as a contingency plan backup.

Consult the model risk management group during the process of procuring any application that might possibly be classified as a “model”

In a perfect world, model validation considerations would be contemplated as part of the procurement process. An agreement to provide developmental evidence, testing results, and cooperation with future model validation efforts would ideally figure into the negotiations before the purchase of any application is finalized. Unfortunately, our experience has shown that banks often acquire what they think of as a simple third-party application, only to be informed after the fact, by either a regulator or the model risk management group, that they have in fact purchased a model requiring validation. A model vendor, particularly one not inclined to think of its product as a “model,” may not always be as responsive to requests for development and testing data after sale if those items have not been requested as a condition for the sale. It is therefore a prudent practice for procurement departments to have open lines of communication with model risk management groups so that the right questions can be asked and requirements established prior to application acquisition.

[1] See also: Federal Reserve Board of Governors Guidance on Model Risk Management (SR 11-7)

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