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The question of “build versus buy” is every bit as applicable and challenging to model validation departments as it is to other areas of a financial institution. With no “one-size-fits-all” solution, banks are frequently faced with a balancing act between the use of internal and external model validation resources. This article is a guide for deciding between staffing a fully independent internal model validation department, outsourcing the entire operation, or a combination of the two. 

Striking the appropriate balance is a function of at least five factors:

  1. control and independence
  2. hiring constraints
  3. cost
  4. financial risk
  5. external (regulatory, market, and other) considerations
Balancing Model Validation Resources


Control and Independence

 Internal validations bring a measure of control to the operation. Institutions understand the specific skill sets of their internal validation team beyond their resumes and can select the proper team for the needs of each model. Control also extends to the final report, its contents, and how findings are described and rated.

Further, the outcome and quality of internal validations may be more reliable. Because a bank must present and defend validation work to its regulators, low-quality work submitted by an external validator may need to be redone by yet another external validator, often on short notice, in order to bring the initial external model validation up to spec.

Elements of control, however, must sometimes be sacrificed in order to achieve independence. Institutions must be able to prove that the validator’s interests are independent from the model validation outcomes. While larger banks frequently have large, freestanding internal model validation departments whose organizational independence is clear and distinct, quantitative experts at smaller institutions must often wear multiple hats by necessity.

Ultimately the question of balancing control and independence can only be suitably addressed by determining whether internal personnel qualified to perform model validations are capable of operating without any stake in the outcome (and persuading examiners that this is, in fact, the case).  


Hiring Constraints

Practically speaking, hiring constraints represent a major consideration. Hiring limitations may result from budgetary or other less obvious factors. Organizational limits aside, it is not always possible to hire employees with a needed skill set at a workable salary range at the time when they are needed. For smaller banks with limited bandwidth or larger banks that need to further expand, external model validation resources may be sought out of sheer necessity.

 

Cost

Cost is an important factor that can be tricky to quantify. Model validators tend to be highly specialized; many typically work on one type of model, for example, Basel models. If your bank is large enough and has enough Basel models to keep a Basel model validator busy with internal model validations all year, then it may be cost effective to have a Basel model validator on staff. But if your Basel model validator is only busy for six months of the year, then a full-time Basel validator is only efficient if you have other projects that are suited to that validator’s experience and cost. To complicate things further, an employee’s cost is typically housed in one department, making it difficult from a budget perspective to balance an employee’s time and cost across departments.

If we were building a cost model to determine how many internal validators we should hire, the input variables would include:

  1. the number of models in our inventory
  2. the skills required to validate each model
  3. the risk classification of each model (i.e., how often validations must be completed)
  4. the average fully loaded salary expense for a model validator with those specific skills

Only by comparing the cost of external validations to the year-round costs associated with hiring personnel with the specialized knowledge required to validate a given type of model (e.g., credit models, market risk models, operational risk models, ALM models, Basel models, and BSA/AML models) can a bank arrive at a true apples-to-apples comparison.


Financial Risk

While cost is the upfront expense of internal or external model validations, financial risk accounts for the probability of unforeseen circumstances. Assume that your bank is staffed with internal validators and your team of internal validators can handle the schedule of model validations (validation projects are equally spaced throughout the year). However, operations may need to deploy a new version of a model or a new model on a schedule that requires a validation at a previously unscheduled time with no flexibility. In this case, your bank may need to perform an external validation in addition to managing and paying a fully-staffed team of internal validators.

A cost model for determining whether to hire additional internal validators should include a factor for the probability that models will need to be validated off-schedule, resulting in unforeseen external validation costs. On the other hand, a cost model might also consider the probability that an external validator’s product will be inferior and incur costs associated with required remediation. 


External Risks

External risks are typically financial risks caused by regulatory, market, and other factors outside an institution’s direct control. The risk of a changing regulatory environment under a new presidential administration is always real and uncertainty clearly abounds as market participants (and others) attempt to predict President Trump’s priorities. Changes may include exemptions for regional banks from certain Dodd-Frank requirements; the administration has clearly signaled its intent to loosen regulations generally. Even though model validation will always be a best practice, these possibilities may influence a bank’s decision to staff an internal model validation team. 

Recent regulatory trends can also influence validator hiring decisions. For example, our work with various banks over the past 12-18 months has revealed that regulators are trending toward requiring larger sample sizes for benchmarking and back-testing. Given the significant effort already associated with these activities, larger sample sizes could ultimately lower the number of model validations internal resources can complete per year. Funding external validations may become more expensive, as well.

Another industry trend is the growing acceptance of limited-scope validations. If only minimal model changes have occurred since a prior validation, the scope of a scheduled validation may be limited to the impact of these changes. If remediation activities were required by a prior validation, the scope may be limited to confirming that these changes were effectively implemented. This seemingly common-sense approach to model validations by regulators is a welcome trend and could reduce the number of internal and external validations required. 
 

Joint Validations

In addition to reduced-scope validations, some of our clients have sought to reduce costs by combining internal and external resources. This enables institutions to limit hiring to validators without model-specific or highly quantitative skills. Such internal validators can typically validate a large number of lower-risk, less technical models independently.

For higher-risk, more technical models, such as ALM models, the internal validator may review the controls and documentation sufficiently, leaving the more technical portions of the validation—conceptual soundness, process verification, benchmarking, and back-testing, for example—to an external validator with specific expertise. In these cases, reports are produced jointly with internal and external validators each contributing the sections pertaining to procedures that they performed. 

The resulting report often has the dual benefit of being more economical than a report generated externally and more defensible than one that relies solely on internal resources who may lack the specific domain knowledge necessary.

 

Conclusion

Model risk managers have limited time, resources, and budgets and face unending pressure from management and regulators. Striking an efficient resource-balancing strategy is critically important to consistently producing high-quality model validation reports on schedule and within budgets. The question of using internal vs. external model validation resources is not an either/or proposition. In considering it, we recommend that model risk management (MRM) professionals

  • consider the points above and initiate risk tolerance and budget conversations within the MRM framework. 
  • reach out to vendors who have the skills to assist with your high-risk models, even if there is not an immediate need. Some institutions like to try out a model validation provider on a few low- or moderate-risk models to get a sense of their capabilities.  
  • consider internal staffing to meet basic model validation needs and external vendors (either for full validations or outsourced staff) to fill gaps in expertise.