Model risk tiering: an exploration of industry practices and principles

Model risk management continues to be an important area of risk management across financial services firms. Regulatory expectations for model risk management apply to an expanding number and variety of financial firms. In our conversations with clients, we find that many risk managers are unaware of standard practices in developing and implementing frameworks for model risk management. This paper – based on our experience as consultants, former banking supervisors and leaders of units focused on model risk management – seeks to shed light on one critical area of such frameworks: model risk tiering, or the rating of risk inherent in the use of individual models, which can benefit a firm’s resource allocation and overall risk management capabilities. Although the range of practice in model risk tiering across financial services is broad and varied, our work has revealed a number of insights. Most financial firms use explicit procedures and decision tools to assign models to risk tiers. Nearly all firms assign models to several risk tiers rather than seeking to rank them individually from high to low. Although most firms use model risk-tiering tools, these tools serve primarily to systematize the application of judgment to the risk posed by models rather than to directly quantify risk. A set of useful principles regarding the construction of such risk-tiering tools can be gleaned from observing industry practices. Tiering tools generally fall into one of two categories – scorecards or decision trees – with scorecard approaches being the more common of the two. Tiering tools generally take into account both the risk and the impact of model failure; the building blocks for these two factors include a variety of descriptors regarding the construction and use of each model in the inventory. Calibration of model risk-tiering tools is largely judgmental and often depends on whether the firm has a preexisting allocation of models to risk tiers. Governance over model risk-tiering tools is an evolving process with rising standards.