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Emerging Trends in Model Risk Management Introduction Emerging Trends in Model Risk Management Introduction Financial institutions rely more and Banks are also modeling many key As a result, the danger stemming from more upon advanced mathematical, elements of business planning and rare yet plausible occurrences might statistical and numerical models development, such as the appropriate be understated, as such occurrences to measure and manage risk bundling of product features, customer might not appear in reference data and manage their businesses.1 or on-customer income, or churn rates. sets or in historical data patterns. Models are used to calculate economic capital charges for various types of As the use of these models increases, In order to mitigate potential emerging exposure, subject to different risk so does the possibility that any risks, the discipline of model risk types – such as credit, market, or particular model may not properly management (MRM) has evolved operational. Through their individual capture financial risk. Model error over the years to support emerging components the bank’s current liquidity refers to the simplification or regulatory and business agendas. position is projected under alternative approximation of reality within models, Until recently, industry MRM efforts scenarios, as well as the projection incorrect or missing assumptions, have focused upon the management of the balance sheet and income incorrect design processes, and of risk for individual models; now, statements for use in stress testing.2 errors in measurement or estimation. however, we are seeing more Model misuse is the application of institutions focus on quantifying and models outside the use for which aggregating enterprise-wide model risk. they were designed and/or intended. 2 Regulatory Guidance As the use of complex models has become prevalent in the industry, regulators have continued to push financial institutions to invest in model risk management, with focus on establishing comprehensive frameworks for active model risk management including robust development, validation and monitoring capabilities. In this regard, a high proportion of bank • As with other types of risk, model risk Within this framework, there are elements decisions are automated through decision can never be eradicated, only controlled of good governance that should be observed. models, which can be statistical in nature, by effective risk management, including In particular, in our view the three elements or a methodology that constitutes a rule-set.3 comprehensive model development and of model ownership (identification and There are several areas in which we see this rigorous model validation. measurement of the model risk to which the trend manifest itself. For example, an increased institution is exposed); model control (setting use of electronic trading platforms known • Institutions should establish an MRM limits, following up and independently as algorithmic trading that execute trade framework that is approved and overseen validating models); and model compliance commands which have been pre-programmed by senior management and the board (establishing processes to help perform (e.g., through timing, price or volume), and can of directors. ownership and control rules in accordance 4 be initiated with manual intervention. • A well-documented and structured with accepted policies) are essential. At this time, supervisory guidance on approach to model development and Overall, the supervisors expect institutions model risk management is limited, validation can be useful in managing to create MRM frameworks that feature and the regulations published to date model risk, but is not a substitute for the model development and validation criteria tend to be based on principles; that is, continuous process of improving models. which are formalized, promote careful they lack specificity in how to define • Prudent use of models is likely to involve model use, establish criteria to assess model and treat model risk. elements such as conservative adjustments, performance, and define policy governance stress testing or capital buffers, but an for consistent implementation of framework In the US, the Federal Reserve and the Office and applicable standards of documentation. of the Comptroller of the Currency (OCC) over-reliance on such elements may lead to the misuse of models. This holistic approach to model risk combined to publish the Supervisory Guidance management continues to be adopted by the on Model Risk Management, which lays out • There are many potential sources of model financial services industry, and we expect it 5 basic principles for model risk management: risk and therefore institutions should to become increasingly prevalent as more • Model risk is to be managed like other risks, consider the interaction of these factors institutions use such an approach. in that model risk managers should identify and try to quantify the aggregated model the sources of risk, assess the likelihood of risk that results from their combination. occurrence and the severity of any specific model failure. 3 Model Risk Governance Framework As seen in Figure 1 below, the organizational structure for MRM should establish clear lines for development and monitoring and provide the right incentives while promoting cross-functional involvement in model risk discussions. In our view, these are the key • Model Administrator. The model • Model Risk Committee. This is the roles involved in the model administrator is usually the supervisor senior management committee with governance process: of the model owner and may be responsible responsibility for overseeing the model for assisting the model owner with governance program. The committee • Model Owner. Ideally a person is assigned certain governance responsibilities. reports on risk issues and trends to responsibility for developing or maintaining the risk committee of the board, or a model, including documenting the model. The model administrator guides the takes other action as appropriate. The model owner will also lead the model model developers in his or her team to implementation process, along with the complete the model documentation, • Internal Audit. The internal audit function model user. The model owner is usually complying with the model validation undertakes the independent review of all responsible for ongoing model monitoring. department’s model document template. model risk and governance activities. • Model User. The model user has • Model Validation and Review. Independent While some overlaps may occur among the responsibility for the use of a model from the model owner, a validation unit is roles of model owners, model users and for business purposes. Each model assigned the responsibility to implement model administrators, the model validation, can have multiple model users. and oversee the model validation and model risk committee and internal audit review functions and the model governance functions should remain independent. program on a daily basis. Figure 1. Model Risk and Governance Framework Board Board risk committee Treasury Model risk committee Finance Enterprise analytics Risk Line of business Line of business Model administrator(s) Internal audit Model user Model owner(s) Model validation and review Model Model Model Change Ongoing Methdology implementation development documentation management monitoring Source: Accenture, August 2015 4 The Analytics Function As seen in Figure 2 below, the preferred approach to setting up an efficient modeling function is to have a modular team structure with specialized groups and/or centers of excellence addressing different aspects of the model lifecycle. A well-structured analytics • Documentation development of model function should follow an design and testing using standardized ordered process including: approved templates across lines of business (LoB) and risk types. • Methodology design, including model design research and development. • Implementation of a set of processes that leverages cross-functional teams • Execution of the development process under specializing in model implementation a well-defined and established process. and user acceptance testing (UAT). • Reporting of model risk rating and inventory. Figure 2. Proposed Analytics Function Model risk committee Enterprise analytics Methodology Development Documentation Implementation Validation Responsible for model Executes the Documents models via Cross-functional (LoB, Independent validation design research, development steps standardized approved IT, analytics) team and review function. develops list of approved for the model(s) templates, works with specializing in model methodologies and steps. concerned, follows an all other functions. implementation and established process. UAT process. Source: Accenture, August 2015 5 The Validation Function Finally, the key part of a model risk management framework in our view is establishing a strong and independent validation function. This function should be able to address the quantitative and qualitative review of models across the five broad areas of data, methodology, documentation, processes and governance. Figure 3 highlights some of the key themes that should be considered by the validation team while going through the process. As institutions continue to build out their with specialized skill sets to help drive An emerging trend in model validation is with validation function, they should consider the validation for all internal and vendor- regard to models for stressed capital (e.g.,
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