Model Risk Management- Needs a thoughtout execution strategy

Model Risk Management – Efficient, Effective and Transparent
“Can you imagine risk of nuclear power generation without functions to monitor and control conditions of the reactor?”
An evolving environment
The global financial crisis ushered in a new era of increased regulatory scrutiny. In this new environment, regulators have, and continue to implement a host of new laws and rules to prevent a repeat of the crisis. A number of these regulations, namely, the Dodd-Frank Act, Basel III framework and Solvency Act affect financial institutions around the way they manage a broad range of business services and activities including credit decisions and valuation (e.g., exposures, instruments). To assist in the management and decision making process, banks have been increasingly relying on quantitative models for these activities. However, more recently banks have extended these models into more complex activities such as enterprise wide risk measurement and determining minimum regulatory capital. This reliance on models carries with it a high level of operational risk, and because of the guidance issued by Federal Reserve in SR 11-7  provided guidance for model risk management by broadening the scope of model validation activity to manage model risk like other types of risks.  Now, banks have little option but to invest heavily in implementing effective model risk management in order to prevent incorrect business and financial decisions being made. At a time when institutions are looking at ways to reduce cost and increase efficiency, enforced ring fencing of high cost model risk management has been a pain point for many banks.
Changing the way you do business
Model risk management begins with robust model design, development, and model review & validation deployment, accompanied by sound monitoring process. These aspects form various stages of the model life cycle, and impact senior management, the Board of directors, Internal Audit, model developers, owners, users and model validators. Model governance, an important aspect in model risk management, sets an effective framework with defined roles and responsibilities for clear communication of model limitations and assumptions to improve transparency, as well as the authority to restrict model usage among various stakeholders.

In the implementation of model risk management, the rising costs of implementing various aspects of the model life cycle and the risk of adverse consequences from failure of the models have become clear pain points for senior management. Therefore, Banks have to think how to integrate various aspects of model life cycle within the framework of model risk management by optimizing cost efficiency and model effectiveness. Effective model risk management can help mitigate the impact of these pain points. Effective management of model risk requires an overall risk management framework which must be built on a coherent architecture that includes identification, assessment, and mitigation, monitoring and reporting activities at various stages of model life cycle. This will result in important benefits by ensuring effectiveness of the MRM Communications of model risk assessment to all the stakeholders.

• This way senior management and regulators clearly understand the embedded model risk in the models they are using.

Cost efficiency gains with in model life cycle activities.

• Implementation and ongoing monitoring and validation costs can be controlled by efficiently managing model validation and model development processes with proper model governance function.
• Model validation process should be transformed into a cost effective and efficient process by redesigning to handle large inventory of models with less number of personnel in limited time frames.

Strategy
Currently many institutions have either initiated the work or already in the midst of the implementation of the model risk management. All of these firms are racing towards the deadline of decemeber 2014. They are investing resources and personnel reluctantly. As they consider model risk management is leading to more pressure on their revenues. In a short period of time banks have to validate their, capital planning models, Risk management models, Credit models and other VAR models. for each of these models, examining the inputs, output analysis, bench marking against industry standard models and performing a comprehensive test for theoretical soundness of the model needs skills. Along with the validation of models, ongoing monitoring of the models and periodic validation needs investments. There are many ways one can think to solve the problem of performing a cost efficient model risk management. All of these approaches look at the concept of identify the target, understand the target and execute the plan on the target. I think over the last decade many of the valuation methodologies have matured with newer one's being invented in the wake of financial crisis. Valuation processes and models can be segregated into high to low risk categories and then they can be validated against a battery of tests and document and report the results. Efficient and effective model risk management is the nirvana state regulators are on the look out for. How this will play out only time will answer.