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Model Validation Best Practices: Achieving Value-Added

Celent outlines a framework geared toward mitigating inherent risks borne by financial institutions' complex network of models.

The last decade has seen a maturing process for the management of financial risks. One of the drivers of this process has been the increasingly complex dynamics of the global financial markets, which have brought about the necessity for commensurately complex models. The upsurge in usage of models has firmly placed model risk (the risk that models do not perform as intended) on regulators' and executives' agendas.

Building a model governance framework to contain this risk has become a prevalent risk management practice. Model validation, essentially a peer review system with the ultimate goal of providing efficient quality control, has been an integral part of these efforts. With a few exceptions, financial institutions have approached model validation as a compliance activity. In a new report, Model Validation Best Practices: Achieving Value-Added, Celent advises institutions to build a streamlined process that can deliver robust quality control around the entire model lifecycle.

"We have seen quite a bit of activity in this area over the past few years. The focus has mostly been complying with various regulations. The next wave is going to be characterized by achieving a value-added model validation framework that goes beyond compliance," says Umit Kaya, co-author of the report.

The report introduces the concept of a model lifecycle and presents a model governance framework around it derived from first principles. The best practices highlighted in the report outline everything from high-level model governance setups to the actual validation processes that materializes the value-added. Observations on pitfalls from the experiences of many diverse financial institutions are offered throughout the report.

"The recent market turmoil has shown that models are only as good as their weakest links. Model risk is not limited to a particular stage in the model lifecycle. Neither should model validation be," Kaya adds.

The past few years have seen the establishment of model validation units. However, best practices are only employed by a minority, and it would be optimistic to conclude that the state of the market is close to the end game. A significant portion of market participants have approached model validation with the mindset of a one-off exercise or a pure compliance activity. Optimizing returns from the investment in model validation requires more.