September 29, 2019 Subject:
The Evolution of Model Risk Management: for Managers and World Leaders
An increasing reliance on models, regulatory challenges, and talent
scarcity is driving banks toward a model risk management organization
that is both more effective and value-centric.
he number of models is rising dramatically—10 to 25 percent annually at large
institutions—as banks utilize models for an ever-widening scope of decision making.
More complex models are being created with advanced-analytics techniques, such as
machine learning, to achieve higher performance standards. A typical large bank can now
expect the number of models included within its model risk management (MRM) framework
to continue to increase substantially.
Among the model types that are proliferating are those designed to meet regulatory
requirements, such as capital provisioning and stress testing. But importantly, many of the
new models are designed to achieve business needs, including pricing, strategic planning,
and asset-liquidity management. Big data and advanced analytics are opening new areas for
more sophisticated models—such as customer relationship management or anti-money
laundering and fraud detection.