Risk Dynamics helps clients create sustainable modelling and analytics platforms to support their businesses in a data-driven world. From core regulatory capital and risk models to business decision analytics and model risk management, we create value by improving performance across the model lifecycle.
Risk Dynamics is a team of over 200 experts in data, analytics, model development, and model risk covering all major geographies across the globe. As part of McKinsey & Company, we combine quantitative analysts, PhDs, actuaries, former regulators, and business consultants to provide a powerful combination of deep analytics expertise, industry knowledge, regulatory perspective, and distinctive capabilities in corporate strategy and transformation.
We work with companies across financial services, energy, manufacturing, pharmaceuticals, healthcare, and many other sectors to develop and deploy leading capabilities in data, analytics, modeling, and model risk management. We support clients in everything from large-scale analytics programs to in-depth modeling exercises.
There are many applications that can help public agencies improve outcomes and streamline processes to make the best use of limited resources. New technologies, including AI and ML do come with challenges, and understanding these risks, including bias, is crucial for organizations to increase positive outcomes.
In the decade since US banking regulators published SR 11-7, model-risk management development has continued to evolve, challenged even more so by the COVID-19 pandemic. Six best practices may help banks to rebuild better after the crisis and avoid undesirable trade-offs between cost, timelines and quality.
Given the complexities of the global marketplace, it is critical that FIs improve the management of their model life cycle to improve efficiencies and controls. By taking a more integrated, strategic approach to the management of the model life cycle, banks can unlock massive model development and validation potential.