MEW is a technology platform that lets clients standardize, digitize, and automate model analytics workflows at every stage.
Digital and analytical models are increasingly defining the DNA of financial institutions. As data volumes, the model landscape, and the number of use cases explodes, these institutions need faster, more efficient and effective model analytics. Unfortunately, many analytics processes are highly customized, with limited automation, leading to unexpected re-work and model iterations. The MEW platform, supported by our decades of experience in this domain, allows clients to transform model development, validation, and ongoing activities such as monitoring, re-validation and annual model review.
By using industry-grade, open-source technologies, MEW leverages clients’ own environments and tools, augmenting them with our insights into effective processes, and codified libraries for development, testing, and assessment. As a result, we can reduce turnaround times and improve process efficiency on average by 30 to 50 percent or more. We focus on the model domains that matter most to our clients, and we work at scale.
A financial infrastructure player engaged Risk Dynamics to help streamline and improve recurring model validation activities for its initial margin and stock haircut models.
We applied MEW’s digitization and automation features, and our own expertise, to eliminate manual and recurring elements of the validation workflow. That workflow now delivers precise, reproducible and consistent results, including full replication, back-testing, and report production.
For replication and back-testing, we applied modularized codes and test plans, making them reusable and easy to maintain. Users now apply independent parameter files to run a variety of tests under different conditions, with consistent, error-free results. For reporting, the client now generates validation reports automatically, with one click, following a pre-defined, standardized template.
Today, the client’s periodic validation of market risk models is over 50 percent more efficient, saving resources and time. Validation activities follow a codified, standardized approach, which the client can apply to similar models throughout the organization.
Frank develops & implements innovative risk management solutions through digital innovation and advanced analytics, bringing 25 years of research and industry experience in statistics, econometrics, and machine learning.
Pedro develops & implements innovative advanced analytics risk management solutions leveraging digitization & automation bringing 20 years of industry experience in data, systems & architecture, Stress Testing and Capital & Balance Sheet Management.
Andreas advises clients across the breadth of the financial industry, has led expansion of Risk Dynamics into APAC in recent years, and is now leading client development of new value propositions with primary focus on Europe.
Christophe is a leader of McKinsey’s North America Model Risk Management Service Line. He serves financial institutions across North America and Europe on a broad breadth of analytics topics, along with application of intelligent automation, and management of financial risk.