By giving clients an advance view of their industry’s recent performance, our Nowcasting platform gives them the power to make timely critical decisions, and stay a step ahead.
In today’s fast-changing environment, leaders need a faster and more accurate look at how their industry, market, and the economy are doing, but publication of official indicators can lag by 3 months or more. Risk Dynamics’ Nowcasting platform helps clients develop a robust statistical framework that gives them the earliest performance estimates, so they can shape their risk strategy, management, and product offerings.
We use robust and low dimensional statistical techniques and a trove of “alternative” high frequency data – things like web search and social media trends, job listings, card swipes, and restaurant reservations. Our Nowcasting approach offers significant granularity across countries and industries. Our analytics are tailor-made for clients, and transparent to them, facilitating easy interpretation. They are also pragmatic, allowing for natural integration into clients’ existing analytics capabilities. The Nowcasting platform is focused on maximizing impact for every client.
To navigate deep uncertainties created by the COVID pandemic and support sound credit decisions, a large European Bank engaged Risk Dynamics to help strengthen its views of different economic sectors.
Our solution applied the Nowcasting methodology to help the bank gain real-time views, overcoming the publication lag of official figures, and the limitations of traditional forecasting during times of unexpected market turmoil. We help the client improve their credit provisioning and refine its credit risk strategy.
We co-developed these sector views with the client through “sprints” that applied high-frequency and unconventional data - rapidly producing 5 models of Nowcasting on high-relevance sectors. This work endowed the Bank with a new and scalable model methodology, technical competencies needed to expand the base of models, and a new mindset to tackle current uncertainties. We also applied McKinsey’s sector-specific knowledge to guide the client in the first phases of the models’ design, and in validating results.
As the result of our work, the bank reached a high degree of autonomy in developing Nowcasting models to improve its sector views, and leveraging those views to support a variety of different processes in a scalable way.
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.
Marie-Paule serves major financial institutions and other companies, specializing in all elements of risk modelling and model risk management. She has most recently focused on helping clients de-risk their operations based on advanced analytics.