With experience spanning a wide array of sectors, Risk Dynamics specializes in the digital transformation of risk functions, risk modelling, and the de-risking of analytics.
Using advanced analytics, we help our clients detect, prevent, and mitigate potential risks by developing state-of-the-art risk data infrastructures and advanced analytics models. We reduce corporate-wide risks by automating and digitally transforming end-to-end risk management processes to improve controls’ efficiency and effectiveness. Further, we ensure that analytics use cases deliver expected performance levels and are subject to adequate controls.
Risk Dynamics has strengthened many GEM clients’ financial resilience by designing, implementing, and managing analytical models that reduce risk. Our experience spans a range of GEM sectors, including basic materials, oil and gas, electricity production and distribution, chemicals, and agriculture. For these clients, we have helped manage financial exposure throughout the economic cycle, estimated the impact of potential crises, and identified and managed risks associated with advanced analytics.
A major oil-and-gas company was seeking to better manage its portfolio risk. To assist this effort, Risk Dynamics developed a tool to model the company’s portfolio under several scenarios, including base, high, and decarbonization scenarios.
We incorporated into this tool the impact of investing in renewable energy sources (such as offshore wind farms) and consolidated data from several business lines to improve consistency. We developed coherent scenarios with related, underlying risk drivers. Then, we projected revenues from all business lines and incorporated investment policies into our projections. Finally, we built a proof of concept as a user-friendly tool.
For a company managing a large European country’s electricity grid, we collaboratively developed an innovative solution that assesses the impact of climate change on the transport of electric current. This complex model aims to reduce the impact of severe climate events by efficiently prioritizing mitigation strategies.
Risk Dynamics assessed the solution’s initial results on a local scale and helped to finalize the associated methodology. We also assured that the model’s final outcomes were sound, and we identified potential items to consider when expanding the solution to a broader set of situations.
Arvind assists executives across industries on their strategic and risk problems using a range of advanced analytics techniques, and enables firms to improve their own analytics capabilities. He leads Risk Dynamics in Americas.
Alfonso supports clients to strengthen their risk management frameworks and infrastructure, focusing on enterprise risk management, risk and control governance, risk modelling and analytics
Bryan leads complex, transformational data science engagements, helping clients apply artificial intelligence, including machine learning, natural language processing, and simulations, while also managing AI’s risks.
Marc supports banks, insurers, and industrial companies worldwide in their model risk management and validation initiatives.