Riskthinking.AI: Using Digital Twin Technology to Project Climate Finance Risk

Riskthinking.AI: Using Digital Twin Technology to Project Climate Finance Risk

Author: Paul Ellis November 3, 2024 Duration: 25:51
In 1989, Ron Dembo founded Algorithmics Inc., which he grew from a start-up to the largest supplier of enterprise financial risk systems, serving 80% of the world’s largest banks and insurers. Fast forward to 2020, with just three employees, Dembo embarked on and even bolder mission, launching Riskthinking.AI–a groundbreaking simulation engine capable of modeling the world’s largest financial institutions, the most complex corporations, and even entire countries, all to assess the impact of climate change on their futures. On today’s program, Dembo talks to us about developing a platform that is scientifically rigorous, mathematically sound, scalable, computationally efficient and evolving alongside advancements in data science.

Hosted by Paul Ellis, The Sustainable Finance Podcast is a resource for investors and financial advisors looking to move beyond the buzzwords and understand the practical realities of integrating environmental, social, and governance principles into portfolios. This isn't about abstract theory; it's a series of direct conversations with the people shaping the industry-from asset managers and analysts to corporate leaders and policy experts. Each episode digs into how sustainability metrics are being applied, what constitutes genuine impact versus marketing, and where the real financial opportunities and risks lie. You'll hear detailed discussions on evolving regulations, new investment vehicles, and the tangible data driving decisions. By focusing on these candid interviews with pioneers, the podcast provides a clear-eyed view of a rapidly changing landscape, offering actionable insights for anyone navigating the intersection of capital and responsibility. Tune in for a grounded perspective that equips you to participate in this critical shift within modern finance.
Author: Language: en-us Episodes: 100

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