Get ready for climate
regulations.

To guide business strategy, it’s essential to understand that climate financial risk data must take account of the radical uncertainty of climate change.

This data must include probability distributions that represent:

• every risk factor (sea-level rise, heat stress, hurricanes, extreme precipitation and more)
• in relevant business geographies across the entire surface of the planet
• from now until the end of the century.

Achieving this level of data, and maintaining it over time, is a Herculean task. Yet it’s vital if we want to measure future climate risk with any accuracy.

Riskthinking.AI is one of the few companies to offer this level of granular data.

Our VELO® climate data platform is the only available platform to offer probabilistic (stochastic) analysis of climate financial risk.

Our data derives from climate science, mathematical models, scientists’ views and climate models – all of which evolve constantly.

It is constructed around every single physical and transition risk variable needed to conduct climate risk assessments – at any future period.

The climate risk of every asset depends on its location and function. The toughest data challenge facing banks, insurance and other companies is the physical nature and location of their and their counterparties’ assets. For most, these assets are geographically dispersed.

To accurately measure climate financial risk, this data needs to be sourced, continuously updated, and aligned geospatially and temporally.

Even the biggest and best data providers struggle with it. This is where riskthinking.AI shines.

Our VELO® assets database contains the physical assets of over 200,000 companies, most of which represent the equity indices of the world’s major financial markets.

VELO® is the first platform on the market to decipher the complex physical structure of counterparties’ assets. It contains information on asset type, emissions, financial data, global ownership structure, location, building size and more.

Most market-ready climate financial risk solutions treat physical and transition risk as separate entities.

Yet physical and transition risk are intimately linked.

The physical assets of counterparties change over time. A shift in company strategy will influence the future physical nature of every single asset. It follows that the physical nature of a company is closely linked to the transitions it undergoes – and its future is inherently uncertain.

This means data must consider every imaginable future transition – due to strategy, technology, politics and more – and take account of the resulting benefits and cost.

At riskthinking.AI we integrate all risks – physical and transition – and apply our patented algorithm to stress test a dynamically changing portfolio of physical assets.

Most assets, when affected by climate, are likely to be influenced by multiple risk factors.
This means climate financial stress testing requires a range of multifactor stress scenarios.

We have developed and patented a multifactor stress testing algorithm that is driven by empirical data and is consistent with the uncertainty data we collect.

Using this algorithm, we can generate stress tests that combine multiple, distinct risk factors such as strategy, technology, political, transition and physical risk, among others.

This gives riskthinking.AI one of the world’s most advanced tools for modelling real-world climate financial risk situations.

We test the behavior of our ‘uncertain future data’ models against their analysis of actual extreme events. After all, risk management is largely about low probability, high impact events (the tail risk).

To do this we back-test the validity of our stochastic data by observing how it uncovers “black swans” before they occur.

Our stochastic approach has captured over 90% of record-setting extreme weather events and 100% of carbon price changes in 2022.