The level and impact of damages from climate change has been rising significantly for years. They present a risk which threatens the resilience of society, the economy and our health systems across the globe. Whilst ESG benchmarking, standards and gap analysis are extremely useful tools in helping us understand and address our current situation - they are only a part of the picture. They are vital in helping us comply with customer and regulatory requirements, address supplier shortcomings and understand competitor preparations. However, we also need tools to help us understand the future impact over a longer time horizon. Climate stress testing and scenario analysis help assess physical exposure to the climate emergency and the transition risks to a low carbon society.
To date stress testing and scenario analysis has been a discipline utilized by financial services firms to meet regulatory demands including exposure of loan books, asset holdings and underwriting risks. The development of robust stress tests and scenario analysis can be complex and beyond the capabilities of many firms, requiring specialist data modelling and climate science skills. Together with Basinghall Analytics we have collaborated to develop a comprehensive stress testing platform Pluto. It covers a wide spectrum of use cases: regulatory macroeconomic and climate stress tests as well as bespoke climate analysis, with full projection of regulatory templates, financial statements and selected KPIs/KRIs over chosen time horizons.
Originally designed for financial services Pluto supports organisations across most other sectors. It can also be used to model industry, supply chain and customer exposure providing valuable insights across an organisation’s entire ecosystem. It also can apply an important role in acquisition and investment due diligence.
We believe Pluto is the one of the few tools in the market that allows a fully integrated macroeconomic and climate stress testing. The end-to-end orchestration is fully automated. This includes data ingestion, calling of forecasting and other models, application of business logic, and creation of completed reporting templates. Management actions have been incorporated in the tool as semi-automated business logic. Results are produced both before and after application of management actions. This capability takes contingency planning to another level. Sustainability plans can be fine-tuned easily and made more robust.
The three main technology components of Pluto are:
1. The main tool (named Charon). This is the tool used in a production environment for running stress testing or similar simulations
2. The sandbox (named Styx). This is designed for what-if analysis and for test-running the simulations prior to running them in the production environment. It employs a Jupyter Notebook. This guide explains how to run a simulation in Styx and ad how to modify certain aspects of the simulation, e.g. the business logic rules. It also possible to very easily experiment by substituting one model for another to see the impact on the results. However, this feature is not explained in this guide as it is available only as part of a paid subscription
3. A model executor (named Nix). This allows the execution of models and calculators in any language via the use of Docker containers. These models are an essential part of the forecasting process.
Two libraries are used as shown above: one for the models and one for the business logic rules. These are used by both the main tool and sandbox. The usual inputs and outputs are also shown in the diagram above along with the frontend, a 3rd party analysis and visualization engine (e.g. Power BI or Tableau) and a reporting engine.
Centigo are delighted to partner with Basinghall on this important development. It is one of our key tools in helping clients of all sizes and maturity deal with the complex issue of climate emergency. Basinghall Analytics is a specialist risk and quant advisory firm which help clients focus on key business risks and decisions. Their unique value comes from combining deep domain experience with specialist skills in analytics, risk and technology.
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