Fintech

The Climate Capital Platform combines both public domain data, and private client protected data, which together are used for quantity and price forecasting and economic analysis and decision making in three sectors - environmental markets, energy markets and event futures. As well as standard DCF analysis we utilise the following risk analysis and management methodologies:

  • purpose built very large database time series econometric methods to analyse daily, monthly and longer term trends and relationships

  • purpose built project and asset tracking spreadsheet

  • Monte Carlo simulation to capture probabilities of different scenarios - daily, monthly and longer term.

  • AI to scrape and analyse very short term exogenous shocks which impact energy assets & liabilities and the environment both locally in the form of very short term events and very long term in the case of global climate change impacts

  • Real Options analysis to explore different timings of capital allocation to projects into an uncertain future

  • DLT Smart Contracts to trustlessly manage, verify  and report asset (and liability) value and exposure

  • providing users with access to curated information and data on:

    emissions volumes

    carbon and energy prices and price forecasts

    reporting data

    allows public sector users to improve policy making and private sector users to enhance capital allocation and investment performance. Data driven insights generate greater opportunities for revenue generation and higher trading profits.

  • 1. Regression forecasting on very large databases to analyse effects of multiple variable inputs

    2. Monte Carlo Simulation to capture probability estimates and graphical presentation of outputs

    3. AI methodologies using a unique system whereby each run of our algorithm runs several possible AI methodologies on real time data to analyse which one or more AI techniques is performing best in real time

    4. Real Options Analysis to permit better structuring of capital allocation over a sustained timeframe into an uncertain future

    These techniques allow both public and private sector users to improve their decision making, budget and capital allocation and optimise timing and risk both in projects and spend in the face of uncertainty.

    Our suite of algorithms permits users to forecast emissions costs in the form of tradeable carbon credit prices from day ahead to multi-day cumulative over ten days, to multi-month up to several years ahead. This facilitates enhanced economic analysis, and short up to long term decision making, and so better capital allocation by users.

    User defined tailor made forecasts are also available for energy and broad commodity prices.

  • allows highly-secure sharing and combining of data ▪ fully under user control

    This provides users with the flexibility and power of advanced large scale data analytics combing curated big data public domain information with their own private data, whilst keeping their own data, segregated, confidential and secure.

    ▪ Users of our price forecasting algorithms with DLT processing in combination with our 4 fintech tools can achieve very significantly higher financial returns whilst fully maintaining data security and trading integrity

    ▪ Project developers can secure additional sources of finance through regulated Asset Backed Tokenisation