Introducing the 4-Xtra Platform
Building upon initial academic work in the theory and predictability of extreme events, and utilising innovative machine learning and artificial intelligence methods, 4-Xtra has developed an extreme event forecasting risk modelling solution and a complementary synthetic data generator for the increasingly complex world of the financial markets and beyond. Data and signals can be easily output through the web-based user interface, or delivered through our API for integration into your own systems as required.
SaaS based, machine learning risk management platform that is capable of accurately predicting the likelihood of a multi-variate extreme event occurring, together with the associated magnitude of that predicted event using nonstationary time-series data.
The platform allows for any number of adaptable business configurations to be overlaid to manage specific industry risks and produces outstanding results, 6-7 times more accurate and faster than classical risk models based on stationary data.
Leveraging different data sources as inputs such as text, images, tabular and time-series data, the engine can efficiently extract extreme value information from the underlying inputs and make future predictions about upcoming extreme events.
Applicability of the 4-Xtra Extreme Forecasting Engine is extremely wide ranging in financial services alone, with proven use cases such as:
Trading – Forecasting individual stocks, indexes, alternative assets and currency movements
Portfolio Management – Optimisation and improved performance
Lending – Forecasting events to enhance and improve credit decision making and repayment delinquency rates
Insurance – Predicting probability of claims to enhance risk pricing
Based on a user-uploaded tabular (time-series) dataset (either through our user interface or an API call), the 4-Xtra Synthetic Data Generator is able to generate completely synthetic data that effectively preserves the statistical properties of the original dataset ensuring that data privacy and utility of the synthetic data are maximized.
Furthermore, leveraging the 4-Xtra EV engine within the SDG, the generator can efficiently, on-demand generate extreme samples of the data that go far beyond what was observed in the original dataset. This empowers users to efficiently manage risk by simulating and exploring extreme samples of data that would usually require years to collect.
Applicability of our synthetic data generator to financial services is vast and can be used in a variety of cases, for example where:
Data is required for testing purposes but is scarce or lacking
Data privacy is required
Regulatory constraints exist on the utilisation of data (location, anonymity requirements) The risk characteristics of an investment portfolio, trading strategy, require testing without criticism of over-fitting models to historical data
Scenario analysis can be performed – data sets can be constructed to test trading models performance against extreme events
Insurance pricing models can be optimised
Who we are
The leadership Team of 4-Xtra Technologies
Our team is composed of seasoned experts in their respective fields.
Learn more about their individual contributions and their collective efforts in making this innovative breakthrough possible.
Principle data scientist
Co-inventor and academic lead