The world’s first causal AI platform, created by deep-tech scaleup causaLens, is being leveraged by financial services companies (including Aviva Investors, 2IQ, TIAA, CLS Group and a plethora of prominent hedge funds), to automatically extract valuable causal insights from financial data and therefore boost the profitability of their trading strategies. The technology understands and explains the causal drivers of capital markets, rapidly adjusts to new market conditions, and uniquely is able to deploy counterfactual modelling tools to manage portfolio risk.
The success of the financial services industry relies on understanding the true drivers of dynamic markets, but current AI systems can only identify correlations. These ‘curve-fitting’ machines, which rely solely on historical data to predict the future, fail as the world inevitably changes. They are not scalable, require expensive and hard-to-hire teams of data scientists, offer limited explainability and ultimately do not work well for financial markets.
causaLens’ Causal AI platform, launched in stealth-mode during 2020, addresses these challenges. Causal AI is a completely new kind of machine learning (ML), which brings us one step closer to truly intelligent machines. Causal AI can understand cause and effect, intuitively incorporate human knowledge, design optimal interventions and imagine counterfactual scenarios – all of which help drive strategy and decision making. Furthermore, it displays superior performance on conventional prediction tasks, having been proven to adapt three times quicker to new market conditions than current machine learning technology.
Michael Grady, Head of Investment Strategy and Chief Economist at Aviva Investors explains the asset management company’s work with causaLens: “Causal AI plays an ever more important role in our investment analysis. It empowers our strategists and portfolio managers to generate alpha by identifying new causal relationships in economic, financial and alternative data, with sophisticated, adaptive and explainable models that don’t suffer from overfitting.”
Another example of the value of Causal AI is causaLens’ work with CLS Group, a specialist US financial institution that provides settlement services in the foreign exchange market. Applying causaLens’ technology to its own FX Spot volume data – which consists of over 1 billion trades across 18 currencies – CLS has studied the changing macro patterns in the world’s major currencies through the pandemic and Brexit. These findings can be used by CFOs and treasurers to enhance their hedging strategies.
Masami Johnston, Head of Information Services at CLS Group explained: “Causal AI enables us to identify significant and unexpected changes in key factors associated with the FX markets, enabling quick reactions to market conditions and enhancing investing strategies.”
Darko Matovski, CEO and Co-Founder of causaLens commented,
“We pioneered automated machine learning (AutoML) for time-series data in 2017 and brought immense value to our clients in terms of performance and cost savings. We are proud to have now brought the next level of intelligence to the market. Causal AI offers superior performance and explainability. Counterfactual and interventional reasoning, unique features of Causal AI, allow our clients to reach a higher level of automation and intelligence than was previously possible, leading to superior ROI. We have also extended our offering beyond time-series data.”
Alongside financial services, causaLens also works with organisations in industries including energy, healthcare, transport and logistics to enable advanced diagnostics, efficient resource allocation, significant cost savings and pricing strategy optimisation.
Further use cases, white papers and demonstrations of Causal AI can be found on this website, an invaluable resource for all organisations seeking to unlock the value from AI and their data.
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