Capital Markets
Capital markets are changing due to technological innovation, event-driven shocks and broader macroeconomic forces. But current machine learning systems falsely assume that the future will be very similar to the past.
Causal AI finds the real drivers of capital markets, enabling industry players to discover market structures, unlock value and solve their biggest challenges.
Current challenges in capital markets are well known
Investors demand lower fees and greater explainability from discretionary managers, while systematic funds must constantly extract new signals from an ocean of marginally-useful data. Banks find their models frequently upended by regulations, geopolitics, or regime changes.
Artificial Intelligence and Machine Learning techniques can provide solutions to these and other problems. But current approaches fail to unlock the true potential of AI for Capital Markets:
- Non-causal ML techniques based on pairwise relationships will necessarily overfit to the past
- Existing platforms offer limited insights beyond simple predictions based on past patterns
- They are not truly explainable, and are often perceived as a “black boxes”
- They fail to translate predictions and models into optimized business outcomes
causaLens is the only AI technology that can unlock true value in Capital Markets.
Solutions
Unlock the hidden drivers within your business with causaLens. Standard techniques are overwhelmed by the many correlated data sources in a large organization; only Causal AI can cut through the noise and discover meaningful opportunities for efficiency.
Our causal discovery methods can identify the true causal drivers of exposure for a portfolio, rather than focusing on spurious correlations. Using causalNet, we can generate realistic scenarios that capture fundamental regime shifts during periods of market stress while also remaining intuitive and explicable.
Macroeconomic data can often tell a lot about what happened yesterday. causaLens allows you to provide causal explanations of tomorrow, merging different sources of data to create dynamic models of the world economy and uncovering the true structure behind global macroeconomic variables.
In today’s market, having the right data is a key to success. Evaluating the quality of data is nonetheless a challenging task. With causaLens this task is made easier with our proprietary dataset evaluator: benchmark the candidate data against public datasets and quantify the impact of the data on your KPIs, while avoiding the spurious correlations in all large datasets.
Why causaLens
Which level is your organisation in?
No Machine Learning
- Do you think it would take you years to become an AI-driven Enterprise?
- Is the value of your enterprise’s data asset largely unrealised?
- Are the predictions, insights and business decisions compromised due to human error?
- Are resources wasted improvising solutions to problems that could be better solved with ML?
Manual Machine Learning
- Is it hard to build and retain Quant teams?
- Does it take months or years to achieve real business impact?
- Is the team mostly reactive, responding to requests from business functions for analytics?
- Does your team spend their time implementing repetitive & expensive processes?
Automated Machine Learning
- Do you find that generic Data Science Platforms overfit & underperform in Capital Markets?
- Do you have trouble translating predictive models & predictions to real value for the business?
- Are generic platforms not flexible or transparent enough while failing to incorporate your domain expertise?
Reach the top levels of Enterprise AI for Capital Markets
Causal AI
- Goes beyond modelling correlations in historical data and understands true causal drivers
- Autonomous, from raw data directly to causal signals, predictive models & insights
- Inherently explainable
- Adaptable and works in regime shifts
- Intuitively incorporate domain expertise
- Works in low-signal-to-noise environments
Strategy Optimization AI
- Automated KPI Optimization.
- Includes all benefits of Automated Causal AI.
- Goes beyond predictive models and integrates the business context and the domain knowledge in a meaningful way.
Systematic Trading
Causal AI examines entire dynamic systems to understand the true causal relationships that drive change – relationships that cannot be found with correlation-based techniques. These new angles can be employed in signals research, execution and risk management to create investment opportunities that persist and are robust to unexpected regime changes.
causaLens combines up-to-date academic methods with proprietary R&D from a leading causality research lab. The platform fits easily into existing pipelines, allowing systematic investors to move ahead of existing approaches by applying causal techniques across the business.
High Frequency Trading & Market Making
causaLens can be integrated directly into any pipeline to optimise high-frequency trading strategies, trade execution, and market making. Designed for high-throughput online time series prediction, our models continuously adapt in real time to discover the current causal drivers in the market and produce the most efficient execution.
Data Search & Building New Products
causaLens empowers exchanges, data sourcing teams & data vendors to autonomously discover value in time-series data. Standard AI techniques are confused by large amounts of intercorrelated and mismatched data; only Causal AI allows users to extract valuable signals and build exciting data products that are easily monetized.
Learn how CLS Group is using causaLens to uncover insights in the FX markets
Download the CLS Data Insights report today
