Nervana provides financial institutions a complete solution for deploying deep learning as a core technology. Deep learning is broadly applicable to many financial industry data problems. Nervana’s platform acts as a central hub where state-of-the-art algorithms can be applied across business areas.

Detect Anomalous Data

Deep learning models use a high degree of representational power to capture the complex statistical structure of financial data, often far better than other machine learning methods. They can be used as a powerful tool to detect anomalies in a wide range of settings, including flagging fraudulent credit card transactions, identifying unusual activity in an exchange limit-order book, or predicting sudden regime changes in the securities markets.

Incorporate Exogenous Data

Deep learning models have the unique flexibility to integrate data from disparate sources, such as asset price time series, Twitter volume and sentiment, SEC filing documents, analyst reports, satellite imagery, as well as text, audio, and video news feeds. Nervana can help you greatly augment business decisions by using new, non-traditional sources of data.

Integrate and Optimize to Reduce Cost and Complexity

Financial institutions have sprawling IT infrastructures. Processes are often handled by a large collection of disconnected systems. Deep learning is a powerful generic paradigm for understanding data across these systems. Nervana’s platform acts as central resource for deploying deep reinforcement learning models that can automate complex processes ranging from transaction and settlement to optimal trade execution and automated market making.