A leading proprietary trading firm specializing in quantitative research, liquidity provision, and financial risk management. The firm maintains a proprietary trading platform, leveraging advanced technology and data analytics to optimize trading strategies across equities, fixed income, and commodities.

The client’s symbology data system faced scalability and accuracy challenges, impacting financial operations. Key issues included:

• Inconsistent data quality checks: Manual, reactive processes led to errors and operational risks.
• Delays and inefficiencies: Synchronous workflows slowed data retrieval and affected performance.
• Integration issues with legacy systems: Modernizing infrastructure without disrupting existing financial applications was a challenge.

These inefficiencies limited scalability, reduced accuracy, and slowed financial decision-making.

Turing implemented a high-performance data solution using automated quality checks, an async Python API, and real-time dashboards to improve data access and reliability.

• Async Python API: Enabled scalable, asynchronous data retrieval, integrating with Solace for reliable messaging and AnyIO for async processing.
• Automated data quality checks: Leveraged SQLAlchemy, Redis, and Snowflake to perform real-time validation and anomaly detection.
• Real-time dashboards: Built with Flask and NiceGUI, providing data visibility and decision-making insights.

• 35% faster data access with optimized async API integration.
• 40% lower data risk through automated quality checks.
• 30% higher developer productivity with streamlined regression testing.
• 25% faster migration to new symbology systems, reducing transition times.