LSEG has partnered with Databricks to offer its data directly in Databricks via Delta Sharing, launching with Lipper fund data & analytics and cross asset analytics.
Additional data includes pricing, reference data, models, fundamentals, estimates, economics, and tick history to follow, expanding the range of AI-ready data available. With the solution, customers can build and deploy AI agents on their enterprise data and LSEG’s data faster for real-time investment analytics, risk management, and trading workflows using Databricks Agent Bricks.
Unified data for financial intelligence
Financial firms face challenges when it comes to keeping pace with dynamic markets due to outdated and manual data delivery that can be costly and slow. Analysts spend more time integrating data than building the models needed to respond to fast-changing market conditions. The two companies want to tackle these challenges by allowing enterprises to unify financial data to power analytics, AI apps, and agents. The partnership helps with portfolio, risk management, forecasting, and client reporting, enabling teams to make smarter decisions, make developments faster, and remain competitive. All datasets will be discoverable on Databricks Marketplace via Delta Sharing, Databricks' open-source approach for securely sharing live data and AI assets across platforms.
Use cases of the alliance include investment analytics, trade analytics, and risk management. The companies drive market intelligence, back testing, and portfolio optimisation to provide better AI-powered strategies, enabling real-time market analysis, TCA, predictive forecasting, and algorithmic trading to improve intraday decision-making. Additionally, it unifies and strengthens market, credit and counterparty risk oversight by enabling AI-driven surveillance, exposure monitoring and real-time compliance across the front-to-back office.
Using Agent Bricks on Databricks, teams can combine raw tick history or reference data with their enterprise data to launch production agents that come with built-in, auto-optimised accuracy, governance, and cost efficiency. Global banks can use Agent Bricks to combine transaction and client data with market and reference data, run scenario forecasts, find investment opportunities and portfolio risks, detect anomalous trading, and auto-generate compliance reports in real time.
