Trading and Investing division’s Tenor platform combines advanced AI with end-to-end insights and extensive datasets
SymphonyAI, a leader in predictive and generative AI SaaS products for the enterprise, today announced entry into the trading and investing market with a division focused on bringing insights and analysis from predictive and generative AI capabilities to global financial markets.
The SymphonyAI Trading and Investing division’s Tenor platform will combine new advanced AI capabilities, powered by SymphonyAI’s award-winning Eureka Gen AI platform, with decision science, data management, and data analytics technology from its acquisition of 1010data that leading financial institutions have trusted to simplify trading, research, valuation, and risk modeling workflows for more than 20 years.
“The impact of artificial intelligence on the future of financial markets can’t be overstated,” said Head of Market Structure and Technology Research Kevin McPartland at Coalition Greenwich, a leading global provider of strategic benchmarking, analytics, and insights to the financial services industry. “Applying predictive and generative AI to the ever-expanding universe of fixed income data is crucial to long term improvements in market liquidity, execution quality and investment returns.”
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“The need for rapid, deeply informed decision-making in an increasingly complex financial market is more essential than ever, and AI-based capabilities are imperative to successfully navigating the trading and investing landscape,” said Adam Quinones, president of the SymphonyAI Trading and Investing division. “The SymphonyAI Tenor product portfolio has exciting, aggressive new AI innovations built on 20 years of collaborating closely with customers to meet their unique needs and use cases. With great customers, great data, and great technology, we are incredibly excited about the market opportunity for our expanded portfolio.”
The SymphonyAI Tenor platform provides ad hoc analytics capable of flexible and fast data manipulation across billions of rows of data, customizable to specific customer requirements. The modularized solution automates orchestration and integration of disparate datasets and seamlessly connects it to proprietary data science tools to provide turnkey solutions for housing finance, consumer credit, and macroeconomic modeling workflows.
Predictive and generative AI capabilities include a sentiment engine and a behavioral simulator. The sentiment engine automates collection, transformation, and analysis of curated datasets, news, research, and sentiment. This can, for example, be used to interpret the sentiment of specific Federal Reserve officials and prominent industry analysts to better predict decisions impacting interest rates. By removing guesswork from interpreting Federal Reserve communications and expert research views, the SymphonyAI models democratize insight generation by identifying when markets have disconnected from true macroeconomic reality to make investment decisions more robust and accurate.
The behavioral simulator uses predictive AI to model complex real-world economic interactions at a highly granular geographic level and accurately predicts mortgage lending and consumer credit trends with predictive AI. Users gain expert trained modeling capabilities and AI-generated forecasts of household-level credit performance and the likelihood that borrowers will seek a new loan, with the ability to select from multiple modeling frameworks and variables.
SymphonyAI has also expanded the data available to its trading and investing customers, including 20 years of consumer credit data from Experian loan and security-level residential and commercial mortgage data, as well as bank call report data from Recursion to provide more granular automated insights into hidden risks embedded in consumer credit investment products. With more comprehensive, current data sources, SymphonyAI predictive AI models generate more complete and accurate predictions and recommendations.
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