Quotient, Powered by Snowflake, to drive Speed, Scalability, and Performance
Scientific Financial Systems, Inc. (SFS) launches Quotient™ on the Snowflake Data Cloud
BOSTON, March 22, 2023 /PRNewswire/ — Scientific Financial Systems, Inc. (SFS) is pleased to announce the migration of Quotient™, its flagship Advanced Analytical and Data Management application, to the Snowflake Data Cloud. Quotient, Powered by Snowflake, will allow financial companies to take advantage of the robust quantitative analytics tool set with the speed, scalability, and performance of Snowflake’s single, integrated platform.
Quotient enhances the workflow of Quantitative Analysts and Portfolio Managers by simplifying basic tasks, like loading and mapping data across discrete sources, as well as providing simple-to-use tools. This application allows investment team members to focus on their goals of creating and enhancing predictive investment models and discovering new alpha. Quotient now leverages Snowflake’s ability to store data sets in the cloud, at scale, and in their native formats, without requiring complex transformations, thus supporting a broad range of use cases.
Peter Millington, Founder and Chief Technology Officer at SFS, said “We are excited to offer our unique modeling tools, investment analytics, machine learning, and data integration through the powerful Snowflake platform. This combination will allow users to take advantage of Snowflake’s sophisticated architecture and co-locate their computations in the same environment as their data. Quotient, Powered by Snowflake, allows users to leverage the extensive and growing content that is available to users in the Snowflake Data Cloud.”
“Snowflake’s collaboration with Scientific Financial Systems will allow the investment industry to leverage the power of the Snowflake Data Cloud by streamlining data integration across many data sources,” said Matt Glickman, VP Customer Product Strategy, Financial Services, Snowflake. “Additionally, customers can utilize Snowflake’s platform to perform complex investment workflows.”
SFS is a Boston-based FinTech company that builds intuitive financial analysis platforms utilizing Alternative Datasets and Machine Learning. Now Powered by Snowflake, Quotient enhances the effectiveness of the quant workflow by:
- Reducing time spent on mundane, non-proprietary tasks like data loading, mapping, and cleansing, as well as integrating across applications, and disseminating results
- Aggregating data from varied data sources and venues
- Facilitating collaboration and knowledge sharing, and reducing single-person risk
- Offering self-service data requests
- Featuring an Alpha Factor Service that provides over 300 alpha factor signals for market insights and alpha model construction
- Incorporating Python coding interfaces so that quants can write their own sophisticated algorithms
- Allowing quants to focus more on business impactful tasks
Industry-leading applications are Powered by Snowflake. By building on Snowflake, product and engineering teams are able to develop, scale, and operate their applications without operational burden, delivering differentiated products to their customers. With the Powered by Snowflake program, builders get access to resources to help them design, market, and operate their applications in the Data Cloud. To learn more about the Powered by Snowflake program and how organizations are building on Snowflake, click here.
About Scientific Financial Systems (SFS)
Scientific Financial Systems, Inc., a Boston-based financial technology company, developed Quotient™, an advanced analytical and data management tool enabling the institutional investment community (quants) to improve their performance. Quotient’s quantitative portfolio management platform provides an intuitive user interface to a comprehensive Python toolset for utilizing vendor and proprietary data. Spend more time focusing on building models and solving problems with Quotient, now Powered by Snowflake. Learn more at www.scifinsys.com.
SFS Sales & Media Contact:
Kathie McCue
[email protected]