Better Data Science,
Better Investment Decisions


Enterprise Solution
Quotient™, Scientific Financial Systems’ flagship product, provides an enterprise solution for investment managers that provides a data driven view of investment opportunities and strategies, along with more control and greater flexibility.

Rapid Analysis
Quotient™ enables financial institutions to analyze rapidly large amounts of data and provide data-driven results and recommendations.

Trusted Data
Quotient™ partners with and integrates with some of the largest global financial data providers and provides an advanced analytical engine for data manipulation, factor building, back-testing and portfolio construction.
Simon Whitten, Director of Research at Syntax Indices
Implementing Scientific Financial’s Quotient™ will provide your Firm with Significant Economic Benefits:

Improve Research Team Effectiveness
We all know that the best research teams have high levels of collaboration to help reduce risk. Quotient™ was designed to allow your team to share the same platform to promote transparency and standardization of formulas and approaches.
- Users share a common research platform
- Promotes Collaboration
- Reduces Single Person Risk
- Makes Transparency and Standardization of Formulas easy
More time on research and developing quantitative models
Spend less time developing your research architecture and more time on generating research output and actionable quantitative models. Use a solution built by practitioners with a track record of success.
- End-to-end research workflow
- Define derived data items
- Build screens and multi-level models
- Extensively backtest and forecast using advanced machine learning techniques to enhance alpha
- Leverage factor examples and tutorials to get users working quickly
Effectively Integrate Vendor and Internal data source
Newly acquired data sources can be quickly integrated and ready for use. Vendor and platform agnostic data sourcing allows seamless integration into models.
- Supports sql, cloud sources such as snowflake, csv files, excel and more
- Data standardized for frequency, currency, and corporate actions
- Data presented in an organized and self-documented manner
- Supports point-in-time data sources for improved predictive power
Latest Articles & Insights
It All Started with a Quble
In our last SFS blog, we talked about how the technical challenges in the performance and scaling of our Quotient architecture were solved through the integration of our backend with Snowflake’s Snowpark for Python. We called Snowpark a “game changer” for developers...
Houston, We Had a Problem
Scientific Financial Systems (SFS) knew that in Quotient™ we developed a powerful and flexible Python-based data science SaaS application that could improve the effectiveness of quant finance teams. Our careers in Quant research and fund management led us to...
Differentiate Your Next Investment Study
Get Started with Quotient’s Screener Builder Module Tutorial
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Discover the future of financial data analysis
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