Better Data Science,
Better Investment Decisions

Scientific Financial Systems is a Boston based FinTech company that builds intuitive financial analysis platforms utilizing Alternative Datasets and Machine Learning.

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.

“Quotient™ will unlock significant efficiency gains for our business, one of the most sophisticated index development platforms available today… We will use Quotient to rapidly source, transform and aggregate point-in-time factors across a broad range of sectors and regions.”

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

Peter Millington Attends the Snowflake Data for Breakfast

Peter Millington Attends the Snowflake Data for Breakfast

In today’s fast-paced business environment, data is more valuable than ever. Companies are looking for ways to extract meaningful insights from their data to gain a competitive edge. To do so, they need a robust data warehousing solution that can support their data...

It All Started with a Quble

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...

“We appreciate all the hard work that SFS has put into developing Quotient™. We believe that Quotient™ offers a nice suite of tools that complements Refinitiv Quantitative Analytics.”
Juan Zamudio, Quant and Feeds Partnerships Manager, Refinitiv

Accelerate your research

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Discover the future of financial data analysis

Watch a free demonstration of Quotient™, our flagship financial data analysis product.