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    Home»Financial Technology»Investment Tech Leaders on Data-Driven Decisions
    Financial Technology

    Investment Tech Leaders on Data-Driven Decisions

    FintechFetchBy FintechFetchFebruary 8, 2025No Comments2 Mins Read
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    Scientific Financial Systems’ Founder and Chief Technology Officer Pete Millington sat down recently with Rakesh Reddy, Chief Technology Officer of Kipi.bi, to discuss how technology and data science continue to revolutionize investment management.

    Their recorded Fireside Chat is titled “Decision Making for Investment Management Professionals.” In this chat, Pete and Rakesh delved into the pivotal role technology plays in driving business success within the complex landscape of today’s financial markets.

    To continue delivering outperformance, financial services, companies must now navigate an expanding universe of complex and diverse data sources to develop robust investment strategies. The integration of quantitative methods into financial analytics has further heightened the need for investment firms to innovate as a way to stand out in an ever more competitive market. This innovation need requires the swift and accretive incorporation of new datasets and insights. Investment professionals must swiftly and efficiently move from the initial stages of generating ideas, through testing hypotheses and turning actionable research insights into effective trading strategies.

    Idea generation has becomes a pivotal differentiator for clients of Scientific Financial Systems (SFS). We empower research teams to focus more of their time and energy on these critical activities, enhancing their competitive edge. SFS’ flagship product, Quotient™, was designed and built by a team of highly experienced quantitative investment practitioners and skilled data scientists. Quotient™’s innovative tools offer significant productivity improvements and cutting-edge technological advancements. Quotient™ empowers investment teams to discover novel strategies for gaining a competitive edge by incorporating the latest Machine Learning and AI techniques for getting to alpha faster.

    Quble, SFS’ proprietary Python-based engine inside of Quotient™, provides a major advancement in the concept of “localized compute”. It employs a functional paradigm that simplifies and streamlines algorithms by abstracting logic and operations, further enhancing efficiency and effectiveness.

    Kipi.bi has played a pivotal role in advancing Quotient’s technological capabilities by seamlessly integrating its technology with the Snowflake Data Cloud Platform. Kipi.bi’s deep technical knowledge and expertise have been crucial in the successful migration Quotient™ to the Snowflake platform, ensuring a more efficient, scalable, and robust data analysis solution.

    To learn more, we hope that you hear, enjoy and benefit from the expert insights shared in our recorded Fireside Chat. May this discussion also help you uncover effective strategies and perspectives that guide you through the complexities of today’s investment management and research challenges



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