State Street‘s patent involves an apparatus using machine learning to approximate Net Asset Value for financial portfolios in real-time. The system determines precision based on data captured within a time limit and triggers buy or sell transactions automatically. GlobalData’s report on State Street gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on State Street, Grid computing was a key innovation area identified from patents. State Street's grant share as of February 2024 was 83%. Grant share is based on the ratio of number of grants to total number of patents.
Approximate net asset value calculation for financial portfolios
A recently granted patent (Publication Number: US11875408B2) outlines an innovative apparatus designed to approximate the Net Asset Value of a financial portfolio using machine learning technology. The apparatus includes memory and a processing circuit connected to at least one hardware circuit. This hardware circuit is responsible for training a machine learning model on historical data related to the financial portfolio, determining the weights for data items, and providing real-time approximations of the Net Asset Value based on current data items for a subset of funds within the portfolio. The precision of the approximation is based on the size of the subset of funds captured within a specified time limit, ultimately enabling automated buy or sell transactions in response to requests for the Net Asset Value.
Furthermore, the patent describes a computer-implemented method within a networked environment that mirrors the functionality of the apparatus. It involves training a machine learning model on historical data, processing requests for Net Asset Value, determining precision based on data capture within time limits, and outputting approximations to trigger financial transactions. The method also includes storing information in an immutable log, ensuring data integrity and reliability. The system described in the patent includes an interface for receiving information items, a processing circuit for training the machine learning model, and data storage for maintaining an immutable log of information items. This system is designed to streamline the approximation of Net Asset Value for financial portfolios and facilitate automated trading decisions based on real-time data analysis.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
