Intercontinental Exchange has patented a method for geographical mapping and linking of security and risk indicator data. The method involves creating cross-references between location indicators and geo-spatial areas, generating credit risk indicators, and forming instrument-level data for securities. The system allows for updating and interactive querying of data. GlobalData’s report on Intercontinental Exchange gives a 360-degree view of the company including its patenting strategy. Buy the report here.
According to GlobalData’s company profile on Intercontinental Exchange, Retail trading platforms was a key innovation area identified from patents. Intercontinental Exchange's grant share as of April 2024 was 67%. Grant share is based on the ratio of number of grants to total number of patents.
Geographical mapping and linking of security and risk indicator data
A recently granted patent (Publication Number: US11961139B2) outlines a method for geographical mapping and linking of disparate data structures for interaction. The method involves obtaining and storing data from various data source systems, including geo-spatial data, security data, and additional data. This data is then filtered and organized into different data tables. Cross-references are created between location indicators and geo-spatial areas based on statistical algorithms, with credit risk indicators generated for each geo-spatial area. The method also involves identifying securities associated with location indicators, creating links between securities, geo-spatial areas, and credit risk indicators, and updating data entries as needed. An interactive graphical user interface is generated to allow users to query the filtered data tables.
Furthermore, the method includes disseminating instrument-level data and credit risk indicator data to dissemination entities such as client devices, external distribution systems, delivery platforms, and external databases. The geo-spatial data used in the method includes demographic, economic, social, and healthcare data, while additional data associated with geo-spatial areas includes population, income, migration, labor, housing, education, and healthcare data. The method also involves continually monitoring data from data source systems in real-time or near real-time, determining scores and rankings for credit risk indicators, storing data in data tables, converting data into a common format, and receiving user input for querying data tables or creating user-customized instrument-level data. The identified securities in the method include municipal securities, and links are created between securities, geo-spatial areas, and credit risk indicators to form instrument-level data.
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