Microsoft had three patents in regtech during Q1 2024. Microsoft Corp filed a patent for a computing system that receives input matrices with correlation coefficients, computes closest correlation matrices, generates a training data set, and trains a machine learning model. Another patent relates to securely verifying a user’s identity based on signals transmitted by a client device, involving registering devices via a cloud system, determining trigger conditions, maintaining user verification information, and using biometric scanning for accurate identity verification. GlobalData’s report on Microsoft gives a 360-degree view of the company including its patenting strategy. Buy the report here.
Smarter leaders trust GlobalData
Access deeper industry intelligence
Experience unmatched clarity with a single platform that combines unique data, AI, and human expertise.
Microsoft grant share with regtech as a theme is 33% in Q1 2024. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Computing estimated closest correlation matrices (Patent ID: US20240004953A1)
The patent filed by Microsoft describes a computing system that receives input matrices with estimated correlation coefficients, computes closest correlation matrices using a semidefinite program solver, generates a training data set with these matrices, and trains a machine learning model. The system estimates the closest correlation matrix to be positive definite and uses a least-squares distance measure to determine the closest matrix. It also involves computing a candidate solution matrix that minimizes tr(MX) and includes constraints based on eigenvalues.
The method and system outlined in the patent involve receiving input matrices through a graphical user interface, computing correlation coefficients based on copulas or empirical data, and including marginal distributions in the training data set. The system can handle various types of distributions, such as financial risk or energy source availability distributions. Additionally, there is a method described for displaying the estimated closest correlation matrix at the GUI, allowing users to interact with the results visually. Overall, the patent focuses on a sophisticated computing system for estimating correlation matrices and training machine learning models using semidefinite programming techniques.
To know more about GlobalData’s detailed insights on Microsoft, buy the report here.
Data Insights
From
The gold standard of business intelligence.
Blending expert knowledge with cutting-edge technology, GlobalData’s unrivalled proprietary data will enable you to decode what’s happening in your market. You can make better informed decisions and gain a future-proof advantage over your competitors.
GlobalData, the leading provider of industry intelligence, provided the underlying data, research, and analysis used to produce this article.
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.
