17972637. TRANSACTION CLASSIFYING simplified abstract (Bank of America Corporation)
Contents
TRANSACTION CLASSIFYING
Organization Name
Inventor(s)
Krishna Reddy Mandala of Hyderabad Telangana (IN)
Ananya Bhattacharyya of Gurugram Haryana (IN)
Ashutosh Misra of Gurugram Haryana (IN)
Marc Halsted of Charlotte NC (US)
David Joa of San Francisco CA (US)
TRANSACTION CLASSIFYING - A simplified explanation of the abstract
This abstract first appeared for US patent application 17972637 titled 'TRANSACTION CLASSIFYING
The abstract describes an apparatus and methods for intelligently classifying unclassified transactions. The program receives transaction data, divides it into a training set of classified transactions and a test set of unclassified transactions, and generates a document term matrix to analyze the data.
- The program compares the analyzed terms from the test set to the document term matrix to predict a classification for the unclassified transactions.
- It iterates to a pre-determined level of confidence in the prediction and assigns a classification to each transaction based on the analysis.
Potential Applications: - Financial institutions can use this technology to classify transactions accurately and efficiently. - E-commerce platforms can benefit from automated transaction classification for fraud detection and customer profiling.
Problems Solved: - Streamlines the process of classifying transactions, reducing manual effort and potential errors. - Enhances the accuracy of transaction classification, leading to improved decision-making in various industries.
Benefits: - Increased efficiency in transaction classification processes. - Improved accuracy in predicting transaction classifications. - Enhanced fraud detection capabilities for financial institutions.
Commercial Applications: Title: Automated Transaction Classification Technology for Enhanced Efficiency in Financial and E-commerce Sectors This technology can be utilized by banks, payment processors, and e-commerce platforms to automate transaction classification, improve fraud detection, and enhance customer profiling.
Questions about the technology: 1. How does this technology improve the accuracy of transaction classification? - This technology uses a document term matrix to analyze transaction data and predict classifications with a high level of confidence. 2. What are the potential benefits of using automated transaction classification in the financial industry? - Automated transaction classification can streamline processes, reduce errors, and improve fraud detection in financial institutions.
Original Abstract Submitted
Apparatus and methods for intelligently classifying unclassified transactions are provided. A program may receive a set of transaction data. The program may divide the set into a training set of classified transactions and a test set of unclassified transactions. The program may analyze the training set to generate a document term matrix. The program may analyze the test set and compare the analyzed terms to the document term matrix to predict a classification. The program may iterate to a pre-determined level of confidence in the prediction and assign a classification to a particular transaction.
