Oracle international corporation (20240127240). TOUCHLESS EXPENSES WITH REAL-TIME CARD CHARGES simplified abstract
Contents
- 1 TOUCHLESS EXPENSES WITH REAL-TIME CARD CHARGES
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 TOUCHLESS EXPENSES WITH REAL-TIME CARD CHARGES - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 How does the expense report generation system handle data privacy and security concerns?
- 1.11 What is the scalability of the expense report generation system for large organizations with high transaction volumes?
- 1.12 Original Abstract Submitted
TOUCHLESS EXPENSES WITH REAL-TIME CARD CHARGES
Organization Name
oracle international corporation
Inventor(s)
Dawn Abraham of Foster City CA (US)
Rondy C. Ng of Redwood Shores CA (US)
TOUCHLESS EXPENSES WITH REAL-TIME CARD CHARGES - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240127240 titled 'TOUCHLESS EXPENSES WITH REAL-TIME CARD CHARGES
Simplified Explanation
The expense report generation system described in the patent application receives transaction authorization data from a card issuer and compares it with expense report generation criteria to determine whether to generate an expense report before the transaction is settled. The system evaluates additional data from various sources, including contextual information of the employee, transaction authorization, location, and other employees, to generate the expense report. It updates the report based on updated transaction authorization data and/or settlement data, and utilizes a machine learning model for efficiency and accuracy in generating expense reports while reducing manual input and approval process burdens for employees.
- The expense report generation system receives transaction authorization data from a card issuer.
- It compares the data with expense report generation criteria to determine whether to generate an expense report.
- The system evaluates additional data from various sources to generate the expense report.
- It updates the report based on updated transaction authorization data and/or settlement data.
- The system uses a machine learning model for efficiency and accuracy in generating expense reports.
Potential Applications
The technology described in this patent application could be applied in various industries where expense reporting is required, such as finance, travel, and business management.
Problems Solved
This technology solves the problem of manual input and approval process burdens for employees when generating expense reports. It also improves efficiency and accuracy in expense report generation.
Benefits
The benefits of this technology include reducing the time and effort required to generate expense reports, improving accuracy through machine learning, and streamlining the approval process for expenses.
Potential Commercial Applications
One potential commercial application of this technology could be in expense management software for businesses, offering a more automated and efficient solution for generating expense reports.
Possible Prior Art
Prior art in this field may include existing expense management software that automates certain aspects of expense reporting but may not utilize machine learning for improved efficiency and accuracy.
Unanswered Questions
How does the expense report generation system handle data privacy and security concerns?
The patent application does not provide details on how the system addresses data privacy and security issues related to handling sensitive transaction authorization data.
What is the scalability of the expense report generation system for large organizations with high transaction volumes?
The patent application does not discuss the scalability of the system for organizations with a large number of transactions that require expense reporting.
Original Abstract Submitted
an expense report generation system receives transaction authorization data from a card issuer and compares the data with expense report generation criteria to determine whether to generate an expense report, prior to settlement of the transaction, based on the authorization data. the expense report generation system evaluates additional data obtained from other data sources including contextual information of the employee, transaction authorization, location, and other employees to generate the expense report. the expense report generation system subsequently updates the generated expense report based on updated transaction authorization data and/or transaction settlement data. the expense report generation system trains and uses a machine learning model for efficiency and accuracy in generating expense reports from transaction authorization data while reducing an employee's burden in manually inputting expense information and the approval process burden.
