17985420. Trigger-Based Electronic Fund Transfers simplified abstract (Bank of America Corporation)
Contents
- 1 Trigger-Based Electronic Fund Transfers
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 Trigger-Based Electronic Fund Transfers - 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 Original Abstract Submitted
Trigger-Based Electronic Fund Transfers
Organization Name
Inventor(s)
Lalit Dhawan of Franklin Park NJ (US)
Trigger-Based Electronic Fund Transfers - A simplified explanation of the abstract
This abstract first appeared for US patent application 17985420 titled 'Trigger-Based Electronic Fund Transfers
Simplified Explanation
The abstract describes systems, devices, and methods for machine learning based processing of large transactions, such as business-to-business fund transfers. A transaction management platform incrementally processes payment transactions based on trigger points derived from analysis of transaction history associated with a source account.
- Machine learning based processing of large transactions
- Incremental processing of payment transactions
- Trigger points based on transaction history analysis
Potential Applications
The technology described in this patent application could be applied in various industries and sectors, including:
- Financial services
- E-commerce platforms
- Supply chain management
Problems Solved
The technology addresses several challenges in processing large transactions, such as:
- Ensuring accuracy and efficiency in fund transfers
- Managing complex business-to-business transactions
- Analyzing transaction history for decision-making
Benefits
The use of machine learning for processing large transactions offers several benefits, including:
- Improved transaction accuracy
- Enhanced efficiency in fund transfers
- Better decision-making based on transaction history analysis
Potential Commercial Applications
The technology has potential commercial applications in industries that deal with large transactions, such as:
- Banking and financial services
- Payment processing companies
- Enterprise resource planning systems
Possible Prior Art
One possible prior art for this technology could be traditional transaction processing systems that do not utilize machine learning for analyzing transaction history and processing large transactions.
Unanswered Questions
How does this technology ensure data security in large transactions?
The article does not delve into the specific security measures implemented to protect data during the processing of large transactions.
What are the scalability limitations of this technology in handling a high volume of transactions?
The article does not address the scalability limitations of the technology when processing a large number of transactions simultaneously.
Original Abstract Submitted
Systems, devices, and methods for machine learning based processing of large transactions (e.g., business-to-business (B2B) fund transfers) is described. A transaction management platform may incrementally process a payment transaction based on one or more trigger points. The one or more trigger points may be based on analysis of a transaction history associated with a source account of the transaction.
