Multi-Channel Cognitive Virtual Assistance for Secure Resource Transfers
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Solution Overview
Problem
Existing systems require users to navigate multiple applications and perform redundant actions to execute electronic resource activities, particularly complicating secure resource transfers between accounts managed by separate individuals, such as supervising and dependent users.
Innovation Solution
A multi-channel cognitive virtual assistance system that uses a machine learning engine to analyze resource transfer requests, generate automated notifications, and facilitate secure resource actions between accounts, allowing supervising users to quickly authorize, deny, or edit requests from a single interface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing systems are used for resource transfers, then security can be maintained through multiple verification steps, but user operation complexity increases significantly requiring navigation of multiple applications and redundant actions
Solution Approach 1:
The patent combines multiple separate applications and verification steps into a single integrated interface. The system merges resource request initiation, supervisory approval, and transfer execution into one unified workflow, eliminating the need for users to navigate between multiple applications while maintaining security through integrated verification processes.
Solution Approach 2:
The system creates a universal interface that handles multiple functions within a single application. The platform provides multi-channel communication capabilities, resource request processing, supervisory approval workflows, and transfer execution all through one system, reducing operation complexity while maintaining comprehensive security controls.
2Reliability
If traditional resource transfer systems are used, then account security is protected through manual verification, but time consumption increases due to redundant actions and multiple application navigation
Solution Approach 1:
The system performs preliminary actions by pre-configuring account relationships, transfer limits, and approval workflows before actual resource transfers occur. Supervisors can pre-approve transfer categories and amounts, so when a transfer request is made, the system can quickly validate against pre-set parameters rather than requiring manual verification of each detail, reducing time consumption while maintaining security.
Solution Approach 2:
The system implements automated feedback loops where transfer requests are instantly communicated to supervisors through integrated notifications, and approval decisions are immediately processed and executed. This real-time feedback mechanism eliminates delays associated with manual verification and multiple application switching, significantly reducing time consumption while maintaining account security through automated verification protocols.
3Reliability
If manual resource transfer approval processes are used, then security control is maintained through supervisory review, but productivity decreases due to lack of automation requiring manual analysis and response to each request
Solution Approach 1:
The system enables self-service capabilities where supervisors can configure transfer policies, approval limits, and security parameters in advance. The automated system then handles routine verification and processing of transfer requests according to pre-configured rules, reducing the need for manual analysis of each request while maintaining security control. Only exceptional cases requiring supervisory judgment need manual review.
Solution Approach 2:
The system dynamically adjusts processing parameters based on transfer characteristics. Routine transfers within established parameters are automatically approved by the system, while only transfers exceeding predefined thresholds or parameters require supervisory review. This parameter-based automation significantly increases productivity by handling the majority of requests automatically while maintaining security control through selective human oversight.
Data Source
AI summary
Systems, computer program products, and methods are described herein for multi-channel cognitive virtual assistance for resource transfer requests. The present disclosure is configured to receive a request from a first user device to complete a resource transfer between a first resource account and a second resource account; analyze the request via a machine learning engine and generate an intent based on a communication contained in the request; generate an automated notification based on the generated intent and forward the automated notification to a second user device; receive an approval, denial, or change request in response to the automated notification; based on the approval, denial, or change request, initiate a resource action between the first resource account and the second resource account.