Institution Computing System for Payment Schedule Optimization
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Solution Overview
Problem
Businesses face inefficiencies and increased costs due to fragmented software platforms for managing operations, requiring users to navigate between disparate systems like ERP and CRM applications, leading to cumbersome data exchange and reduced productivity.
Innovation Solution
An institution computing system (ICS) facilitates connections between enterprise resources and APIs, enabling real-time data exchange and integration, using machine learning models to optimize payment schedules and generate interactive graphical user interfaces for seamless data management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If businesses use multiple fragmented software platforms (ERP, CRM, third-party platforms) to manage different business processes, then functional versatility and coverage are improved, but device complexity and ease of operation deteriorate due to difficulty in moving between platforms and cumbersome data exchange
Solution Approach 1:
The patent introduces an intermediary computing system that acts as a mediator between multiple fragmented software platforms (ERP, CRM, third-party platforms). This intermediary system provides unified access points and data exchange interfaces, allowing businesses to interact with different platforms through a single consolidated system rather than navigating between multiple disparate platforms directly.
Solution Approach 2:
The computing system is designed with universal functionality to access and integrate data from multiple different software platforms simultaneously. It provides multi-functional capabilities including financial data access, payment processing, schedule management, and communication with various external systems through standardized interfaces, eliminating the need for separate specialized systems for each function.
2Adaptability or versatility
If businesses navigate between multiple fragmented platforms to manage operations, then access to specialized functionality is improved, but loss of time and productivity deteriorate due to increased time required for data exchange and platform transitions
Solution Approach 1:
The system performs preliminary actions by pre-establishing connections and data exchange protocols with multiple platforms before they are needed. It maintains pre-fetched data, pre-configured interfaces, and anticipates data requirements so that when users need information from different platforms, the data is already prepared and accessible immediately without requiring time-consuming real-time queries.
Solution Approach 2:
The computing system ensures continuous availability of data and functionality by maintaining persistent connections with multiple platforms and continuously synchronizing data. Rather than requiring intermittent manual data extraction and exchange between platforms, the system maintains ongoing data flows and real-time updates, eliminating interruptions and delays in accessing information across different systems.
3Ease of operation
If manual payment schedule management is used, then simplicity of operation is maintained, but productivity and efficiency deteriorate due to time-consuming manual processes and lack of optimization
Solution Approach 1:
The system implements self-service capabilities that automatically manage payment schedules without requiring manual intervention. It autonomously processes payment data extraction, optimization calculation, schedule generation, and reminder notifications. The system monitors account balances, predicts cash flow needs, and automatically adjusts payment timing to optimize cash management while maintaining ease of use through automated decision-making.
Solution Approach 2:
The system continuously monitors payment status, account balances, and cash flow conditions, providing real-time feedback to optimize payment schedules dynamically. It analyzes actual payment performance and adjusts future scheduling decisions based on observed patterns, improving efficiency over time while presenting simplified user interfaces that show users only the necessary information and actions required.
Data Source
AI summary
Systems and methods method include establishing, a connection between the first computing system and an application of a second computing system, the connection associated with an entity having one or more first accounts with the first computing system and a second account with the application of the second computing system, receiving a dataset corresponding to the second account, the dataset comprising a plurality of data entries corresponding to respective invoices, retrieving account data corresponding to the one or more first accounts with the first computing system, applying, the dataset and the account data as inputs to a machine learning model trained to generate optimized orders, and generating, by the one or more processors, a first user interface including data of a list of the plurality of entries, the plurality of entries being ordered according to the optimized order for the dataset.