Intelligent Product Requirement Configurator for Regulatory Compliance
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Solution Overview
Problem
Enterprise solution tools face significant challenges in setting up or updating configuration settings to comply with evolving government regulations and industry standards, requiring extensive manual effort and time, especially in dynamic industries like banking.
Innovation Solution
The Intelligent Product Requirement Configurator (iPROC) tool utilizes a cognitive recommendation engine based on neural networks and deep learning to analyze changes and generate recommended configuration settings, ensuring compliance with industry regulations and standards by creating a unique data set that can be directly implemented on various application platforms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual configuration settings are performed to comply with government regulations and industry standards, then configuration accuracy can be ensured, but the time required and manual effort increase significantly
Solution Approach 1:
The patent replaces manual mechanical configuration processes with an automated cognitive recommendation engine that uses neural networks and deep learning. The system automatically analyzes regulatory changes, determines recommended configuration settings, and generates implementation data sets, eliminating the need for manual research and configuration while maintaining high accuracy through AI-driven analysis.
Solution Approach 2:
The system enables self-service configuration by automatically detecting regulatory changes, analyzing their impact on enterprise solution tools, and generating recommended configuration settings without human intervention. The cognitive engine independently performs the entire configuration process from regulatory monitoring to implementation data set generation.
2Reliability
If comprehensive regulatory analysis is performed to determine recommended configuration settings, then compliance accuracy improves, but the complexity of the system increases
Solution Approach 1:
The patent introduces a cognitive recommendation engine as an intermediary between regulatory requirements and enterprise solution tool configurations. This AI-based mediator automatically analyzes regulatory changes, interprets their implications, and translates them into recommended configuration settings, simplifying the overall system architecture while ensuring comprehensive compliance analysis.
Solution Approach 2:
The system changes the parameters of the configuration process by using neural networks and deep learning models to automatically analyze regulatory parameters and generate configuration recommendations. This transforms the complex manual analysis process into an automated parameter-driven system that maintains high compliance accuracy.
3Adaptability or versatility
If frequent configuration updates are performed to adapt to evolving regulations, then adaptability improves, but the loss of time and resources increases
Solution Approach 1:
The patent implements preliminary action by continuously monitoring regulatory changes and pre-analyzing their impact on enterprise solution tools. The cognitive recommendation engine prepares recommended configuration settings in advance, so when regulatory changes occur, the system can quickly generate implementation data sets without requiring time-consuming manual analysis, thus improving adaptability while reducing implementation time.
Data Source
AI summary
An intelligent product requirement configurator is a tool for assisting the implementation process of application platforms by generating a recommended configuration data set describing recommended configuration settings for a selected application platform. The tool acts as a repository for capturing requirements such as banking market practice requirements, regulatory requirements, and bank specific requirements. The tool further converts the requirements into profile data and business rules that are used to configure the application platform.