AI Account Report Generation for Real-Time Cash Risk Analysis
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Solution Overview
Problem
Administrators face challenges in timely analyzing and acting on data related to computing systems, risking exposure due to inadequate real-time data analysis capabilities.
Innovation Solution
Utilizing artificial intelligence and machine-learning models to capture historical account data, extract item-level features, and generate client account reports based on identified patterns and user preferences, enabling automated decision-making for improved visibility and management of cash and risk.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If administrators manually analyze data related to computing systems, then they can take actions based on the data, but they face challenges in timely analysis and risk exposure due to inability to act in real-time
Solution Approach 1:
The patent replaces manual administrative analysis with an automated machine learning system that processes account data, extracts features, generates reports, and provides recommendations without human intervention, thereby eliminating time loss and enabling real-time decision-making
Solution Approach 2:
The system enables self-service by automatically capturing historical account data, extracting item-level features, generating client account reports, and providing actionable recommendations without requiring administrator effort, thus achieving both speed and reliability
2Productivity
If automated machine learning systems are used for report generation, then productivity and real-time analysis are improved, but device complexity increases
Solution Approach 1:
The patent segments the report generation process into distinct modular components: data capture module, feature extraction module, report generation module, and recommendation module. Each module handles a specific task, improving productivity while managing complexity through clear separation of concerns
Solution Approach 2:
The machine learning model serves multiple functions: it captures historical account data, extracts item-level features, generates client account reports, and provides actionable recommendations. This multi-functionality improves productivity without proportionally increasing complexity
Data Source
AI summary
A method for report generation may include capturing a plurality of historical account data of a client account. The method may further include extracting a plurality of item level features from the plurality of historical account data. The method may further include providing the plurality of item level features and a set of user preferences to a natural language machine-learning model. The natural language machine-learning model may be trained to identify patterns within the plurality of item level features and generate one or more client account reports based on the identified patterns and the set of user preferences. The method may further include transmitting, to a user interface, the one or more client account reports.