AI Data Transformation for Automated Form 990 Completion
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Solution Overview
Problem
Non-profit organizations face significant challenges in preparing and filing Form 990 due to data silos across disparate systems, requiring extensive manual data extraction, parsing, and reconciliation, which is laborious and time-consuming, and lacks integration with IRS e-filing requirements.
Innovation Solution
The e990 system employs hyper-automation, combining AI, intelligent data capture, and robotic process automation to transform data from various repositories into a formatted Form 990, bridging the data silo and enabling direct e-filing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual data extraction and parsing is used to prepare Form 990, then flexibility in handling diverse data sources is maintained, but the process becomes laborious and time-consuming
Solution Approach 1:
The patent replaces manual mechanical data extraction processes with an automated machine learning-based system. The ML model automatically extracts, parses, and transforms data from diverse sources (accounting systems, CRM systems, payroll software) into Form 990 format, eliminating the need for manual intervention in data collection and processing operations.
Solution Approach 2:
The system enables self-service automation where the machine learning model independently performs data extraction, parsing, reconciliation, and form generation without requiring manual intervention. The automated system serves itself by learning from training data and applying transformations to generate accurate Form 990 filings autonomously.
2Quantity of substance
If data is extracted from disparate systems (accounting, CRM, payroll), then comprehensive information can be gathered, but data silos create interoperability challenges
Solution Approach 1:
The machine learning model serves as an intermediary that bridges disparate data sources (accounting systems, CRM systems, payroll software) and the IRS Form 990 structure. It automatically translates data from various formats and systems into the required Form 990 format, resolving interoperability challenges without requiring complex manual integration processes.
Solution Approach 2:
The patent creates a universal data transformation system that can handle multiple data sources (nine different accounting systems, ten CRM systems, five payroll software) and transform them all into a single standardized Form 990 output format. This multi-functional approach consolidates data integration complexity into a single automated model.
3Adaptability or versatility
If existing software systems are used by TEOs, then organizational infrastructure is maintained, but these systems lack functionality to prepare Form 990
Solution Approach 1:
The machine learning model acts as an intermediary layer between existing TEO software systems (accounting, CRM, payroll) and the Form 990 preparation process. It interfaces with existing systems through standard data extraction methods while providing the specialized Form 990 preparation functionality that these systems lack, maintaining infrastructure while adding capability.
Data Source
AI summary
Computer-implemented systems and methods to automatically complete a tax form by generating a transformed dataset using a machine learning model in an artificial intelligence infrastructure.