Line-Item Consolidation for Form 1120
Description
Large Business & International (LB&I) partnerships have a variety of forms and statements that include text. Filings include semi-structured attachments to returns that consist of many short free text labels paired with dollar amounts. Short text labels that include information like descriptions, addresses, and alphanumeric type codes. Non-standard labels are difficult to structure and interpret unstructured narrative text, ranging from a sentence to entire paragraph-based documents, that taxpayers provide to explain, justify, or document a position. This is a research project. The goal of this project is to identify opportunities to derive value from the unstructured text. Assess potential value to examiners from consolidation across labeled pairs, utilize consolidated line items for outlier analysis, etc.
Detailed example
A Form 1120 Other Deduction line-item description is assigned or consolidated to a consolidation group, which is either a subject matter expert defined deduction category or a deduction description existing in the dataset, based on how semantically similar the descriptions are, measured by cosine similarity. The model produces an additional column appended to the original dataset that contains the consolidation group (text string) that the line-item description (row) was matched to.
AI / analytics pattern
Natural Language Processing: AI that processes, interprets, and shares information in human language.
Automation level / stage
c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
Expected benefit
Line-item consolidation is a crucial step in providing value to examiners through the grouping of numerous free-text responses into common, recognizable groups that allow for further analysis and exploration. Not only do these line-items become more accessible to examiners, but it facilitates a more robust benchmarking analysis of line-item amounts by creating larger groupings of common line-items. Success in the line-item consolidation stage was defined by how effectively each stage of the text consolidation pipeline could reduce the number of unique line-item descriptions while maintaining an appropriate level of specificity.
Audit / financial statement impact
The output is not presumed to be high-impact and is not used as the principal basis for significant decisions/actions
Controls / human review
ATO: Yes; PIA: Not published
Data needed
The team evaluated the appropriateness of assignments in the top 500 most frequent and material groups in order to further quantify the accuracy of consolidation. Original descriptions were manually reviewed within their respective assigned consolidated groups and a judgment was made on whether the description fit within the rest of the group or not. We also evaluated the amount of consolidation that our updated algorithm could perform. On a test of all 1120 Other Deductions in CDW, the algorithm was able to consolidate nearly 4 million unique line-item descriptions into 253 groups.