US-20260127682-A1 - SYSTEMS AND METHODS FOR ALERTING TAX PROFESSIONALS ON INCOMING TAX REGULATORY CHANGES

Abstract

A system and method of tax regulatory change management is provided, comprising: receiving tax filing instructions and e-file schemas of tax forms; converting the filing instructions into output filing instructions and the e-file schemas into output e-file schemas; executing a mapping operation to generate an instruction-to-schema mapping; executing a tax form descriptions operation that generates form descriptions and per-line descriptions of each of the tax forms from the instruction-to-schema mapping using a first generative model; receiving a tax article identifying a tax regulation change; executing an impacted forms operation that uses the form descriptions and the identified tax regulation change as inputs to a second generative model that identifies an impacted tax form; executing an impacted lines operation that uses a third generative model to identify an impacted line from the impacted form; and generating a notification including the impacted line in the impacted form.

Inventors

• Adrian Alan Pol
• Stavroula Skylaki
• Krishna Chaitanya Reddy, V
• Palvika Bansal
• Guglielmo Bonifazi

Assignees

• THOMSON REUTERS ENTERPRISE CENTRE GMBH
• Thomson Reuters International Services Private Limited

Dates

Publication Date

20260507

Application Date

20251106

Claims (20)

1. 1 . A method of tax regulatory change management, comprising: receiving, by one or more processors, tax filing instructions from a tax filing instructions database; receiving, by the one or more processors, e-file schemas of tax forms from a tax form schemas database; executing, by the one or more processors, a text extraction operation to convert the tax filing instructions into output tax filing instructions having a text format; executing, by the one or more processors, a preprocessing operation to append an identifier to each line of the tax forms of the e-file schemas and convert the e-file schemas into output e-file schemas; executing, by the one or more processors, a mapping operation to generate an instruction-to-schema mapping by mapping the output tax filing instructions to the output e-file schemas, wherein the output tax filing instructions form a corpus and the output e-file schemas form queries; executing, by the one or more processors, a tax form descriptions operation that generates form descriptions and per-line descriptions of each of the tax forms from the instruction-to-schema mapping using a first generative model for each of the tax forms; receiving, by the one or more processors, a tax article identifying a tax regulation change; executing, by the one or more processors, an impacted forms operation that uses the form descriptions and the identified tax regulation change as inputs to a second generative model that identifies at least one impacted tax form; executing, by the one or more processors, an impacted lines operation that uses a third generative model to identify at least one impacted line from the at least one impacted form; and generating, by the one or more processors, a notification to a user on an interface, the notification including the at least one impacted line in the at least one impacted form.
2. 2 . The method of claim 1 , wherein the mapping operation employs a BM25algorithm to generate the instruction-to-schema mapping.
3. 3 . The method of claim 2 , wherein the BM25 algorithm ranks the output tax filing instructions to generate the instruction-to-schema mapping.
4. 4 . The method of claim 1 , further comprising executing, by the one or more processors, a filtering operation on the instruction-to-schema mapping, the output tax filing instructions and the output e-file schemas.
5. 5 . The method of claim 1 , further comprising executing, by the one or more processors, a long article generation operation that uses a fourth generative model to expand the tax article when a length of the tax article is below a predetermined threshold.
6. 6 . The method of claim 5 , wherein the third generative model identifies the at least one impacted line by determining which lines in the per-line descriptions are impacted by the expanded tax article.
7. 7 . The method of claim 1 , wherein the impacted forms operation performs a hallucination check by comparing the at least one impacted tax form to a predefined list of tax forms for a jurisdiction and filtering out the at least one impacted tax form when it does not appear on the predefined list of tax forms.
8. 8 . The method of claim 1 , wherein the second generative model generates a rationale for identifying the at least one impacted form for display in the notification.
9. 9 . The method of claim 1 , wherein the second generative model assigns a confidence level to the at least one impacted form based on a relevance of the tax regulation change to the at least one impacted form.
10. 10 . The method of claim 1 , wherein the third generative model generates a rationale for identifying the at least one impacted line for display in the notification.
11. 11 . The method of claim 1 , wherein the third generative model assigns a confidence level to the at least one impacted line based on a relevance of the tax regulation change to the at least one impacted line.
12. 12 . The method of claim 1 , wherein the notification includes a listing of searchable tax articles in a tax regulation insights panel.
13. 13 . The method of claim 12 , wherein when a tax article in the tax regulation insights panel is selected by the user, a title and text of the selected tax article are displayed in an article pane of the notification.
14. 14 . A system for tax regulatory change management, comprising: a memory including a plurality of generative models and a plurality of instructions; one or more processors coupled to the memory and configured to execute the instructions to perform a plurality of functions, including: receiving tax filing instructions from a tax filing instructions database; receiving e-file schemas of tax forms from a tax form schemas database; executing a text extraction operation to convert the tax filing instructions into output tax filing instructions having a text format; executing a preprocessing operation to append an identifier to each line of the tax forms of the e-file schemas and convert the e-file schemas into output e-file schemas; executing a mapping operation to generate an instruction-to-schema mapping by mapping the output tax filing instructions to the output e-file schemas, wherein the output tax filing instructions form a corpus and the output e-file schemas form queries; executing a tax form descriptions operation that generates form descriptions and per-line descriptions of each of the tax forms from the instruction-to-schema mapping using a first generative model for each of the tax forms; receiving a tax article identifying a tax regulation change; executing an impacted forms operation that uses the form descriptions and the identified tax regulation change as inputs to a second generative model that identifies at least one impacted tax form; executing an impacted lines operation that uses a third generative model to identify at least one impacted line from the at least one impacted form; and generating a notification to a user on an interface, the notification including the at least one impacted line in the at least one impacted form.
15. 15 . The system of claim 14 , wherein the mapping operation employs a BM25 algorithm to generate the instruction-to-schema mapping.
16. 16 . The system of claim 15 , wherein the BM25 algorithm ranks the output tax filing instructions to generate the instruction-to-schema mapping.
17. 17 . The system of claim 14 , wherein the impacted forms operation performs a hallucination check by comparing the at least one impacted tax form to a predefined list of tax forms for a jurisdiction and filtering out the at least one impacted tax form when it does not appear on the predefined list of tax forms.
18. 18 . The system of claim 14 , wherein the second generative model generates a rationale for identifying the at least one impacted form for display in the notification and assigns a confidence level to the at least one impacted form based on a relevance of the tax regulation change to the at least one impacted form.
19. 19 . The system of claim 14 , wherein the third generative model generates a rationale for identifying the at least one impacted line for display in the notification and assigns a confidence level to the at least one impacted line based on a relevance of the tax regulation change to the at least one impacted line.
20. 20 . A non-transitory computer-readable medium containing program instructions for causing a computer to perform a method of tax regulatory change management, comprising: receiving tax filing instructions from a tax filing instructions database; receiving e-file schemas of tax forms from a tax form schemas database; executing a text extraction operation to convert the tax filing instructions into output tax filing instructions having a text format; executing a preprocessing operation to append an identifier to each line of the tax forms of the e-file schemas and convert the e-file schemas into output e-file schemas; executing a mapping operation to generate an instruction-to-schema mapping by mapping the output tax filing instructions to the output e-file schemas, wherein the output tax filing instructions form a corpus and the output e-file schemas form queries; executing a tax form descriptions operation that generates form descriptions and per-line descriptions of each of the tax forms from the instruction-to-schema mapping using a first generative model for each of the tax forms; receiving a tax article identifying a tax regulation change; executing an impacted forms operation that uses the form descriptions and the identified tax regulation change as inputs to a second generative model that identifies at least one impacted tax form; executing an impacted lines operation that uses a third generative model to identify at least one impacted line from the at least one impacted form; and generating a notification to a user on an interface, the notification including the at least one impacted line in the at least one impacted form.

Description

RELATED APPLICATIONS This application is related to and claims priority to provisional application Ser. No. 63/717,067, entitled “SYSTEMS AND METHODS FOR ALERTING TAX PROFESSIONALS ON INCOMING TAX REGULATORY CHANGES,” filed on Nov. 6, 2024, the entire contents of which being expressly incorporated herein by reference. FIELD The present disclosure pertains to the field of tax regulation monitoring, and more particularly to systems and methods for alerting tax professionals of incoming tax regulatory changes and providing personalized notifications without compromising end user data privacy. BACKGROUND Tax regulatory changes can significantly impact businesses'financial and legal situations. Tax regulations are subject to frequent modifications by government authorities to address evolving economic conditions, promote specific policies, or adjust the tax system. For example, the Tax Cuts and Jobs Act of 2017 had many consequences for corporations and individuals in multiple jurisdictions. Tax professionals face challenges that can be broadly categorized into two groups. First, staying informed about tax regulatory changes is essential for providing accurate and up-to-date advice to individuals and businesses navigating the complex tax landscape. Tax laws and regulations are subject to frequent updates and modifications, occurring more often than annually. These changes can occur at various levels of government, including federal, state, and local jurisdictions. Second, correctly acting on changes to tax regulations is a complex and intricate task that requires a high degree of expertise and thoughtfulness. There are thousands of U.S. tax forms, schedules, and instructions to process to understand the full implications of tax regulation changes. This high volume of tax regulations, guidance, and rulings issued by various government agencies, such as the Internal Revenue Service and state tax authorities, is problematic. Extracting relevant updates from this vast amount of information is time-consuming. Tax professionals have busy schedules, especially during peak tax seasons. Many jurisdictions require tax professionals to complete educational courses or obtain certifications to maintain their licenses or credentials. This mitigates the issue of staying up to date, but does not eliminate it entirely. Finding time to review and comprehend tax regulation updates is difficult within limited timeframes amidst other professional obligations of tax professionals. Additionally, tax laws and regulations are complex, with intricate details, nuances, and implications that involve numerous exceptions, special cases, and interrelated provisions. Moreover, they vary significantly across different jurisdictions. Tax professionals must be aware of these differences when working with clients whose businesses are present in multiple jurisdictions. Finally, even after identifying relevant updates, understanding the implications and their interpretation of how to apply them correctly to specific client situations is non-trivial. Inaccurate interpretation of tax regulation can result in fines and penalties for the parties involved or other negative financial implications. When relevant tax legislation is overlooked, it may result in the incorrect amount of tax paid, which could have monetary or legal consequences for the individuals, businesses and organizations involved. Tax professionals attempt to address the above challenges by relying on diverse strategies such as attending seminars and workshops, subscribing to professional publications and online resources, networking with peers, and seeking guidance from other tax experts or professional organizations. A human-centric approach relies on a manual review of incoming changes and their relevance to the customer base. This is a time-consuming process that is prone to errors and lacks scalability for large data volumes. Additionally, it may introduce inconsistencies due to individual biases and varying levels of expertise among human experts. Notification services, seminars and workshops lack personalization, breadth of information, and real-time adaptability. These methods often provide generic information that may not address specific taxpayer needs. Regarding potential automated strategies for addressing the above-described challenges, rule-based automation systems, although capable of handling straightforward compliance checks, struggle with ambiguity in regulatory language and require frequent manual rule amendments. Collaborative filtering relies heavily on other users'data and thus causes a competitive advantage issue. It can replace human tax advisors with algorithms that can scale to a large data volume but at the cost of sharing companies'data. Additionally, it can create echo chambers that focus only on some changes and limit exposure to uncommon cases. Directly matching client data with regulatory change through a similarity indicator is a straightforward solution,