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Title: Making Federal Financial Data More Reliable With Emerging Tech
Authors: David I. Gill, Avram Ibrahim
Chaudry Umer, Sonia Jolly
Alicia M. Miller
Keywords: Natural Language Processing (NLP)
Financial Data
Process Automation
Issue Date: 2-May-2022
Publisher: Acquisition Research Program
Citation: Published--Unlimited Distribution
Series/Report no.: Acquisition Management;SYM-AM-22-088
Abstract: Federal agencies are stewards of billions in taxpayer funds. Given the scale of federal financial transactions, maintaining reliable, high-quality financial data can be challenging. The use of emerging technologies such as robotic process automation (RPA) and natural language processing can reduce manual work for agency employees and improve the consistency of financial data. These technologies are key to success on financial audits and maintaining public confidence in the reliability of procurement and nonprocurement financial information.
Description: Excerpt from the Proceedings of the Nineteenth Annual Acquisition Research Symposium
Appears in Collections:Annual Acquisition Research Symposium Proceedings & Presentations

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