Please use this identifier to cite or link to this item: https://dair.nps.edu/handle/123456789/4615
Full metadata record
DC FieldValueLanguage
dc.contributor.authorDavid I. Gill, Avram Ibrahim-
dc.contributor.authorChaudry Umer, Sonia Jolly-
dc.contributor.authorAlicia M. Miller-
dc.date.accessioned2022-05-05T22:30:19Z-
dc.date.available2022-05-05T22:30:19Z-
dc.date.issued2022-05-02-
dc.identifier.citationPublished--Unlimited Distributionen_US
dc.identifier.urihttps://dair.nps.edu/handle/123456789/4615-
dc.descriptionExcerpt from the Proceedings of the Nineteenth Annual Acquisition Research Symposiumen_US
dc.description.abstractFederal 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.en_US
dc.description.sponsorshipAcquisition Research Programen_US
dc.language.isoen_USen_US
dc.publisherAcquisition Research Programen_US
dc.relation.ispartofseriesAcquisition Management;SYM-AM-22-088-
dc.subjectNatural Language Processing (NLP)en_US
dc.subjectRoboticen_US
dc.subjectFinancial Dataen_US
dc.subjectProcurementen_US
dc.subjectProcess Automationen_US
dc.titleMaking Federal Financial Data More Reliable With Emerging Techen_US
dc.typeTechnical Reporten_US
Appears in Collections:Annual Acquisition Research Symposium Proceedings & Presentations

Files in This Item:
File Description SizeFormat 
SYM-AM-22-088.pdfProceedings1 MBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.