An AI-Based Automated Continuous Compliance Awareness Framework (CoCAF) for Procurement Auditing
Compliance management for procurement internal auditing has been a major challenge for public sectors due to its tedious period of manual audit history and large-scale paper-based repositories. Many practical issues and potential risks arise during the manual audit process, including a low level of...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-09-01
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| Series: | Big Data and Cognitive Computing |
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| Online Access: | https://www.mdpi.com/2504-2289/4/3/23 |
| _version_ | 1797554720040026112 |
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| author | Ke Wang Michael Zipperle Marius Becherer Florian Gottwalt Yu Zhang |
| author_facet | Ke Wang Michael Zipperle Marius Becherer Florian Gottwalt Yu Zhang |
| author_sort | Ke Wang |
| collection | DOAJ |
| description | Compliance management for procurement internal auditing has been a major challenge for public sectors due to its tedious period of manual audit history and large-scale paper-based repositories. Many practical issues and potential risks arise during the manual audit process, including a low level of efficiency, accuracy, accountability, high expense and its laborious and time consuming nature. To alleviate these problems, this paper proposes a continuous compliance awareness framework (CoCAF). It is defined as an AI-based automated approach to conduct procurement compliance auditing. CoCAF is used to automatically and timely audit an organisation’s purchases by intelligently understanding compliance policies and extracting the required information from purchasing evidence using text extraction technologies, automatic processing methods and a report rating system. Based on the auditing results, the CoCAF can provide a continuously updated report demonstrating the compliance level of the procurement with statistics and diagrams. The CoCAF is evaluated on a real-life procurement data set, and results show that it can process 500 purchasing pieces of evidence within five minutes and provide 95.6% auditing accuracy, demonstrating its high efficiency, quality and assurance level in procurement internal audit. |
| first_indexed | 2024-03-10T16:36:03Z |
| format | Article |
| id | doaj.art-9501465012c3427aa9a96f35fa07a94f |
| institution | Directory Open Access Journal |
| issn | 2504-2289 |
| language | English |
| last_indexed | 2024-03-10T16:36:03Z |
| publishDate | 2020-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Big Data and Cognitive Computing |
| spelling | doaj.art-9501465012c3427aa9a96f35fa07a94f2023-11-20T12:24:44ZengMDPI AGBig Data and Cognitive Computing2504-22892020-09-01432310.3390/bdcc4030023An AI-Based Automated Continuous Compliance Awareness Framework (CoCAF) for Procurement AuditingKe Wang0Michael Zipperle1Marius Becherer2Florian Gottwalt3Yu Zhang4Logistics Insight Lab, School of Business, UNSW Canberra at the Australian Defence Force Academy, 2612 Canberra, AustraliaLogistics Insight Lab, School of Business, UNSW Canberra at the Australian Defence Force Academy, 2612 Canberra, AustraliaLogistics Insight Lab, School of Business, UNSW Canberra at the Australian Defence Force Academy, 2612 Canberra, AustraliaLogistics Insight Lab, School of Business, UNSW Canberra at the Australian Defence Force Academy, 2612 Canberra, AustraliaLogistics Insight Lab, School of Business, UNSW Canberra at the Australian Defence Force Academy, 2612 Canberra, AustraliaCompliance management for procurement internal auditing has been a major challenge for public sectors due to its tedious period of manual audit history and large-scale paper-based repositories. Many practical issues and potential risks arise during the manual audit process, including a low level of efficiency, accuracy, accountability, high expense and its laborious and time consuming nature. To alleviate these problems, this paper proposes a continuous compliance awareness framework (CoCAF). It is defined as an AI-based automated approach to conduct procurement compliance auditing. CoCAF is used to automatically and timely audit an organisation’s purchases by intelligently understanding compliance policies and extracting the required information from purchasing evidence using text extraction technologies, automatic processing methods and a report rating system. Based on the auditing results, the CoCAF can provide a continuously updated report demonstrating the compliance level of the procurement with statistics and diagrams. The CoCAF is evaluated on a real-life procurement data set, and results show that it can process 500 purchasing pieces of evidence within five minutes and provide 95.6% auditing accuracy, demonstrating its high efficiency, quality and assurance level in procurement internal audit.https://www.mdpi.com/2504-2289/4/3/23continuous auditingcomplianceautomationtext mining |
| spellingShingle | Ke Wang Michael Zipperle Marius Becherer Florian Gottwalt Yu Zhang An AI-Based Automated Continuous Compliance Awareness Framework (CoCAF) for Procurement Auditing Big Data and Cognitive Computing continuous auditing compliance automation text mining |
| title | An AI-Based Automated Continuous Compliance Awareness Framework (CoCAF) for Procurement Auditing |
| title_full | An AI-Based Automated Continuous Compliance Awareness Framework (CoCAF) for Procurement Auditing |
| title_fullStr | An AI-Based Automated Continuous Compliance Awareness Framework (CoCAF) for Procurement Auditing |
| title_full_unstemmed | An AI-Based Automated Continuous Compliance Awareness Framework (CoCAF) for Procurement Auditing |
| title_short | An AI-Based Automated Continuous Compliance Awareness Framework (CoCAF) for Procurement Auditing |
| title_sort | ai based automated continuous compliance awareness framework cocaf for procurement auditing |
| topic | continuous auditing compliance automation text mining |
| url | https://www.mdpi.com/2504-2289/4/3/23 |
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