Methods to detect fraud in accounting and finance
dc.contributor.author | Iyer, Arvind, author | |
dc.contributor.author | Nguyen, Nate, advisor | |
dc.contributor.author | Vance, Thomas, committee member | |
dc.date.accessioned | 2025-05-09T17:49:29Z | |
dc.date.available | 2025-05-09T17:49:29Z | |
dc.date.issued | 2025 | |
dc.description | Accounting | |
dc.description.abstract | With the increasing complexity of the business world and the advanced technologies involved, detecting fraud has become difficult. Throughout my paper, I examine different models of Corporate Governance and explain which one is more effective in certain scenarios. I investigate internal controls like the internal audit and Segregation of Duties, and show why it is vital for firms to effectively apply them in their business. I discuss how Corporate Social Responsibility and how to uncover this practice. At the end, I discuss how firms can implement artificial intelligence (AI) and machine learning (ML) to efficiently detect and prevent fraud. To successfully prevent fraud in finance and accounting, firms need strong structural integrity made up of consistently strong internal controls. My paper seeks to suggest some strategies to help companies achieve this goal. Having such frameworks as the internal audit and CSR in place will allow firms to improve their controls and prevent fraud. Advanced technologies based on artificial intelligence and machine learning are also robust approaches to detect fraud. | |
dc.format.medium | born digital | |
dc.format.medium | Student works | |
dc.identifier.uri | https://hdl.handle.net/10217/240591 | |
dc.language | English | |
dc.language.iso | eng | |
dc.publisher | Colorado State University. Libraries | |
dc.relation.ispartof | Honors Theses | |
dc.rights | Copyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright. | |
dc.subject | accounting | |
dc.subject | finance | |
dc.subject | fraud | |
dc.subject | artificial intelligence | |
dc.subject | governance | |
dc.subject | machine learning | |
dc.title | Methods to detect fraud in accounting and finance | |
dc.type | Text | |
dc.type | Image | |
dcterms.rights.dpla | This Item is protected by copyright and/or related rights (https://rightsstatements.org/vocab/InC/1.0/). You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s). | |
thesis.degree.discipline | Honors | |
thesis.degree.discipline | Accounting | |
thesis.degree.grantor | Colorado State University | |
thesis.degree.level | Undergraduate | |
thesis.degree.name | Honors Thesis |