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Abstract(s)
A fraude representa uma ameaça significativa para a integridade das informações financeiras, tornando-se fundamental explorar abordagens inovadoras para lidar com esse desafio. Nesse sentido, a IA (Inteligência Artificial) emerge como uma ferramenta promissora, oferecendo capacidades avançadas de análise de dados e identificação de padrões suspeitos. Esta Dissertação tem como motivação investigar o impacto da IA na deteção e prevenção de fraudes na auditoria. São analisadas vantagens e limitações de diversos subcampos da IA, que podem ser aplicados na área da auditoria. Para esta investigação foi adotada uma metodologia qualitativa, fundamentada em entrevistas semiestruturadas, realizadas a profissionais de auditoria, com a finalidade de compreender as suas perceções sobre a implementação de IA na auditoria para a deteção de irregularidades. Os entrevistados reconhecem o potencial da IA, destacando a sua eficiência na deteção de anomalias. No entanto, também identificam desafios, como a resistência à mudança e a necessidade de adaptação das normas de auditoria para o uso responsável da IA. Esta Dissertação procura preencher uma lacuna na literatura académica, uma vez que o tema em questão ainda é pouco explorado. Além disso, pretende motivar futuras investigações, uma vez que se espera que a IA tenha um impacto substancial na profissão de auditoria.
Fraud represents a significant threat to the integrity of financial information, making it essential to explore innovative approaches to dealing with this challenge. In this regard, AI (Artificial Intelligence) is emerging as a promising tool, offering advanced data analysis capabilities and identifying suspicious patterns. The motivation behind this Dissertation is to investigate the impact of AI on auditing to detect and prevent fraud. The advantages and limitations of various subfields of AI that can be applied to auditing are analysed. A qualitative methodology was adopted for this research, based on semi-structured interviews with auditing professionals, with the aim of understanding their perceptions of the implementation of AI in auditing to detect irregularities. The interviewees recognize the potential of AI, highlighting its efficiency in detecting anomalies. However, they also identify challenges, such as resistance to change and the need to adapt auditing standards to the responsible use of AI. This Dissertation seeks to fill a gap in the academic literature, since the topic in question is still little explored. It also aims to motivate future research, since AI is expected to have a substantial impact on the auditing profession.
Fraud represents a significant threat to the integrity of financial information, making it essential to explore innovative approaches to dealing with this challenge. In this regard, AI (Artificial Intelligence) is emerging as a promising tool, offering advanced data analysis capabilities and identifying suspicious patterns. The motivation behind this Dissertation is to investigate the impact of AI on auditing to detect and prevent fraud. The advantages and limitations of various subfields of AI that can be applied to auditing are analysed. A qualitative methodology was adopted for this research, based on semi-structured interviews with auditing professionals, with the aim of understanding their perceptions of the implementation of AI in auditing to detect irregularities. The interviewees recognize the potential of AI, highlighting its efficiency in detecting anomalies. However, they also identify challenges, such as resistance to change and the need to adapt auditing standards to the responsible use of AI. This Dissertation seeks to fill a gap in the academic literature, since the topic in question is still little explored. It also aims to motivate future research, since AI is expected to have a substantial impact on the auditing profession.
Description
Keywords
Auditoria Fraude Inteligência artificial Audit Artificial intelligence Fraud