Purpose: The purpose of this study is to investigate and analyze whether the relationship between structural domains represented by CAATs and judgment represented by professional scepticism is related to auditors’ individual characteristics, trait scepticism. Methodology: This study is based on a quantitative method in the form of a questionnaire sent to all Swedish authorized auditors. The response rate was 16.8 per cent. The responses were analyzed by Spearman correlation matrix, principal component analysis, multiple linear regression analysis, and hierarchical moderated multiple regression analysis. Moreover, this thesis is based on a positivistic perspective to get a general picture of professional scepticism. A deductive approach, going from theory to empirics, has been implemented. Findings: The results showed a positive relationship between judgment represented by professional scepticism and structure represented by CAATs, where auditors’ individual characteristics, trait scepticism, have a positive moderating effect on the relationship. Theoretical perspectives: We apply the profession theory, comfort theory and structure and judgment at Swedish authorized auditors with diverse experience.

Background: Research has shown that the risk of material misstatements increases during exogenous risk shocks. Simultaneously, auditors shall identify and assess the emergent risks. During the GFC, auditors' response was considered satisfactory by some but criticized byothers. Covid-19 presents a new exogenous risk shock which should entail a similar response by auditors. Purpose: The purpose of this study is to determine the effect that exogenous risks during uncertain economic times have on the risk- and materiality assessments of auditors. Further, to determine if auditor independence and trait scepticism affect the relationship between exogenous risk and risk- and materiality assessments. Methodology: This study used a quantitative method by sending out questionnaires to Swedish authorized and approved auditors. The answers were analysed through Spearman correlation matrixes, Paired-samples T-tests, Ordinary Least Squares (OLS) regressions and a binary logistics regression. This study is based on a positivistic perspective and a deductive approach was used. Conclusion: The findings indicated that auditors did make more conservative risk assessments in response to the Covid-19 pandemic. However, they did not adjust the materiality assessments nor performance materiality assessments significantly. Moreover, that the individually situated factors of auditors had impact on the assessments during the pandemic.

Likt flera branscher utvecklas revisionsbranschen under tidens gång. Nya arbetssätt och verktyg introduceras för att utveckla revisionsutförandet. Ett av dessa verktyg som har implementerats av många revisionsbolag är Big data analys. Forskningsområdet kring Big data analys användande i revisionsutförandet är i ett inledande stadie, och resultaten är skilda. Tidigare forskning är dock ense om att Big data analys har en påverkan på revisionsutförandet och att revisorns kompetenser spelar en avgörande roll om användandet av Big data analys blir framgångsrikt. Till följd av detta var studiens syfte att undersöka vilken påverkan användningen av Big data analys har på revisionsutförandet samt vilka kompetenser som behövs vid användandet av Big data analys. Utifrån studiens syfte formuleradestre forskningsfrågor som behandlade Big data analys påverkan på revisionskvaliteten, revisionsutförandets legitimitet samt vilka kompetenser som behövs för att uppnå komfort och upprätthålla professionell skepticism i revisionsutförandet.För att uppnå studiens syfte har insamlingen av empiri grundat sig i en kvalitativ metod. Tio respondenter deltog i studien, varav sju var auktoriserade revisorer och resterande tre var revisorsassistenter.De slutsatser som studien generat är att revisorns kompetenser ansågs väsentliga för hur välfungerande användandet Big data analys var. Dock ansåg inte respondenterna att det var några nya kompetenser som behövdes vid användandet av Big data analys. Utan det var alltjämt en god förståelse för revision och redovisning som behövdes. Vidare ansågs Big data analys bidra till mer komfort i revisionsutförandet. Samtidigt som den professionella skepticismen alltjämt genomsyrade allt i revisions arbetssätt, och då även Big data analyser. Däremot påvisades det att användandet av Big data analys kunde hjälpa revisorer finna fler revisionsbevis, vilket hjälpte revisorn att vara professionellt skeptisk gentemot det reviderade bolaget. Big data analys förtjänster att testa en större population, jämfört med traditionella stickprov, ansågs öka den övergripande revisionskvaliteten. Detta medförde även att legitimiteten påverkades positivt hos de bolag som hade större kunder med mer transaktioner. Medan revisionsbolaget som jobbade mot kunder med mindre verksamheter inte upplevde samma positiva inverkan på deras legitimitet vid användningen av Big data analys i revisionsutförandet. / Like several industries, the auditing industry is evolving over time. New methods and tools are being introduced to enhance the auditing process. One of these methods that has been implemented by many audit firms is Big Data analysis. The research field on the use of Big Data analysis in auditing is in its early stages, and the results are mixed. However, previous research agreed that Big Data analysis has an impact on the auditing process, and the auditor's competencies play a crucial role in the successful implementation of Big Data analysis.As a result, the aim of this study was to investigate the impact of using Big Data analysis on the auditing process and identify the competencies required for its effective use. Based on the study's objective, three research questions were formulated, addressing the impact of Big Data analysis on audit quality, the legitimacy of the auditing process, and the competencies needed to achieve comfort and maintain professional skepticism in the audit process when using Big Data analysis. To achieve the study's objective, empirical data was collected using a qualitative methodology. Ten respondents participated in the study, including seven certified auditors and three audit assistants. The study's conclusions indicate that the auditor's competencies were considered essential for the successful implementation of Big Data analysis. However, the respondents did not believe that any new competencies were required specifically for conducting Big Data analysis reviews. Instead, a solid understanding of auditing and accounting was deemed necessary. Furthermore, Big Data analysis was seen to contribute to greater comfort in the audit process. At the same time, professional skepticism continued to permeate the entire auditing approach, including Big Data analysis. However, it was demonstrated that the use of Big Data analysis could help auditors find more audit evidence, aiding the auditor in maintaining professional skepticism toward the audited company. The advantages of Big Data analysis in testing a larger population, compared to traditional sampling, were seen to enhance overall audit quality. This also had a positive impact on the legitimacy of companies with larger clients and more transactions. Conversely, audit firms working with smaller businesses did not experience the same positive impact on their legitimacy when using Big Data analysis in the audit process.