The aim of this study is to introduce an innovative text mining approach to assess firms' risks using unstructured textual disclosure from annual reports. Specifically, we use Natural Language Processing techniques to extract firms' self-identified risks including financial, strategic,...

This study explores the most recent episode in the evolution of audit technology, namely the incorporation of Big Data and Data Analytics (BDA) into audit firm approaches. Drawing on twenty-two interviews with individuals with significant experience in developing, implementing or assessing the...

This study compares the ability of four data-mining techniques in the prediction of audit opinions on companies' financial statements. The research data consists of 37,325 firm-year observations for companies listed on the New York Stock Exchange (NYSE), the American Stock Exchange (AMEX), and...

Modern financial management is largely about risk management, which is increasingly data-driven. The problem is how to extract information from the data overload. It is here that advanced statistical and machine learning techniques can help. Accordingly, finance, statistics, and data analytics...

To meet general objectives of the article, i.e. to check the extent to which the information needs of financial market institutions are satisfied, and to learn about whether there is a transition in this realm triggered by the advent of social media and big data, we surveyed a sample of 415...