Considerable effort has been devoted to the development of software to support the detection of fraud in published financial statements of companies. Until the present date, however, the applied use of such research has been extremely limited due to the ``black box'' character of the existing...

Ratios are commonly used to extract information from accounting reports. However, ratios present only part of the information available in their two components. This article infers the functional form of the information discarded by ratios. It then develops ratio complements that incorporate the...

Key Audit Matters (KAMs) are informative for future accounting outcomes. Using FINBERT, a deep learning model for natural language processing that allows human-like text comprehension, we show that goodwill-related KAMs are predictive for firms' future impairments. In fact, we find that using...

The accurate prediction of incoming cash flows enables more effective cash management and allows firms to shape their planning based on forward-looking information. Although most firms are aware of the benefits of these forecasts, many still have difficulties identifying and implementing an...

In this study, we investigate the relationship between tax avoidance and earnings management in the largest five European Union economies by using artificial neural network regressions. This methodology allows us to deal with nonlinearities detected in the data, which is the principal...

In this study, we aim to advance the prediction of firm earnings - an important task for many business applications. While existing earnings prediction models only rely on numerical financial data, we hypothesize and find that vocal cues from manager speech yield substantial predictive power:...

We introduce a machine learning approach to quantify the thematic content of climate reporting in annual reports and use this to analyze firms’ climate reporting practices in the context of the widespread European Non-Financial Reporting Directive. We finetune ClimateBert to identify climate...

This study performs fundamental analysis and cross-sectional prediction of stock return with neural network technology. Eighteen financial ratios are used as the input vector and one-year ahead stock returns are used as the output vector. The fundamental analysis trading strategy generated by...

As documented by empirical research, tax compliance costs are a considerable burden for private businesses. However, cost estimates may be biased due to survey non-response and questionnaire framing effects. This paper investigates the impact of both aspects on cost estimates. We do not find...

The Bank for the Accounts of Companies Harmonized (BACH) is a free-of-charge database containing the aggregated accounting data of non-financial incorporated enterprises for, so far, 11 European countries. While the individual accounts feeding the database were originally prepared in line with...