Discretionary Disclosure in Financial Reporting: An Examination Comparing Internal Firm Data to Externally Reported Segment Data

Financial Reporting Fraud Detection: An Analysis of Data Mining Algorithms

In the last decade, high profile financial frauds committed by large companies in both developed and developing countries were discovered and reported. This study compares the performance of five popular statistical and machine learning models in detecting financial statement fraud. The research objects are companies which experienced both fraudulent and non-fraudulent financial statements betw...

Non-discretionary imprecise data in efficiency Measurement

This paper introduces discretionary imprecise data in Data Envelopment Analysis (DEA) and discusses the efficiency evaluation of Decision Making Units (DMUs) with non-discretionary imprecise data. Then, suggests a method for evaluation the efficiency of DMUs with non-discretionary imprecise data. When some inputs and outputs are imprecise and non-discretionary, the DEA model becomes non-linear ...

Linked Data for Financial Reporting

Recently, uncertainty has dominated global financial markets. Companies are struggling with their balance sheets while merges and acquisitions (M&A) happens on a more frequent basis. This calls for highly accurate corporate performance data, which serve as the ground truth for M&A decisions. Conventional financial reporting approach has drawn criticism from both investors and analysts, attribut...

Data Envelopment Analysis Models In The Presence Of Ratio Data and Non-Discretionary Factors

Non-discretionary Factors in Data Envelopment Analysis: Review and Extension