Machine learning techniques for credit risk evaluation: a systematic literature review

S Bhatore, L Mohan, YR Reddy - Journal of Banking and Financial …, 2020 - Springer
Credit risk is the risk of financial loss when a borrower fails to meet the financial commitment.
While there are many factors that constitute credit risk, due diligence while giving loan (credit …

Predicting restaurant financial distress using decision tree and AdaBoosted decision tree models

SY Kim, A Upneja - Economic Modelling, 2014 - Elsevier
The restaurant industry has been facing tough challenges because of the recent economic
turmoil. Although different industries face different levels of competition and therefore the …

Integrating reward maximization and population estimation: Sequential decision-making for Internal Revenue Service audit selection

P Henderson, B Chugg, B Anderson… - Proceedings of the …, 2023 - ojs.aaai.org
We introduce a new setting, optimize-and-estimate structured bandits. Here, a policy must
select a batch of arms, each characterized by its own context, that would allow it to both …

A full population auditing method based on machine learning

Y Chen, Z Wu, H Yan - Sustainability, 2022 - mdpi.com
As it is urgent to change the traditional audit sampling method that is based on manpower to
meet the growing audit demand in the era of big data. This study uses empirical methods to …

Data mining method for identifying biased or misleading future outlook

A Yosef, M Schneider, E Shnaider - International Journal of …, 2022 - World Scientific
In this study, we introduce a data mining method to identify biased and/or misleading
outlooks for future performance of various factors, such as income, corporate profits …

Corporate governance fraud detection from annual reports using big data analytics

GS Sadasivam, M Subrahmanyam… - … Journal of Big …, 2016 - inderscienceonline.com
Financial reports of corporations publicise their performance. This in turn motivates
manipulation of financial statements. Falsification of financial statements over prolonged …

Financial fraud identification based on stacking ensemble learning algorithm: Introducing MD&A text information

Z Zhang, Y Ma, Y Hua - Computational Intelligence and …, 2022 - Wiley Online Library
In recent years, there have been frequent incidents of financial fraud committed through
various means. How to more efficiently identify financial fraud and maintain capital market …

[PDF][PDF] Using ants to detect fraudulent financial statements

CD Katsis, Y Goletsis, PV Boufounou… - Journal of applied …, 2012 - scienpress.com
Fraudulent financial reporting is a matter of great social and economic concern. Managers
may distort financial statements so as to present their companies more favorably to investors …

Rumor detection in business reviews using supervised machine learning

A Habib, S Akbar, MZ Asghar… - … Economic, and Socio …, 2018 - ieeexplore.ieee.org
Currently, a high volume of business data is generating with a high velocity in different forms
like unstructured, structured or semi-structured. Due to social media arrival, there is a deluge …

Using active learning methods for predicting fraudulent financial statements

S Karlos, G Kostopoulos, S Kotsiantis… - … Applications of Neural …, 2017 - Springer
Abstract Detection of Fraudulent Financial Statements (FFS), or simpler fraud detection
problem, refers to the falsification of financial statements with the aim either to demonstrate …