The Impacts of Machine Learning in Financial Crisis Prediction

Siddhartha Vadlamudi
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Siddhartha Vadlamudi: Software Engineer II, Xandr, AT&T Services Inc., New York, USA

Asian Business Review, 2020, vol. 10, issue 3, 171-176

Abstract: The most complicated and expected issue to be handled in corporate firms, small-scale businesses, and investors’ even governments are financial crisis prediction. To this effect, it was of interest to us to investigate the current impact of the newly employed technique that is machine learning (ML) to handle this menace in all spheres of business both private and public. The study uses systematic literature assessment to study the impact of ML in financial crisis prediction. From the selected works of literature, we have been able to establish the important role play by this method in the prediction of bankruptcy and creditworthiness that was not handled appropriately by others method. Also, machine learning helps in data handling, data privacy, and confidentiality. This study presents a leading approach to achieving financial growth and plasticity in corporate organizations. We, therefore, recommend a real-time study to investigate the impact of ML in FCP.

Keywords: Machine learning; financial crisis prediction; bankruptcy; creditworthiness (search for similar items in EconPapers)
JEL-codes: H12 (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)

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