Affiliation:
1. Department of Business Administration, Saint Peter’s University, Jersey City, NJ 07306, USA
2. Data Science Institute, Saint Peter’s University, Jersey City, NJ 07306, USA
Abstract
The study presents a comprehensive approach to examining the potential risk of bankruptcies in financial sector organizations. This investigation explores 20 financial sector entities and evaluates their fiscal history from 2000 to 2018. The developed model assesses the chance of these companies going bankrupt by analyzing indicators like liquidity, profitability, debt composition, and operational effectiveness. These metrics are contrasted to regulatory requirements and assessed as having low, moderate, or elevated risk repercussions, ultimately contributing to an overall threat rating. Additionally, the model has a unique algorithm that compensates for excessive debt levels, strengthening the reliability of the risk appraisal grade. This straightforward instrument illustrates the demand to incorporate a variety of financial health indicators. According to the findings, excessive amounts of debt have a detrimental influence on profitability, leading to decreased stock returns and a greater probability of bankruptcy. These findings have practical implications for investors and stakeholders, providing insightful information to help inform decision-making, especially during periods of economic unpredictability such as pandemics. Furthermore, they encourage the enhancement of financial market efficiency.
Funder
The Data Science Institute, Saint Peter’s University
Subject
Finance,Economics and Econometrics,Accounting,Business, Management and Accounting (miscellaneous)
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