# Financial Distress and Bankruptcy Prediction

**Type:** Topics  
**Canonical URL:** https://scholariq.org/topics/financial-distress-and-bankruptcy-prediction/

## Facts

| Field | Value |
| --- | --- |
| Description | This cluster of papers focuses on the development and comparison of machine learning models, including neural networks, support vector machines, and ensemble methods, for predicting bankruptcy and assessing credit risk. The research explores various techniques for financial distress prediction, credit scoring, and risk assessment in both corporate and consumer contexts. |
| Domain | Social Sciences |
| Field | Business, Management and Accounting |
| OpenAlex ID | t11653 |
| Works | 18 |

## Topic papers all

Showing 15 of 18.

- [A Comparison of Undersampling, Oversampling, and SMOTE Methods for Dealing with Imbalanced Classification in Educational Data Mining](https://scholariq.org/papers/a-comparison-of-undersampling-oversampling-and-smote-methods-for-dealing-with/)
- [Credit Card Fraud Detection - Machine Learning methods](https://scholariq.org/papers/credit-card-fraud-detection-machine-learning-methods/)
- [Intelligent financial fraud detection practices in post-pandemic era](https://scholariq.org/papers/intelligent-financial-fraud-detection-practices-in-post-pandemic-era/)
- [Vertical bagging decision trees model for credit scoring](https://scholariq.org/papers/vertical-bagging-decision-trees-model-for-credit-scoring/)
- [Neural network prediction analysis: The bankruptcy case](https://scholariq.org/papers/neural-network-prediction-analysis-the-bankruptcy-case/)
- [Federated learning model for credit card fraud detection with data balancing techniques](https://scholariq.org/papers/federated-learning-model-for-credit-card-fraud-detection-with-data-balancing/)
- [Estimating Missing Values Using Neural Networks](https://scholariq.org/papers/estimating-missing-values-using-neural-networks/)
- [A privacy-preserving decentralized credit scoring method based on multi-party information](https://scholariq.org/papers/a-privacy-preserving-decentralized-credit-scoring-method-based-on-multi-party/)
- [Clues from networks: quantifying relational risk for credit risk evaluation of SMEs](https://scholariq.org/papers/clues-from-networks-quantifying-relational-risk-for-credit-risk-evaluation-of/)
- [Diagnosis with incomplete multi-view data: A variational deep financial distress prediction method](https://scholariq.org/papers/diagnosis-with-incomplete-multi-view-data-a-variational-deep-financial-distress/)
- [Extracting Prediction Rules for Loan Default Using Neural Networks through Attribute Relevance Analysis](https://scholariq.org/papers/extracting-prediction-rules-for-loan-default-using-neural-networks-through/)
- [Operating Cash Flow Ranking Using Data Envelopment Analysis with Network Security Driven Blockchain Model](https://scholariq.org/papers/operating-cash-flow-ranking-using-data-envelopment-analysis-with-network/)
- [AI for bureaucratic productivity: Measuring the potential of AI to help automate 143 million UK government transactions](https://scholariq.org/papers/ai-for-bureaucratic-productivity-measuring-the-potential-of-ai-to-help-automate/)
- [Research on Enterprise Financial Early Warning System Based on AIO Algorithm and Z-Score Model](https://scholariq.org/papers/research-on-enterprise-financial-early-warning-system-based-on-aio-algorithm-and/)
- [Enhancing Loan Default Prediction with Human-in-the-Loop and XGBoost Ensemble Learning](https://scholariq.org/papers/enhancing-loan-default-prediction-with-human-in-the-loop-and-xgboost-ensemble/)

## Topic primary papers

- [Vertical bagging decision trees model for credit scoring](https://scholariq.org/papers/vertical-bagging-decision-trees-model-for-credit-scoring/)
- [Neural network prediction analysis: The bankruptcy case](https://scholariq.org/papers/neural-network-prediction-analysis-the-bankruptcy-case/)
- [Estimating Missing Values Using Neural Networks](https://scholariq.org/papers/estimating-missing-values-using-neural-networks/)
- [A privacy-preserving decentralized credit scoring method based on multi-party information](https://scholariq.org/papers/a-privacy-preserving-decentralized-credit-scoring-method-based-on-multi-party/)
- [Clues from networks: quantifying relational risk for credit risk evaluation of SMEs](https://scholariq.org/papers/clues-from-networks-quantifying-relational-risk-for-credit-risk-evaluation-of/)
- [Diagnosis with incomplete multi-view data: A variational deep financial distress prediction method](https://scholariq.org/papers/diagnosis-with-incomplete-multi-view-data-a-variational-deep-financial-distress/)
- [Extracting Prediction Rules for Loan Default Using Neural Networks through Attribute Relevance Analysis](https://scholariq.org/papers/extracting-prediction-rules-for-loan-default-using-neural-networks-through/)
- [Research on Enterprise Financial Early Warning System Based on AIO Algorithm and Z-Score Model](https://scholariq.org/papers/research-on-enterprise-financial-early-warning-system-based-on-aio-algorithm-and/)
- [Credit Risk Prediction Using Machine Learning on Apache Spark Big Data Framework](https://scholariq.org/papers/credit-risk-prediction-using-machine-learning-on-apache-spark-big-data-framework/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.