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Predicting failure in the U.S. banking sector: An extreme gradient boosting approach
9 references·16 citing·48 second hop
Predicting failure in the U.S. banking sector: An extreme gradient boosting approach (2018)Predicting failure in the U.S. banking se…Ensemble boosted trees with synthetic features generation in application to bankruptcy prediction (2016)Ensemble boosted trees with s…Nontraditional banking activities and bank failures during the financial crisis (2013)Nontraditional banking activi…How does capital affect bank performance during financial crises? (2013)How does capital affect bank …Credit Booms and Lending Standards: Evidence from the Subprime Mortgage Market (2012)Credit Booms and Lending Stan…Comparative analysis of data mining methods for bankruptcy prediction (2011)Comparative analysis of data …Bankruptcy prediction in banks and firms via statistical and intelligent techniques – A review (2006)Bankruptcy prediction in bank…Size and performance of banking firms (1993)Size and performance of banki…An application of the cox proportional hazards model to bank failure (1986)An application of the cox pro…PREDICTION OF BANK FAILURES (1970)PREDICTION OF BANK FAILURESCredit growth, the yield curve and financial crisis prediction: Evidence from a machine learning approach (2023)Credit growth, the yield curv…The role of Environmental, Social, and Governance (ESG) in predicting bank financial distress (2022)The role of Environmental, So…Operational Research and Artificial Intelligence Methods in Banking (2022)Operational Research and Arti…No more black boxes! Explaining the predictions of a machine learning XGBoost classifier algorithm in business failure (2022)No more black boxes! Explaini…House price prediction using hedonic pricing model and machine learning techniques (2022)House price prediction using …Gradient tree boosting and the estimation of production frontiers (2022)Gradient tree boosting and th…Bankruptcy Prediction using the XGBoost Algorithm and Variable Importance Feature Engineering (2022)Bankruptcy Prediction using t…A novel ensemble feature selection method by integrating multiple ranking information combined with an SVM ensemble model for enterprise credit risk prediction in the supply chain (2022)A novel ensemble feature sele…Predicting bankruptcy of local government: A machine learning approach (2021)Predicting bankruptcy of loca…Financial distress prediction by combining sentiment tone features (2021)Financial distress prediction…The impact of the magnitude of service failure and complaint handling on satisfaction and brand credibility in the banking industry (2020)The impact of the magnitude o…Predicting next day direction of stock price movement using machine learning methods with persistent homology: Evidence from Kuala Lumpur Stock Exchange (2020)Predicting next day direction…It’s a Peoples Game, Isn’t It?! A Comparison Between the Investment Returns of Business Angels and Machine Learning Algorithms (2020)It’s a Peoples Game, Isn’t It…Determinants of corporate default risk in China: The role of financial constraints (2020)Determinants of corporate def…An ordinal classification framework for bank failure prediction: Methodology and empirical evidence for US banks (2019)An ordinal classification fra…A New Perspective of Performance Comparison among Machine Learning Algorithms for Financial Distress Prediction (2019)A New Perspective of Performa…An analytic derivation of the cost of deposit insurance and loan guarantees An application of modern option pricing theory (1977)Financial Intermediation and Delegated Monitoring (1984)Agency Costs, Net Worth, And Business Fluctuations (1988)Regulations, Market Structure, Institutions, and the Cost of Financial Intermediation (2003)Bank Concentration and Competition: An Evolution in the Making (2004)Benchmarking Financial Systems around the World (2012)Early warning of bank failure (1977)Introducing Recursive Partitioning for Financial Classification: The Case of Financial Distress (1985)Predicting corporate bankruptcy: where we stand? (2006)Are Competitive Banking Systems More Stable? (2009)Frailty Correlated Default (2009)Crime and Punishment: An Economic Approach (1968)FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY (1968)A MULTIVARIATE STATISTICAL ANALYSIS OF THE CHARACTERISTICS OF PROBLEM BANKS (1975)Prediction of financial distress: An empirical study of listed Chinese companies using data mining (2014)Financial Ratios As Predictors of Failure (1966)Corporate bankruptcy prediction: a high dimensional analysis (2017)Utilization of artificial intelligence in the banking sector: a systematic literature review (2022)Fuzzy sets (1965)Measuring the efficiency of decision making units (1978)Fuzzy sets (1996)Assessing bank efficiency and performance with operational research and artificial intelligence techniques: A survey (2009)Using artificial neural network models in stock market index prediction (2011)Financial Distress Prediction in an International Context: A Review and Empirical Analysis of Altman's Z‐ Score Model (2016)Financial Ratios and the Probabilistic Prediction of Bankruptcy (1980)A comparative study on base classifiers in ensemble methods for credit scoring (2016)Cost-sensitive boosted tree for loan evaluation in peer-to-peer lending (2017)CatBoost model and artificial intelligence techniques for corporate failure prediction (2021)Bank Runs, Deposit Insurance, and Liquidity (1983)Agency Costs of Free Cash Flow, Corporate Finance, and Takeovers (1986)Agency costs of free cash flow, corporate finance, and takeovers (1996)Liquidity risk management and credit supply in the financial crisis (2011)Bank size, capital, and systemic risk: Some international evidence (2015)Macroprudential Policy, Countercyclical Bank Capital Buffers, and Credit Supply: Evidence from the Spanish Dynamic Provisioning Experiments (2017)Credit Cycles (1997)The Theory of Bank Risk Taking and Competition Revisited (2005)Originate-to-distribute Model and the Subprime Mortgage Crisis (2010)Financial Innovation and Endogenous Growth (2013)Credit Supply and the Price of Housing (2015)Deposit Insurance, Risk, and Market Power in Banking (1988)Diversification in Banking: Is Noninterest Income the Answer? (2004)Bank activity and funding strategies: The impact on risk and returns☆ (2010)The Relationship between Liquidity Risk and Credit Risk in Banks (2012)Which banks are more risky? The impact of business models on bank stability (2014)The Roles of Corporate Governance in Bank Failures during the Recent Financial Crisis (2016)An explainable artificial intelligence approach for financial distress prediction (2022)Explainable artificial intelligence modeling to forecast bitcoin prices (2023)Machine learning techniques in bankruptcy prediction: A systematic literature review (2024)
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References

  • 2013How does capital affect bank performance during financial crises?1,690 cited
  • 2006Bankruptcy prediction in banks and firms via statistical and intelligent techniques – A review1,068 cited
  • 1993Size and performance of banking firms826 cited
  • 2012Credit Booms and Lending Standards: Evidence from the Subprime Mortgage Market733 cited
  • 1986An application of the cox proportional hazards model to bank failure559 cited
  • 2013Nontraditional banking activities and bank failures during the financial crisis540 cited
  • 1970PREDICTION OF BANK FAILURES501 cited
  • 2016Ensemble boosted trees with synthetic features generation in application to bankruptcy prediction419 cited
  • 2011Comparative analysis of data mining methods for bankruptcy prediction323 cited

Cited by

  • 2022Bankruptcy Prediction using the XGBoost Algorithm and Variable Importance Feature Engineering204 cited
  • 2022Operational Research and Artificial Intelligence Methods in Banking197 cited
  • 2022The role of Environmental, Social, and Governance (ESG) in predicting bank financial distress178 cited
  • 2019A New Perspective of Performance Comparison among Machine Learning Algorithms for Financial Distress Prediction169 cited
  • 2020It’s a Peoples Game, Isn’t It?! A Comparison Between the Investment Returns of Business Angels and Machine Learning Algorithms

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100 cited
  • 2023Credit growth, the yield curve and financial crisis prediction: Evidence from a machine learning approach100 cited
  • 2022No more black boxes! Explaining the predictions of a machine learning XGBoost classifier algorithm in business failure97 cited
  • 2022A novel ensemble feature selection method by integrating multiple ranking information combined with an SVM ensemble model for enterprise credit risk prediction in the supply chain95 cited
  • 2020The impact of the magnitude of service failure and complaint handling on satisfaction and brand credibility in the banking industry89 cited
  • 2020Determinants of corporate default risk in China: The role of financial constraints80 cited
  • 2020Predicting next day direction of stock price movement using machine learning methods with persistent homology: Evidence from Kuala Lumpur Stock Exchange74 cited
  • 2021Predicting bankruptcy of local government: A machine learning approach71 cited
  • 2022Gradient tree boosting and the estimation of production frontiers69 cited
  • 2022House price prediction using hedonic pricing model and machine learning techniques67 cited
  • 2019An ordinal classification framework for bank failure prediction: Methodology and empirical evidence for US banks66 cited
  • 2021Financial distress prediction by combining sentiment tone features64 cited