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Machine learning in banking risk management: Mapping a decade of evolution
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References

  • 2021The PRISMA 2020 statement: an updated guideline for reporting systematic reviews13,845 cited
  • 2020The PRISMA 2020 statement: an updated guideline for reporting systematic reviews8,068 cited
  • 2004Procedures for Performing Systematic Reviews5,198 cited
  • 20132013 IEEE International Conference on Big Data1,390 cited
  • 2016Big data preprocessing: methods and prospects714 cited
  • 2019Machine Learning in Banking Risk Management: A Literature Review463 cited
  • 2004A General Approach to Integrated Risk Management with Skewed, Fat-tailed Risks*351 cited
  • 2020A Gated Recurrent Unit Approach to Bitcoin Price Prediction230 cited
  • 2020Machine learning techniques for credit risk evaluation: a systematic literature review226 cited
  • 2020Machine Learning for Financial Risk Management: A Survey203 cited
  • 2022How are reinforcement learning and deep learning algorithms used for big data based decision making in financial industries–A review and research agenda203 cited
  • 2019Machine Learning for Quantitative Finance Applications: A Survey199 cited
  • 2022Machine learning-driven credit risk: a systemic review195 cited
  • 2023Artificial Intelligence risk measurement176 cited
  • 2017An Artificial Neural Network and Bayesian Network model for liquidity risk assessment in banking

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134 cited
  • 2005Essentials of Financial Risk Management132 cited
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