SZodixStudyAcademic Library
ShelvesOpen access
Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated
Credit risk prediction with and without weights of evidence using quantitative learning models
14 references·1 citing·50 second hop
Credit risk prediction with and without weights of evidence using quantitative learning models (2024)Credit risk prediction with and without w…Machine Learning for Enhanced Credit Risk Assessment: An Empirical Approach (2023)Machine Learning for Enhanced…Network centrality effects in peer to peer lending (2022)Network centrality effects in…Machine learning for credit scoring: Improving logistic regression with non-linear decision-tree effects (2021)Machine learning for credit s…Machine Learning (ML) Technologies for Digital Credit Scoring in Rural Finance: A Literature Review (2021)Machine Learning (ML) Technol…A Comparative Assessment of Credit Risk Model Based on Machine Learning ——a case study of bank loan data (2020)A Comparative Assessment of C…Network based credit risk models (2019)Network based credit risk mod…PREDICTING THE DEFAULT RISK OF COMPANIES. COMPARISON OF CREDIT SCORING MODELS: LOGIT VS SUPPORT VECTOR MACHINES (2018)PREDICTING THE DEFAULT RISK O…A boosted decision tree approach using Bayesian hyper-parameter optimization for credit scoring (2017)A boosted decision tree appro…Using data mining to improve assessment of credit worthiness via credit scoring models (2011)Using data mining to improve …Statistical merging of rating models (2010)Statistical merging of rating…Weight of Evidence: A Review of Concept and Methods (2005)Weight of Evidence: A Review …A Methodology for Assessing Model Risk and Its Application to the Implied Volatility Function Model (2002)A Methodology for Assessing M…Statistical Classification Methods in Consumer Credit Scoring: A Review (1997)Statistical Classification Me…A k-Nearest-Neighbour Classifier for Assessing Consumer Credit Risk (1996)A k-Nearest-Neighbour Classif…Synergizing Generative AI and Machine Learning for Financial Credit Risk Forecasting and Code Auditing (2025)Synergizing Generative AI and…Risk Assessment in the Federal Government: Managing the Process (1983)Best evidence synthesis: An intelligent alternative to meta-analysis (1995)Use of Multicriteria Decision Analysis to Support Weight of Evidence Evaluation (2011)Instruments for Assessing Risk of Bias and Other Methodological Criteria of Published Animal Studies: A Systematic Review (2013)About and beyond leading uniqueness and belongingness: A systematic review of inclusive leadership research (2022)Neural network credit scoring models (2000)Credit rating analysis with support vector machines and neural networks: a market comparative study (2003)Decision tree analysis of construction fall accidents involving roofers (2014)Multivariate analysis of credit risk and bankruptcy research data: a bibliometric study involving different knowledge fields (1968–2014) (2016)Comprehensive review of text-mining applications in finance (2020)The Pricing of Options and Corporate Liabilities (1973)A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options (1993)Throwing away a billion dollars: the cost of suboptimal exercise strategies in the swaptions market (2001)Theory of rational option pricing (2005)Value–at–Risk Models (2009)Hedging stocks with oil (2019)FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY (1968)A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting (1997)Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research (2015)Statistical and machine learning models in credit scoring: A systematic literature survey (2020)CatBoost model and artificial intelligence techniques for corporate failure prediction (2021)Forecasting gold price with the XGBoost algorithm and SHAP interaction values (2021)A New Status Index Derived from Sociometric Analysis (1953)Financial Contagion (2000)Econometric measures of connectedness and systemic risk in the finance and insurance sectors (2012)COVID-19 pandemic risk and probability of loan default: evidence from marketplace lending market (2021)A systematic review of green finance in the banking industry: perspectives from a developing country (2022)Exploring the impact of green credit policies on corporate financing costs based on the data of Chinese A-share listed companies from 2008 to 2019 (2022)A Note on the Comparison of Logit and Discriminant Models of Consumer Credit Behavior (1980)Assessing Credit Card Applications Using Machine Learning (1987)Comprehensive review of different artificial intelligence-based methods for credit risk assessment in data science (2023)Credit Risk Prediction using Ensemble Machine Learning Algorithms (2023)Advancing credit risk modelling with Machine Learning: A comprehensive review of the state-of-the-art (2024)Comparing Predictive Accuracy (1994)Comparing Predictive Accuracy (1995)Credit default prediction from user-generated text in peer-to-peer lending using deep learning (2021)A two-stage hybrid credit risk prediction model based on XGBoost and graph-based deep neural network (2022)Big data, artificial intelligence and machine learning: A transformative symbiosis in favour of financial technology (2022)E-commerce in agri-food sector: a systematic literature review (2017)DGHNL: A new deep genetic hierarchical network of learners for prediction of credit scoring (2019)Machine Learning in Banking Risk Management: A Literature Review (2019)Machine Learning Models for Predicting Bank Loan Eligibility (2022)What? Why? When? How? Where? of Technology-Based Bibliometric Review (2023)Machine learning powered financial credit scoring: a systematic literature review (2025)PREDICTING BANKRUPTCY FOR FIRMS IN FINANCIAL DISTRESS (1990)Credit scoring and rejected instances reassigning through evolutionary computation techniques (2003)A comparative study on base classifiers in ensemble methods for credit scoring (2016)Predicting and Deterring Default with Social Media Information in Peer-to-Peer Lending (2017)The comparisons of data mining techniques for the predictive accuracy of probability of default of credit card clients (2008)Consumer credit-risk models via machine-learning algorithms (2010)
this work references cited by second hop

References

  • 1997Statistical Classification Methods in Consumer Credit Scoring: A Review1,039 cited
  • 2017A boosted decision tree approach using Bayesian hyper-parameter optimization for credit scoring770 cited
  • 2021Machine learning for credit scoring: Improving logistic regression with non-linear decision-tree effects438 cited
  • 2005Weight of Evidence: A Review of Concept and Methods419 cited
  • 1996A k-Nearest-Neighbour Classifier for Assessing Consumer Credit Risk286 cited
  • 2011Using data mining to improve assessment of credit worthiness via credit scoring models210 cited
  • 2020A Comparative Assessment of Credit Risk Model Based on Machine Learning ——a case study of bank loan data124 cited
  • 2002A Methodology for Assessing Model Risk and Its Application to the Implied Volatility Function Model112 cited
  • 2019Network based credit risk models107 cited
  • 2021Machine Learning (ML) Technologies for Digital Credit Scoring in Rural Finance: A Literature Review86 cited
  • 2010Statistical merging of rating models61 cited
  • 2023Machine Learning for Enhanced Credit Risk Assessment: An Empirical Approach49 cited
  • 2022Network centrality effects in peer to peer lending39 cited
  • 2018PREDICTING THE DEFAULT RISK OF COMPANIES. COMPARISON OF CREDIT SCORING MODELS: LOGIT VS SUPPORT VECTOR MACHINES21 cited

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work

Cited by

  • 2025Synergizing Generative AI and Machine Learning for Financial Credit Risk Forecasting and Code Auditing11 cited