On the public citation graph
Credit Risk Management with Machine Learning-Based Assessments
0 signed · 33 inferred · view as graph
Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.
Is this your work? Sign in with ORCID and put your name on the
claims that are yours.
Reference health. See whether every reference in this work resolves to a
known work and none has been retracted — and get a dated CiteStamped
badge you can embed.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/s00521-022-07472-2openalex-extracted
Machine learning-driven credit risk: a systemic review
inferredcites →https://doi.org/10.1007/s10479-021-04114-zopenalex-extracted
Credit risk classification: an integrated predictive accuracy algorithm using artificial and deep neural networks
inferredcites →https://doi.org/10.1007/s13199-021-00778-0openalex-extracted
Survey of artificial intelligence approaches in the study of anthropogenic impacts on symbiotic organisms – a holistic view
inferredcites →https://doi.org/10.1007/s40747-022-00854-yopenalex-extracted
Credit risk assessment mechanism of personal auto loan based on PSO-XGBoost Model
inferredcites →https://doi.org/10.1007/s42979-021-00592-xopenalex-extracted
Machine Learning: Algorithms, Real-World Applications and Research Directions
inferredcites →https://doi.org/10.1016/j.asoc.2019.105936openalex-extracted
A Bolasso based consistent feature selection enabled random forest classification algorithm: An application to credit risk assessment
inferredcites →https://doi.org/10.1016/j.cesx.2019.100023openalex-extracted
Identification of flow regime in a bubble column reactor with a combination of optical probe data and machine learning technique
inferredcites →https://doi.org/10.1016/j.dss.2013.11.002openalex-extracted
Using a transactor/revolver scorecard to make credit and pricing decisions
inferredcites →https://doi.org/10.1016/j.eswa.2020.113925openalex-extracted
Utilizing historical data for corporate credit rating assessment
inferredcites →https://doi.org/10.1016/j.eswa.2020.113986openalex-extracted
A benchmark of machine learning approaches for credit score prediction
inferredcites →https://doi.org/10.1016/j.ins.2013.10.008openalex-extracted
Business intelligence in risk management: Some recent progresses
inferredcites →https://doi.org/10.1016/j.procs.2020.06.069openalex-extracted
A Comparative Assessment of Credit Risk Model Based on Machine Learning ——a case study of bank loan data
inferredcites →https://doi.org/10.1016/s2212-5671(15)00860-6openalex-extracted
Impact of Credit Risk Management
inferredcites →https://doi.org/10.1038/nrcardio.2014.94openalex-extracted
Effects of alcohol consumption on MI risk—evidence from INTERHEART
inferredcites →https://doi.org/10.1080/23322039.2022.2132638openalex-extracted
Big data and credit risk assessment: a bibliometric review, current streams, and directions for future research
inferredcites →https://doi.org/10.1109/cspa.2017.8064963openalex-extracted
Utilizing unsupervised weightless neural network as autonomous states classifier in reinforcement learning algorithm
inferredcites →https://doi.org/10.1109/eeeic.2018.8494594openalex-extracted
Centrifugal Pump Cavitation Detection Using Machine Learning Algorithm Technique
inferredcites →https://doi.org/10.1109/icctct.2018.8551134openalex-extracted
Machine Learning will Transfigure Medical Sector: A Survey
inferredcites →https://doi.org/10.1109/icecds.2017.8389769openalex-extracted
Credit risk analysis using machine learning classifiers
inferredcites →https://doi.org/10.1109/icoiact53268.2021.9563995openalex-extracted
CRAM: A Credit Risk Assessment Model by Analyzing Different Machine Learning Algorithms
inferredcites →https://doi.org/10.1111/asej.12225openalex-extracted
Influence of Egoistic and Altruistic Bequest Motives on the Willingness to Participate in Reverse Mortgages in China*
inferredcites →https://doi.org/10.1155/2021/6276155openalex-extracted
Financial Credit Risk Control Strategy Based on Weighted Random Forest Algorithm
inferredcites →https://doi.org/10.1155/2022/4060256openalex-extracted
Digital Universal Financial Credit Risk Analysis Using Particle Swarm Optimization Algorithm with Structure Decision Tree Learning‐Based Evaluation Model
inferredcites →https://doi.org/10.1186/s40537-020-00318-5openalex-extracted
Cybersecurity data science: an overview from machine learning perspective
inferredcites →https://doi.org/10.17762/ijritcc.v11i9s.7402openalex-extracted
A Framework for Credit Risk Prediction Using the Optimized-FKSVR Machine Learning Classifier
inferredcites →https://doi.org/10.21817/ijet/2016/v8i5/160805414openalex-extracted
Credit Risk Analysis and Prediction Modelling of Bank Loans Using R
inferredcites →https://doi.org/10.2478/jamsi-2023-0001openalex-extracted
Credit risk analysis using boosting methods
inferredcites →https://doi.org/10.32604/cmes.2021.015528openalex-extracted
A Contemporary Review on Drought Modeling Using Machine Learning Approaches
inferredcites →https://doi.org/10.3390/ijfs9030039openalex-extracted
Financial Inclusion in Emerging Economies: The Application of Machine Learning and Artificial Intelligence in Credit Risk Assessment
inferredcites →https://doi.org/10.3390/jcm11102866openalex-extracted
The Applications of Artificial Intelligence in Cardiovascular Magnetic Resonance—A Comprehensive Review
inferredcites →https://doi.org/10.54254/2755-2721/4/20230355openalex-extracted
Machine learning algorithms review
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.