SZodixStudyAcademic Library

Dashboard Shelves Open access My library Inbox Notes Write Learn Alerts

More

Ask your library Notifications Quick cite Review

Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated

Deep learning for credit scoring: Do or don’t? · Study

ArticleShelves

ArticleDeep learning for credit scoring: Do or don’t?

Björn Rafn Gunnarsson2021

OA

Articlegreen2021

Deep learning for credit scoring: Do or don’t?

Björn Rafn Gunnarsson · Seppe vanden Broucke · Bart Baesens · María Óskarsdóttir · Wilfried Lemahieu

241 citations·0/0 files stored·European Journal of Operational Research

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Financial Distress and Bankruptcy Prediction Forecasting Techniques and Applications Imbalanced Data Classification Techniques

Abstract

No abstract was published for this record.

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 241 citations exist upstream.

References

2014Scientific method: Statistical errors 2015Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research 2003Benchmarking state-of-the-art classification algorithms for credit scoring 2008The comparisons of data mining techniques for the predictive accuracy of probability of default of credit card clients 2017A boosted decision tree approach using Bayesian hyper-parameter optimization for credit scoring 2002Credit Scoring and Its Applications 2019Deep learning in business analytics and operations research: Models, applications and managerial implications 2018Credit Risk Analysis Using Machine and Deep Learning Models

Cited by

2022Operational Research and Artificial Intelligence Methods in Banking 2021Credit default prediction from user-generated text in peer-to-peer lending using deep learning 2022Deep reinforcement learning with the confusion-matrix-based dynamic reward function for customer credit scoring 2022Credit scoring methods: Latest trends and points to consider 2023Consumer credit risk assessment: A review from the state-of-the-art classification algorithms, data traits, and learning methods

Related works

Explore the map →

Papers that cite the same references — the relational fallback while embeddings are still backfilling.

2021Modelling customers credit card behaviour using bidirectional LSTM neural networksarticle · 5 shared references 2021Multi-classification assessment of bank personal credit risk based on multi-source information fusionarticle · 5 shared references 2022A deep learning model for behavioural credit scoring in banksarticle · 5 shared references 2018Dynamic ensemble classification for credit scoring using soft probabilityarticle · 4 shared references 2022Deep reinforcement learning with the confusion-matrix-based dynamic reward function for customer credit scoringarticle · 4 shared references 2019Best classification algorithms in peer-to-peer lendingarticle · 4 shared references

Details

Year2021

Typearticle

Published2021-03-10

VenueEuropean Journal of Operational Research

ISSN-L0377-2217

Languageen

Citations241

Files0 public / 0

ShelfFinancial Distress and Bankruptcy Prediction

Identifiers

doi10.1016/j.ejor.2021.03.006

openalex_workW3135286407

Links

Imported from OpenAlex (CC0) — nothing here is generated.

2024Deep Learning in Finance: A Survey of Applications and Techniques

2021Applying machine learning algorithms to predict default probability in the online credit market: Evidence from China

2023Hybrid neural network-based metaheuristics for prediction of financial markets: a case study on global gold market