Bayesian credit ratings: A random forest alternative approach

Imad Bou-Hamad

13 citations0/0 files storedCommunication in Statistics- Theory and Methods

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 Statistical Methods and Applications Credit Risk and Financial Regulations

Abstract

Cerciello and Giudici (2014 Cerciello, P., Giudici, P. (2014). Bayesian credit ratings. Commun. Stat. Theory Methods. 43:867–878.[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]) proposed a Bayesian approach to improve the ordinal variable selection in credit rating assessment. However, no comparison has been made with other methods and the predictive power was not tested. This study proposes an integrated framework of random forest (RF)-based methods and Bayesian model averaging (BMA) to validate and investigate the ordinal variable importance in evaluating credit risk and predicting default in greater depth. The proposed approach was superior to the Cerciello and Giudici method in terms of predictive accuracy and interpretability when applied to a European credit risk database.

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 — 13 citations exist upstream.

References

1968FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY 1997Statistical Classification Methods in Consumer Credit Scoring: A Review 2000Neural network credit scoring models 2003Credit rating analysis with support vector machines and neural networks: a market comparative study 2003Benchmarking state-of-the-art classification algorithms for credit scoring 2006Credit scoring with a data mining approach based on support vector machines 2000A survey of credit and behavioural scoring: forecasting financial risk of lending to consumers 1996A comparison of neural networks and linear scoring models in the credit union environment

Cited by

2022RETRACTED ARTICLE: Analyzing online consumer purchase psychology through hybrid machine learning

Explore the map →

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

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