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Sankore

Named after the University of Sankore in Timbuktu — one of the world’s oldest centres of learning. Every figure here is computed from work-level records in our own graph, never copied from a source’s summary count.

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Coverage is partial and says so. A country appears with its research output only once its works have been swept; until then the portal shows whatever the graph happens to hold for it and labels it as exactly that.

Machine Learning-Based Credit Default Prediction: Challenges, Concerns, and Model Comparisons

2026FUOYE Journal of Engineering and TechnologyJournalOpen access

10.4314/fuoyejet.v10i2.12 Full text1 citations

Authors

4 authors across 2 institutions in 1 country.

Joshua B. HassanFirst author
- Federal University Oye Ekiti (NG)
as printed: Joshua Bature Hassan
John Awoyemi Oloruntoba
- Federal University Oye Ekiti (NG)
Daniel Dauda Wisdom
- Federal University Oye Ekiti (NG)
Taiwo David AjayiSenior author
- Federal University of Agriculture, Abeokuta (NG)

Fields

Assignment is probabilistic — a work belongs to several fields in proportions.

Financial Distress and Bankruptcy Predictionlevel 3 · 0.96
Credit Risk and Financial Regulationslevel 3 · 0.01
Imbalanced Data Classification Techniqueslevel 3 · 0.00

Sources

Several sources describing one work is the point — it means the record rests on more than one authority.

openalexseen September 9, 2026
2026 · FUOYE Journal of Engineering and Technology · 1 citations
https://openalex.org/W7124264912

Machine Learning-Based Credit Default Prediction: Challenges, Concerns, and Model Comparisons · Sankore