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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.

CREDIT RISK ANALYSIS: AN ASSESSMENT OF THE PERFORMANCE OF SIX MACHINE LEARNING TECHNIQUES IN CREDIT SCORING MODELLING

2024FUDMA Journal of SciencesJournalOpen access

10.33003/fjs-2024-0806-2893 Full text5 citations

Authors

6 authors across 3 institutions in 2 countries.

Ali Musa MuhammadFirst author
as printed: Abba Bello Muhammad
Ishaq O. Olawoyin
- Ahmadu Bello University (NG)
Abubakar Yahaya
- Usmanu Danfodiyo University (NG)
Shehu Usman Gulumbe
as printed: S. U. Gulumbe
Abdullahi. A. Muhammad
Iliyasu Abubakar SalisuSenior author

Fields

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

Financial Distress and Bankruptcy Predictionlevel 3 · 1.00
Credit Risk and Financial Regulationslevel 3 · 0.99
Imbalanced Data Classification Techniqueslevel 3 · 0.99

Sources

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

openalexseen September 9, 2026
2024 · FUDMA Journal of Sciences · 5 citations
https://openalex.org/W4406545763

CREDIT RISK ANALYSIS: AN ASSESSMENT OF THE PERFORMANCE OF SIX MACHINE LEARNING TECHNIQUES IN CREDIT SCORING MODELLING · Sankore