Research Article
Predicting the Performance of Rural Banks in Ghana Using Machine Learning Approach
Table 1
Various classes used by ARB to classify rural banks’ financial status (source: Association of Rural Banks Quarter Report, 2017).
| Rating range | Rating analysis | Interpretation of rating analysis | DMUs |
| 1.0–1.50 | Strong | Sound in all indicators, no supervisory response required | 99 | 1.50–2.50 | Satisfactory | Fundamentally sound with modest correctable weaknesses; supervisory responses limited | 330 | 2.50–3.50 | Fair (watch category) | Combination of weaknesses which if not addressed will become severe. Watch category | 164 | 3.50–4.50 | Marginal (signs of risk of failure) | Immoderate weaknesses: unless properly addressed, could impair future viability. Needs close supervision. | 64 | 4.50–5.0 | Unsatisfactory (high degree of failure evident) | High risk of failure in the near term. Needs constant supervision. | 0 |
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