Predicting Efficiency in Angolan Banks: A Two-Stage TOPSIS and Neural Networks Approach

This paper presents an efficiency assessment of the Angolan banks using Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS). TOPSIS is a multi-criteria decision-making technique similar to data envelopment analysis, which ranks a finite set of units based on the minimisation of distance from an ideal point and the maximisation of distance from an anti-ideal point. In this research, TOPSIS is used first in a two-stage approach to assess the relative efficiency of Angolan banks using the most frequent indicators adopted by the literature. Then, in the second stage, neural networks are combined with TOPSIS results as part of an attempt to produce a model for banking performance with effective predictive ability. The results reveal that variables related to cost structure have a prominent negative impact on efficiency. Findings also indicate that the Angolan banking market would benefit from higher level of competition between institutions.