Cristian Cornejo Gaete

This study extends the existing Neutrosophic STATIS framework toward the dual analysis of relationships among financial variables observed over multiple periods. Financial uncertainty was operationalized as modeled indeterminacy derived from local temporal volatility and deviation from annual sectoral behavior. Each observation was represented through truth, indeterminacy, and falsity components and subsequently aggregated into a scalar neutrosophic score. Dual STATIS was then applied to annual matrices containing seven financial indicators for 25 Segment 1 Ecuadorian savings and credit cooperatives observed from 2016 to 2023. The resulting structure was compared with classical Dual STATIS applied to the original standardized indicators, and sensitivity analyses were conducted under alternative weighting specifications. The neutrosophic-score analysis revealed generally high temporal similarity among annual financial structures. ROA and ROE primarily defined the profitability dimension, LIQCOR and INTFIN characterized the second dimension, and DEP and SCC were principally represented by the third dimension. The first three dimensions explained 64.94% of the total inertia, compared with 64.23% in the classical analysis. The comparison showed that the neutrosophic transformation preserved the main profitability and institutional-activity relationships but modified the temporal similarity ordering, annual weight ranking, factorial configuration, and position of MORAMP. Sensitivity results indicated that the principal structural conclusions remained stable under moderate changes in the weighting parameters. The proposed approach provides a complementary exploratory tool for incorporating modeled indeterminacy into longitudinal financial-structure analysis and cooperative-sector supervision.

This article presents an innovative methodology that integrates Dual STATIS analysis with neutrosophic logic to evaluate the stability of the structure of relationships among financial variables in savings and credit cooperatives. The developed approach makes it possible to incorporate the uncertainty present in financial indicators and analyze their temporal evolution. Unlike classical STATIS, which focuses on similarity among cooperatives, the dual approach analyzes the covariance structure among the variables, identifying stable latent dimensions and turning points in the cooperative system. The results reveal patterns of structural stability and significant changes associated with relevant economic events, including the impact of the COVID-19 pandemic. The proposed methodology constitutes a useful alternative for strengthening financial supervision processes and supporting strategic decision-making in the cooperative sector.