Adaptation to the altman z2 score model as an indicator of financial stability behavior

Abstract

Banking institutions also monitor their financial stability, which is of paramount importance due to the nature of their business and their contribution to the flow of money in the economy. To this end, in some countries, they use traditional financial analysis methods focused on composition and financial trends, as well as the Altman Z-Score insolvency estimation method, in its base version (Z) and variants (Z1 and Z2). The aim of this research is to implement the adaptation to the Altman Z2-Score model as an indicator of financial stability behavior, applied to a bank in Nicaragua for the year 2023. The synthetic analytical method was used, with a pragmatic paradigm and therefore a mixed approach, and its design is concurrent triangulation. The qualitative aspect is supported by interviews with financial experts, while the quantitative aspect relies on historical financial statements data from the Superintendency of Banks and Other Financial Institutions (SIBOIF) for the period 2016-2022. The information was systematized to apply the multiple linear regression model, which explained the incidence of the independent variables: liquidity (X1), profitability (X2 and X3), and debt (X4), on the final score of financial stability (Z2) as the dependent variable. A new formula was obtained: Z3 = -0.275 + 1.090 X1 + 0.596 X2 + 0.840 X3 + 2.371 X4, based on banking terminology and with a decision criterion grounded in the minimum solvency index established by SIBOIF for banking institutions. The bank in Nicaragua under study exceeded the decision criterion, indicating that it is a solvent institution for the year 2023.