This paper proposes using Gram-Charlier Type A probability distributions to measure solvency risk. The method assesses the likelihood of a bank's solvency falling below the minimum ratio set by regulators. Applied to 15 banks in Colombia, the study reveals the importance of considering the proximity of the Capital Adequacy Ratio (CAR) to the regulatory minimum and the probability distribution of solvency changes. Gram-Charlier Type A functions offer a better fit than the normal distribution. These findings hold significance for regulators and decision-makers, emphasizing the need to incorporate suitable measures for assessing solvency risk in banks.