AbstractThis paper proposes new risk measures by accurately estimating the components of solvency risk and focusing on prudential policy implementation. We use semi‐nonparametric statistics to model the stylised facts of the probability density functions, particularly the higher‐order moments of three variables: the solvency decline rate, the tier decline rate and the portfolio growth rate. The proposed measures allow the evaluation of the impact of expansionary monetary policy on the risk‐taking transmission channel and implementation of the minimum solvency ratios required by banking regulators based on the estimation of quantile risk metrics. Using a database of Colombian solvency indicators, we show that the liquidity injection measures employed in response to the COVID‐19 pandemic led to a significant increase in portfolio risk in the banking system. The proposed methodology is suitable for micro‐ and macroprudential regulation at different levels of portfolio risk aggregation.