The article explores ways to measure risks in financial positions for solvency requirements. It shows that current risk measures often don't meet consistency standards, so new methods are suggested. The study also looks at the impact of errors in estimating data on risk measures, introducing a new concept called residual estimation risk. Different approaches are tested to reduce this risk, with promising results shown in simulations. The research highlights the importance of considering both parameter and model uncertainty when calculating solvency capital requirements.