Correlation is often misunderstood in financial risk management. It is used to measure the relationship between financial instruments, but it may not always be reliable, especially in areas like credit risk. Linear correlation cannot capture the complex non-linear relationships between real-world risk factors. To address this, an alternative approach called copulas is introduced to better model dependency. The article emphasizes the limitations of using correlation as a one-size-fits-all measure of dependence and highlights the importance of understanding subtle issues surrounding correlation in risk management.