Extensive research has been devoted to the modeling and analysis of systematic risk in various literature. However, these studies have predominantly focused on system failures or measuring systematic risk, disregarding the need for well-defined principles that underpin systematic risks. In our effort to reassess the concept of systematic risk, we adopt an innovative approach that identifies the defining characteristics of systematic risks, which remain invariant regardless of the number of losses or any manipulations within a finite set of losses. To explore these principles, we find the framework of risk management on sequences in Banach spaces to be particularly suitable. In establishing these principles, we introduce the notion of "systematic compatibility," signifying invariance to variations in finite changes within a sequence of losses. Consequently, we observe that while systematic risk often possesses an implicit representation in the risk space, it exhibits a distinct and explicit representation in the bi-dual space. Moreover, we introduce systematic compatible risk measures and establish their dual characterization. As a result, we demonstrate that risk measurement naturally splits into a summation of systematic and unsystematic components. In practical applications, we employ these measures to address risk management problems, with a specific emphasis on risk pooling scenarios. In revisiting the traditional "principle of insurance" (POI), we propose an extension called the "principle of pooling" (POP). By showing that the principle of pooling holds if and only if the systematic risk is secure, we delve into this novel concept. Time allowing, we provide illustrative examples that facilitate the calculation of systematic risk within risk pools using common shock models.