Emerging economies in Asia have become more vulnerable in the face of volatile capital flows and the reality of Trilemma constraints. The impact of the shifting perception of global risk, given the near-zero interest rates along with unconventional monetary policies (UMPs) in advanced economies after the global financial crisis, brought important challenges to monetary policy and central banking in ASEAN-4 countries. The extent of unintended effects is usually viewed as merely modest in many research studies. But the real extent of their pervasive effects and the challenges these central banks faced in order to respond appropriately are far greater than what most outside of these economies have imagined. This study provides a closer look into this policy view. In this paper, we provide empirical evidence that the policy rate gap measure in four emerging Southeast Asian countries—the Philippines, Indonesia, Malaysia, and Thailand—depict regime-switching policies of the central banks, mainly reflecting adjustments in monetary policies adapting to the magnitude of capital flows and driven by the risk-on and risk-off periods of global investor perception, within what we denote as an integrated central banking approach. We therefore tested and verified, using Markov-type regime-switching regression with time-varying transitional probabilities, that their policy rate gap is indeed regime-switching, and that indicators of global risk perception and, more recently, UMP-driven indicators of capital flows—including the shadow short rate, country risk premia, the EMBI+ Global indicators, the HSBC’s Risk-On, Risk-Off Index, and foreign ownership of local currency denominated assets—have an impact on the degree of response of market rates to policy. A regime-switching policy gap therefore has important implications on decisions toward an appropriate policy stance, since the degree of response of the market interest rates to the policy rate depends on which regime the economy is. At the same time, emerging drivers of the switching probabilities are variables that could be helpful if followed closely by monetary policymakers and could be used as early warning or leading indicators.