This paper proposes a real-time process quality control methodology for Business Activity Monitoring by estimating the risk level (RL) and its confidence intervals (CIs) of an ongoing process. We formulate algorithms to estimate RL and CIs as a continuous measure, based on the partial information of the ongoing process. By using the proposed method, RL and CIs can be estimated in real-time during process execution, so as to effectively control the process quality. Furthermore, it is feasible to generate early warnings based on the status of RL and CIs. We also provided experiments to compare the proposed method with existing approaches, which showed that the proposed method can detect the risks of the ongoing process more precisely and even earlier than existing approaches.