<p>In the retail sector of Fintech, the new generations of customers demand digital solutions, including fast, cost-effective, and competitive interbank transaction services. The mechanism design and development of such services would require comprehensive evaluations based on substantial data and simulations of real-world environments. Our research explores the business rationale, the core theoretical perspective, and the adaptable algorithmic basis for low-risk real-time continuous (24/7/365) settlement that integrates different retail networks and the functions of queue management, multilateral netting, and data-based risk control. To evaluate network benefits, we adopt a time-to-time computational modeling approach based on reasonable experimental conditions and an empirical distribution of the data of small-value-transaction activities. We further investigate the heterogeneous behaviors of the individual banks within a network and show that all the factors of the transaction value thresholding, initial liquidity provision, and submission time of transactions can influence settlement and deferment costs across the network of member banks. Overall, we have demonstrated the liquidity-saving benefits of a hybrid settlement mechanism and a simulator of transaction settlement networks. Based on the computational modeling of the massive real data of interbank retail transactions in Sweden, the settlement mechanism has shown robust optimization performance, under which the settlement risks of individual banks are also under control.</p>