In recent years, to satisfy diversified customer needs in the target market, an increasing number of brands have launched mass customization (MC) programs as one of their core operations strategies. The production process flexibility and personalization degree of customized products (i.e., the MC products) have thus become key to the success of MC schemes. In the meantime, however, considering the high market uncertainty in consumer preferences and the challenges from the production process, there are plenty of risks in MC operations. Hence, in this paper we develop a game-theoretic model consisting of an MC brand and an upstream manufacturer to identify the influences of supply chain finance (SCF) on MC programs. The influences brought by the risk attitudes of both MC brand and manufacturer are analyzed. Besides, an extra interest rate for raising the working capital for production (e.g., from the bank) at the manufacturing level is also considered in this paper to address the impact of cash flow shortage. We find that when the positive sensitivity of the market demand with respect to the modularity level of the MC product is sufficiently high, the optimal product modularity level of the MC product increases with the MC brand's degree of risk averse. In addition, it can also be observed that when both the market demand's positive sensitivity to the modularity level of the MC product and the MC brand's opportunity cost rate for placing the advance order are sufficiently high, any increase in the risk-averse degree of the MC brand or the manufacturer will lower the manufacturer's optimal wholesale price of the MC product as well as the MC brand's optimal rate of the advance order. Furthermore, the higher the interest that the manufacturer needs to pay (such as to the bank) for raising the working capital for the MC production process, the lower the optimal wholesale price of each finished MC product will be to help the manufacturer raise more money through the advance order placed by the MC brand. These observations complete the findings in the extant literature and provide important managerial insights into managing MC operations.