Commercial banks might profit from the adoption of methods widely used in network theory. A decision making process might become biased if one disregards network effects within the corporate client portfolio. This paper models the phenomenon of customer attrition by generating a weighted and directed network of corporate clients linked by financial transactions. During the numerical study of the agent-based toy model we demonstrate that multiple steady states may exist. The statistical properties of the distinct steady states show similarities. We show that most companies of the same community choose the same bank in the steady state. In contrast to the case for the steady state of the Barabási–Albert network, market shares in this model equalize by network size. When modeling customer attrition in the network of 3 × 10⁵ corporate clients, none of the companies followed the behavior of the initial switcher in three quarters of the simulations. The number of switchers exceeded 20 in 1% of the cases. In the worst-case scenario a total of 688 companies chose a competitor bank. Significant network effects have been discovered; high correlation prevailed between the degree of the initial switcher and the severity of the avalanche effect. This suggests that the position of the corporate client in the network might be much more important than the underlying properties (industry, size, profitability, etc) of the company.