Trust facilitates collaboration and coordination in teams and is paramount to achieving optimality in the absence of direct communication and formal coordination devices. We investigate the influence of agents' risk-attitudes on trust and the emergence of coordination in multi-agent environments. To that end, we consider Independent Risk-sensitive Policy Gradient, Risk-sensitive REINFORCE, RL-agents in repeated 2-agent coordination games (Stag-Hunt). We experimentally validate our hypothesis that the agents' risk-attitudes influence coordination and collaboration by influencing the agents' learning dynamics and can lead to efficient learning of Pareto optimal policies. This suggests that risk-sensitive agents could achieve better results in multi-agent task environments.