We study in this paper the impact of the investor's behavior on the liquidity risk exposure of an investment fund. Using a new set of proprietary data on individual investors behavior, we split the net flows observed at the fund level, and compute different flow metrics related to the investor’s type. We use Hawkes processes to model flows’ persistence and forecast future flows at the investor level. We then use these forecasts to predict the future evolution of the fund’s asset under management.