Accurately forecasting expenditures is crucial for budgeting and policy planning. This session presents a multi-task LSTM model designed to predict annual federal student aid (BAföG) expenditures for the current and next two years. Using 16 state-level time series, it addresses extreme intra-year volatility, strong seasonality, and the risk of overfitting with small datasets. Attendees will gain insights into overcoming these challenges and improving real-world time series forecasting models.