Predicting how many and which accounts will require manual preparation in the coming close, so staffing and deadlines can be planned rather than discovered.
Time-series forecasting on historical manual-preparation counts, with close-cycle type (month, quarter, year end) as a known regressor
pandas rolling averages by cycle type; Prophet with quarter-end and year-end as events