Forecast demand before liquidity becomes the bottleneck.

My forecasting post explores using historical transaction activity to estimate near-term remittance demand and the funding pressure that may follow.

Start with useful data

Aggregate activity by time, currency pair, and corridor. Examine calendar patterns, peak periods, and changes in behavior.

Evaluate before relying on it

Compare forecasts with observed demand over relevant horizons. Measure performance against a sensible baseline and monitor how results change when conditions shift.

Forecasts can support partner-liquidity planning and alerts for unusual surges or drops. They are planning inputs, not a guarantee of future demand. The original post discusses several modeling approaches, including Prophet, XGBoost, and recurrent time-series models.