Importance

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Abstract

A method of monitoring cashless transaction data includes extracting transaction history data for a merchant within a first predetermined time period from a transaction data storage. A plurality of forecast models that forecast transaction patterns for the merchant over the first predetermined time period are provided, each forecast model of the first plurality having a different forecast period. The forecast models may be constructed according to a Holt-Winters time-series forecast. The forecast model which most accurately forecasts periodic fluctuations in the transaction history data is selected, and a first forecast of transactions for the merchant for a first forecast period outside the first predetermined time period is provided. A score comparing the forecast with actual data for the first forecast period is further provided. An alert is generated when the score exceeds a predetermined threshold. Also disclosed are a computer and recording medium to carry out the method.

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First Claim