#lifeeventdetection

Banks utilize a mix of data-based techniques to customize product offerings for a customer. Propensity modeling predicts the likelihood that a customer will take a behavior product action - like opening a high-yield savings account - by forecasting based on historical behavior patterns of similar customers. Life event detection discovers significant life events - like marriage, engagement in a new mortgage, or having a baby - that can signal the customer's potential for new life changes that may involve a financial decision. Real-time scoring then incorporates that context to generate real-time meaning, based on the current context of the customer (e.g., current balance, payments pending, prior support interaction) to determine the most relevant product to display to the customer at that moment. Combining these three base approaches allows banks to deliver the right product to the right customer at the right time, resulting in higher engagement and conversion.