Abstract: Features from historical transaction and customer data of a financial institution are calculated and/or extracted. Each customer is assigned to a given profitability cluster within each interval of time over a historical period of time based on the corresponding features. A self-supervised machine learning model is trained on the features to predict the clusters in a future interval of time. Features for a most-recent past interval of time are provided as input to the model and the model returns a predicted cluster for a given customer in a future interval of time. When the customer-assigned cluster in the most-recent past interval of time is a higher prioritized cluster than the predicted cluster for the future interval of time, a system of a financial institution (FI) is notified to take one or more mitigating in an attempt to prevent customer churn with the FI.

Abstract: A device for effecting heat transfer from a first fluid medium to a second fluid medium and for enhancing mixing and uniform distribution of the second fluid medium within the confines of a conduit. The device includes providing a core pipe for receiving the first fluid medium and a series of helically wound tubes in fluid communication with the core pipe along the longitudinal axis of the conduit. The second fluid passes within the conduit and is mixed by virtue of the static mixing effect of the helically wound tubes and engages in heat transfer as a result of the intimate contact between the second fluid, the core pipe and the helically wound tubes.