Abstract: Logic may detect a malfunctioning payment interface on a customer's payment instrument. Logic may receive transaction data about at least one transaction performed via a payment instrument associated with a customer. The transaction data may indicate a payment interface of the payment instrument through which the customer conducted the at least one transaction and the payment instrument may comprise one or more payment interfaces. Logic may determine, by a model, based on the transaction data, a probability of a malfunction by at least one interface of the one or more payment interfaces. The model may be trained based on a pattern of transactions associated with malfunctioning payment instruments. Logic may compare the probability of the transaction against a threshold. And logic may determine whether to contact a customer associated with the payment instrument, based comparison of the probability of the transaction against the threshold.

Abstract: Logic may detect a malfunctioning payment interface on a customer's payment instrument. Logic may receive transaction data about at least one transaction performed via a payment instrument associated with a customer. The transaction data may indicate a payment interface of the payment instrument through which the customer conducted the at least one transaction and the payment instrument may comprise one or more payment interfaces. Logic may determine, by a model, based on the transaction data, a probability of a malfunction by at least one interface of the one or more payment interfaces. The model may be trained based on a pattern of transactions associated with malfunctioning payment instruments. Logic may compare the probability of the transaction against a threshold. And logic may determine whether to contact a customer associated with the payment instrument, based comparison of the probability of the transaction against the threshold.

Abstract: Logic may detect a malfunctioning payment interface on a customer's payment instrument. Logic may receive transaction data about at least one transaction performed via a payment instrument associated with a customer. The transaction data may indicate a payment interface of the payment instrument through which the customer conducted the at least one transaction and the payment instrument may comprise one or more payment interfaces. Logic may determine, by a model, based on the transaction data, a probability of a malfunction by at least one interface of the one or more payment interfaces. The model may be trained based on a pattern of transactions associated with malfunctioning payment instruments. Logic may compare the probability of the transaction against a threshold. And logic may determine whether to contact a customer associated with the payment instrument, based comparison of the probability of the transaction against the threshold.

Abstract: Logic may detect a malfunctioning payment interface on a customer's payment instrument. Logic may receive transaction data about at least one transaction performed via a payment instrument associated with a customer. The transaction data may indicate a payment interface of the payment instrument through which the customer conducted the at least one transaction and the payment instrument may comprise one or more payment interfaces. Logic may determine, by a model, based on the transaction data, a probability of a malfunction by at least one interface of the one or more payment interfaces. The model may be trained based on a pattern of transactions associated with malfunctioning payment instruments. Logic may compare the probability of the transaction against a threshold. And logic may determine whether to contact a customer associated with the payment instrument, based comparison of the probability of the transaction against the threshold.

Abstract: Logic may detect a malfunctioning payment interface on a customer's payment instrument. Logic may receive transaction data about at least one transaction performed via a payment instrument associated with a customer. The transaction data may indicate a payment interface of the payment instrument through which the customer conducted the at least one transaction and the payment instrument may comprise one or more payment interfaces. Logic may determine, by a model, based on the transaction data, a probability of a malfunction by at least one interface of the one or more payment interfaces. The model may be trained based on a pattern of transactions associated with malfunctioning payment instruments. Logic may compare the probability of the transaction against a threshold. And logic may determine whether to contact a customer associated with the payment instrument, based comparison of the probability of the transaction against the threshold.

Abstract: Logic may detect a malfunctioning payment interface on a customer's payment instrument. Logic may receive transaction data about at least one transaction performed via a payment instrument associated with a customer. The transaction data may indicate a payment interface of the payment instrument through which the customer conducted the at least one transaction and the payment instrument may comprise one or more payment interfaces. Logic may determine, by a model, based on the transaction data, a probability of a malfunction by at least one interface of the one or more payment interfaces. The model may be trained based on a pattern of transactions associated with malfunctioning payment instruments. Logic may compare the probability of the transaction against a threshold. And logic may determine whether to contact a customer associated with the payment instrument, based comparison of the probability of the transaction against the threshold.

Abstract: Logic may detect a malfunctioning payment interface on a customer's payment instrument. Logic may receive transaction data about at least one transaction performed via a payment instrument associated with a customer. The transaction data may indicate a payment interface of the payment instrument through which the customer conducted the at least one transaction and the payment instrument may comprise one or more payment interfaces. Logic may determine, by a model, based on the transaction data, a probability of a malfunction by at least one interface of the one or more payment interfaces. The model may be trained based on a pattern of transactions associated with malfunctioning payment instruments. Logic may compare the probability of the transaction against a threshold. And logic may determine whether to contact a customer associated with the payment instrument, based comparison of the probability of the transaction against the threshold.