Abstract: Embodiments of the invention are directed to systems, methods, and computer program products for providing intelligent proactive identification of, and protection against, malfeasant data collection, user device control, or user account access. The invention utilizes a continuous data analysis technique in order to recognize patterns in device data and network communications indicative of remote device control requests, and responds to these identified data points by implemented an automated solution to protect users against unauthorized access of their devices or accounts.

Abstract: Aspects of the disclosure relate to a payment device to detect real-time suspicious payment cards. Prior to a transaction, a payment device detects suspicious payment cards based on captured images of the payment card. An alert may be generated upon detection of any suspicious or fraudulent payment card. In some arrangements, institutions may share information regarding suspicious payment cards to prevent fraud. The payment device may utilize machine learning models or machine learning capabilities to detect suspicious payment cards. A characterization score may be generated and used to determine if a payment card is suspicious. The characterization scores may be updated based on different card issuer criteria and transaction use of each payment card.

Abstract: Embodiments of the invention are directed to systems, methods, and computer program products for providing intelligent proactive identification of, and protection against, malfeasant data collection, user device control, or user account access. The invention utilizes a continuous data analysis technique in order to recognize patterns in device data and network communications indicative of remote device control requests, and responds to these identified data points by implemented an automated solution to protect users against unauthorized access of their devices or accounts.

Abstract: Embodiments of the invention are directed to systems, methods, and computer program products for providing intelligent proactive identification of, and protection against, malfeasant data collection, user device control, or user account access. The invention utilizes a continuous data analysis technique in order to recognize patterns in device data and network communications indicative of remote device control requests, and responds to these identified data points by implemented an automated solution to protect users against unauthorized access of their devices or accounts.

Abstract: Aspects of the disclosure relate to a payment device to detect real-time suspicious payment cards. Prior to a transaction, a payment device detects suspicious payment cards based on captured images and determined indicia of the payment card. An alert may be generated upon detection of any suspicious or fraudulent payment card. In some arrangements, the payment device may utilize machine learning models or machine learning capabilities to detect suspicious payment cards. A characterization score may be generated and used to determine if a payment card is suspicious. The characterization scores may be updated based on different card issuer criteria and transaction use of each payment card.

Abstract: Aspects of the disclosure relate to a payment device to detect real-time suspicious payment cards. Prior to a transaction, a payment device detects suspicious payment cards based on captured images of the payment card. An alert may be generated upon detection of any suspicious or fraudulent payment card. In some arrangements, institutions may share information regarding suspicious payment cards to prevent fraud. The payment device may utilize machine learning models or machine learning capabilities to detect suspicious payment cards. A characterization score may be generated and used to determine if a payment card is suspicious. The characterization scores may be updated based on different card issuer criteria and transaction use of each payment card.

Abstract: Aspects of the disclosure relate to a payment device to detect real-time suspicious payment cards. Prior to a transaction, a payment device detects suspicious payment cards based on captured images of the payment card. An alert may be generated upon detection of any suspicious or fraudulent payment card. In some arrangements, the payment device may utilize machine learning models or machine learning capabilities to detect suspicious payment cards. A characterization score may be generated and used to determine if a payment card is suspicious. The characterization scores may be updated based on different card issuer criteria and transaction use of each payment card.

Abstract: Embodiments of the invention are directed to systems, methods, and computer program products for providing intelligent proactive identification of, and protection against, malfeasant data collection, user device control, or user account access. The invention utilizes a continuous data analysis technique in order to recognize patterns in device data and network communications indicative of remote device control requests, and responds to these identified data points by implemented an automated solution to protect users against unauthorized access of their devices or accounts.

Abstract: An event monitor includes an event counter for counting one or more preselected events detected by an event counter. The events are counted for successive time periods and an indication of system stability is calculated to detect possible error conditions. The indication of system stability is calculated by taking a nonweighted or weighted sum of the total number of events counted in the current time period, the total number of events counted in all time periods monitored, and the difference between the total number of events counted in the current time period and the total number of events counted in the preceding time period. In this manner, the event monitor is able to identify possible error conditions more quickly than systems using rate thresholding so that remedial action may be initiated sooner.

Abstract: An event monitor includes an event counter for counting one or more preselected events detected by an event counter. The events are counted for successive time periods and an indication of system stability is calculated to detect possible error conditions. The indication of system stability is calculated by taking a nonweighted or weighted sum of the total number of events counted in the current time period, the total number of events counted in all time periods monitored, and the difference between the total number of events counted in the current time period and the total number of events counted in the preceding time period. In this manner, the event monitor is able to identify possible error conditions more quickly than systems using rate thresholding so that remedial action may be initiated sooner.