Abstract: Various methods, apparatuses/systems, and media for implementing a payment application module for searching billets are disclosed. A plurality of data sources include customer profile data, customer payment history data, biller information data, and biller directory data. A processor operatively coupled to the plurality of data sources via a communication network builds a customer profile service area popularity model based on the customer profile data, customer payment history data, biller information data, and biller directory data; receives search query data for searching a biller; builds a biller search machine learning model to optimize weights applied to the search query data; and ranks search results by utilizing the machine learning model in response to the search query data.

Abstract: Various methods, apparatuses/systems, and media for implementing a payment application module for searching billets are disclosed. A plurality of data sources include customer profile data, customer payment history data, biller information data, and biller directory data. A processor operatively coupled to the plurality of data sources via a communication network builds a customer profile service area popularity model based on the customer profile data, customer payment history data, biller information data, and biller directory data; receives search query data for searching a biller; builds a biller search machine learning model to optimize weights applied to the search query data; and ranks search results by utilizing the machine learning model in response to the search query data.

Abstract: Systems and methods for machine-assisted document input are disclosed. In one embodiment, a method may include a data extraction application executed by a computer processor: receiving an image of a document/email; generating a transcript of the document/email, wherein the transcript comprises a plurality of text groups from the document/email and a location for each text group in the document/email; identifying a vendor associated with the document/email based on contents of one of the text groups and/or one of the locations of the one of one of the text groups; retrieving a vendor-specific machine learning model for the vendor; associating each of the plurality of locations in the document/email with a billing field using the vendor-specific machine learning model; extracting each of the text groups into one of the billing fields based on the association; and transmitting the billing fields with the extracted data to a user electronic device.

Abstract: An apparatus comprises a memory and a processor. The memory is operable to store information associated with a user account. The processor can receive a message indicating that a transaction associated with a card has occurred and receive a first input indicating that the transaction is fraudulent. The processor can receive a second input indicating that a report should be filed and present, on a display, a plurality of questions to determine whether the card has been stolen. The processor can receive a third input indicating an answer to each of the plurality of questions and present, on the display, an affidavit. The processor can receive a fourth input indicating the affidavit has been electronically signed and present, on the display, a confirmation message indicating that the report has been filed.

Abstract: An apparatus comprises a memory and a processor. The memory is operable to store information associated with a user account. The processor can receive a message indicating that a transaction associated with a card has occurred and receive a first input indicating that the transaction is fraudulent. The processor can receive a second input indicating that a report should be filed and present, on a display, a plurality of questions to determine whether the card has been stolen. The processor can receive a third input indicating an answer to each of the plurality of questions and present, on the display, an affidavit. The processor can receive a fourth input indicating the affidavit has been electronically signed and present, on the display, a confirmation message indicating that the report has been filed.

Abstract: An apparatus comprises a memory and a processor. The memory is operable to store information associated with a user account. The processor can receive a message indicating that a transaction associated with a card has occurred and receive a first input indicating that the transaction is fraudulent. The processor can receive a second input indicating that a report should be filed and present, on a display, a plurality of questions to determine whether the card has been stolen. The processor can receive a third input indicating an answer to each of the plurality of questions and present, on the display, an affidavit. The processor can receive a fourth input indicating the affidavit has been electronically signed and present, on the display, a confirmation message indicating that the report has been filed.

Abstract: An apparatus comprises a memory and a processor. The memory is operable to store information associated with a user account. The processor can receive a message indicating that a transaction associated with a card has occurred and receive a first input indicating that the transaction is fraudulent. The processor can receive a second input indicating that a report should be filed and present, on a display, a plurality of questions to determine whether the card has been stolen. The processor can receive a third input indicating an answer to each of the plurality of questions and present, on the display, an affidavit. The processor can receive a fourth input indicating the affidavit has been electronically signed and present, on the display, a confirmation message indicating that the report has been filed.

Abstract: According to one embodiment, an apparatus comprising a memory and a processor is provided. The memory is operable to store information associated with a user account. The processor can receive a message indicating that a transaction associated with a card has occurred and receive a first input indicating that the transaction is fraudulent. The processor can receive a second input indicating that a report should be filed and present, on a display, a plurality of questions to determine whether the card has been stolen. The processor can receive a third input indicating an answer to each of the plurality of questions and present, on the display, an affidavit. The processor can receive a fourth input indicating the affidavit has been electronically signed and present, on the display, a confirmation message indicating that the report has been filed.

Abstract: According to one embodiment, an apparatus comprising a memory and a processor is provided. The memory is operable to store information associated with a user account. The processor can receive a message indicating that a transaction associated with a card has occurred and receive a first input indicating that the transaction is fraudulent. The processor can receive a second input indicating that a report should be filed and present, on a display, a plurality of questions to determine whether the card has been stolen. The processor can receive a third input indicating an answer to each of the plurality of questions and present, on the display, an affidavit. The processor can receive a fourth input indicating the affidavit has been electronically signed and present, on the display, a confirmation message indicating that the report has been filed.

Abstract: A multi-stage filtering process and system for fraud detection is disclosed. The process includes one or more preliminary filtration stages followed by one or more additional filtration stages that provide for enhanced screening for fraudulent activity. In one such embodiment the preliminary filtration provides for evaluating financial transactions based on financial transaction attribute data and secondary filtration provides for further evaluating the financial transactions based on a customer's account event data. Over a plurality of transactions, a portion of the transactions are cleared for processing (e.g., deemed not likely fraudulent or of too low value to continue processing) after each filtration stage. As such, acceptable transactions are not unnecessarily scrutinized. In specific embodiments, filtration is based on financial transaction data and account event data.

Abstract: A multi-stage filtering process and system for fraud detection is disclosed. The process includes one or more preliminary filtration stages followed by one or more additional filtration stages that may include velocity filters that provide for enhanced screening for fraudulent activity. Over a plurality of transactions, a portion of the transactions are cleared for processing (e.g., deemed not likely fraudulent or of too low value to continue processing) after each filtration stage. As such, acceptable transactions are not unnecessarily scrutinized.

Abstract: A multi-stage filtering process and system for fraud detection is disclosed. The multi-stage filtering process allows for the ability to dynamically increase/decrease server capacity, as well as application capacity to support fraud detection activities. The system monitors the queues of the transactions being made using various channels, and responds by adjusting the server and application resources needed for performing pre-filtering on the transactions in the queues. The invention allows for the fraud detection systems to maintain the capacity necessary to examine, at some level, if one or more of the transactions being processed by a financial institution are potentially fraudulent. The capacity can be changed during times of high and low volumes, thus allowing the allocation of resources based on transaction volume, which reduces the computing, energy, labor, etc. costs associated with fraud detection systems without losing the ability to detect almost all of the fraudulent transactions occurring.

Abstract: A multi-stage filtering process and system for fraud detection is disclosed. The process includes one or more preliminary filtration stages followed by one or more additional filtration stages that may include customer history filters that provide for enhanced screening for fraudulent activity. Over a plurality of transactions, a portion of the transactions are cleared for processing (e.g., deemed not likely fraudulent or of too low value to continue processing) after each filtration stage. As such, acceptable transactions are not unnecessarily scrutinized.

Abstract: A multi-stage filtering process and system for fraud detection is disclosed. The process includes one or more preliminary filtration stages followed by one or more additional filtration stages that may include velocity filters that provide for enhanced screening for fraudulent activity. Over a plurality of transactions, a portion of the transactions are cleared for processing (e.g., deemed not likely fraudulent or of too low value to continue processing) after each filtration stage. As such, acceptable transactions are not unnecessarily scrutinized.

Abstract: A multi-stage filtering process and system for fraud detection is disclosed. The process includes one or more preliminary filtration stages followed by one or more additional filtration stages that provide for enhanced screening for fraudulent activity. Over a plurality of transactions, a portion of the transactions are cleared for processing or marked as not fraudulent (e.g., deemed not likely fraudulent or of too low a value to continue analyzing) after each filtration stage. As such, acceptable transactions are not unnecessarily scrutinized.

Abstract: A multi-stage filtering process and system for fraud detection is disclosed. The process includes one or more preliminary filtration stages followed by one or more additional filtration stages that provide for enhanced screening for fraudulent activity. Over a plurality of transactions, a portion of the transactions are cleared for processing (e.g., deemed not likely fraudulent or of too low value to continue processing) after each filtration stage. As such, acceptable transactions are not unnecessarily scrutinized. Methods include receiving transaction data; filtering the transaction data based on a first stage filtration to produce filtered data; enriching the filtered data with geo-positioning data to produce enriched data; and filtering the enriched data based on other attributes to indentify a possible fraud.

Abstract: A multi-stage filtering process and system for fraud detection is disclosed. The process includes one or more preliminary filtration stages followed by one or more additional filtration stages that may include customer history filters that provide for enhanced screening for fraudulent activity. Over a plurality of transactions, a portion of the transactions are cleared for processing (e.g., deemed not likely fraudulent or of too low value to continue processing) after each filtration stage. As such, acceptable transactions are not unnecessarily scrutinized.

Abstract: A multi-stage filtering process and system for fraud detection is disclosed. The process includes one or more preliminary filtration stages followed by one or more additional filtration stages that provide for enhanced screening for fraudulent activity. Over a plurality of transactions, a portion of the transactions are cleared for processing (e.g., deemed not likely fraudulent or of too low value to continue processing) after each filtration stage. As such, acceptable transactions are not unnecessarily scrutinized. Another user of the multi-stage filtering process and system is to detect false positive fraud alerts produced by other systems. By reducing the prevalence of false positives, the process and system saves the financial institution costs associated with conducting expensive screening of valid transactions and saves the customers inconvenience and frustration of having valid transactions declined.

Abstract: A multi-stage filtering process and system for fraud detection is disclosed. The process includes one or more preliminary filtration stages followed by one or more additional filtration stages that provide for enhanced screening for fraudulent activity. In one such embodiment the preliminary filtration provides for evaluating financial transactions based on financial transaction attribute data and secondary filtration provides for further evaluating the financial transactions based on a customer's account event data. Over a plurality of transactions, a portion of the transactions are cleared for processing (e.g., deemed not likely fraudulent or of too low value to continue processing) after each filtration stage. As such, acceptable transactions are not unnecessarily scrutinized. In specific embodiments, filtration is based on financial transaction data and account event data.

Abstract: A multi-stage filtering process and system for fraud detection is disclosed. The multi-stage filtering process allows for the ability to dynamically increase/decrease server capacity, as well as application capacity to support fraud detection activities. The system monitors the queues of the transactions being made using various channels, and responds by adjusting the server and application resources needed for performing pre-filtering on the transactions in the queues. The invention allows for the fraud detection systems to maintain the capacity necessary to examine, at some level, if one or more of the transactions being processed by a financial institution are potentially fraudulent. The capacity can be changed during times of high and low volumes, thus allowing the allocation of resources based on transaction volume, which reduces the computing, energy, labor, etc. costs associated with fraud detection systems without losing the ability to detect almost all of the fraudulent transactions occurring.