Abstract: A system and method for automation of flight functions across an aircraft cockpit provides an open systems architecture to meet next generation mission capabilities for increased aircrew effectiveness. A mission reasoner (MR) receives inputs from a vehicle health system, mission phase analysis, and external assets (wingmen) to build a decision network based on a knowledge database providing a decision aid to automate flight functions across the cockpit. The MR reduces crew workload by providing an automated decision aid and increased situational awareness of own ship aircraft and cooperating nearby vehicle health status relating to a phase of mission success. The MR provides predictive decisions and alternative actions to complete one or more desired mission objectives and determines predictive maintenance and future failures to optimize condition-based maintenance and reduce cost.

Abstract: In some aspects, the techniques described herein relate to a method including: receiving, at a transaction decisioning platform, a customer pre-approval notification; receiving, at the transaction decisioning platform, a stream of transactions, wherein the transactions are associated with a demand deposit account and the demand deposit account is associated with a customer; receiving, at the transaction decisioning platform, a total finance amount for the customer; applying a transaction eligibility rule to each transaction in the stream of transactions; determining, based on application of the transaction eligibility rule, that one of the transactions from the stream of transactions is eligible for a credit product; determining, based on a customer eligibility variable, that the customer is eligible for the credit product; and including the one of the transactions from the stream of transactions on an eligible transaction list.

Abstract: In some aspects, the techniques described herein relate to a method including: receiving, at an attribute and income platform, demand deposit account information associated with a demand deposit account; receiving, at the attribute and income platform, financial information of a customer associated with the demand deposit account; generating, by the attribute and income platform, a financial profile for the customer; generating, by a customer decisioning platform, a pre-approval of a credit product for the customer, wherein the customer pre-approval is based on the financial profile for the customer; providing, by the event streaming platform, a customer pre-approval topic; publishing the customer pre-approval to the customer pre-approval topic; and subscribing, by one or more processing platforms, to the customer pre-approval topic.

Abstract: A method may include a centralized recommendation engine computer program receiving a request for content to display on a mobile electronic device from an ad framework, and requesting offers for the customer based on the customer context from an offer interface platform; the offer interface platform querying a plurality of offer providers for offers, receiving a plurality of ranked offers and an offer identifier for each ranked offer from each of the plurality of offer providers and caching the plurality of ranked offers and an offer identifier for each ranked offer; the centralized recommendation engine computer program receiving the offer identifiers for the ranked offers and providing the offer identifiers for the ranked offers to the ad framework. The ad framework requests content for the ranked offers associated with the offer identifiers from the offer interface platform and generates a webpage with the content in the spaces.

Abstract: A method may include receiving a first recommendation request context from a first communication channel; routing the first recommendation request context to a channel recommendation engine for the first communication channel; receiving a first recommendation from the channel recommendation engine for the first communication channel; providing the first recommendation and the first recommendation request context to a centralized recommendation engine that trains a machine learning engine; providing the first recommendation to the first communication channel that provides the first recommendation to the first customer; receiving a first result of the first recommendation from the first communication channel; receiving a second recommendation request context from the first communication channel; routing the second recommendation request context to the centralized recommendation engine; receiving a second recommendation from the centralized recommendation engine; and providing the second recommendation to the fi

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 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 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. 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 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. 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 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.