Abstract: Disclosed are various embodiments for providing consistent user content. A first content request is received from a browser. Personalized content is then generated based at least in part on the first content request. A second content request is then received from the browser, the second content request including personally identifying information (PII). The alternative personalized content is then generated using the personally identifying information (PII). Either the personalized content or the alternative personalized content is elected to become the consistent personalized content. The consistent personalized content is provided to the browser in response to the second request.

Abstract: A system for instant qualification cross channel offer targeting is disclosed. The system may receive a plurality of personally identifiable information (PII) elements from at least one of a customer device or an affiliate system. The system may determine a credit authorization state in response to the PII element. The system may receive a first request to generate an offer from at least one of the customer device or the affiliate system. The system may generate the offer in response to an offer optimization model, the credit authorization state, and the first request to generate an offer. The system may hash the plurality of PII elements and determine a unique hash based on the plurality of PII elements. The system may associate the unique hash to the offer and store the offer as offer data.

Abstract: At least some embodiments are directed to a prediction system of software objects. The prediction system predicts a first aspect of a user profile utilizing a categorization machine learning model and a user activity profile, the user profile and the user activity profile are associated with a user. The user activity profile comprises a plurality of values associated with demographics and historical activity data of the user. The prediction system predicts a software object associated with the user profile utilizing an optimization machine learning model, the first aspect of the user profile, and a second aspect of the user profile. The software object is optimized with respect to at least one competitive interest between the user associated with the user profile and an entity associated with the software object. The prediction system outputs the software object to a client computing device of the user.

Abstract: Disclosed are various embodiments for providing consistent user content. A first content request is received from a browser. Personalized content is then generated based at least in part on the first content request. The personalized content is returned to the browser and saved in association with the unique device identifier and the session identifier. A second content request is then received from the browser, the second content request including personally identifying information (PII). The saved personalized content is searched and alternative personalized content is then generated using the personally identifying information (PII). An inconsistency between the personalized content and the alternative personalized content is then resolved to generate consistent personalized content. Finally, the consistent personalized content is provided to the browser in response to the second request.

Abstract: At least some embodiments are directed to a prediction system of software objects. The prediction system predicts a first aspect of a user profile utilizing a categorization machine learning model and a user activity profile, the user profile and the user activity profile are associated with a user. The user activity profile comprises a plurality of values associated with demographics and historical activity data of the user. The prediction system predicts a software object associated with the user profile utilizing an optimization machine learning model, the first aspect of the user profile, and a second aspect of the user profile. The software object is optimized with respect to at least one competitive interest between the user associated with the user profile and an entity associated with the software object. The prediction system outputs the software object to a client computing device of the user.

Abstract: A system for instant qualification cross channel offer targeting is disclosed. The system may receive a plurality of personally identifiable information (PII) elements from at least one of a customer device or an affiliate system. The system may determine a credit authorization state in response to the PII element. The system may receive a first request to generate an offer from at least one of the customer device or the affiliate system. The system may generate the offer in response to an offer optimization model, the credit authorization state, and the first request to generate an offer. The system may hash the plurality of PII elements and determine a unique hash based on the plurality of PII elements. The system may associate the unique hash to the offer and store the offer as offer data.

Abstract: A system for instant qualification cross channel offer targeting is disclosed. The system may receive a plurality of personally identifiable information (PII) elements from at least one of a customer device or an affiliate system. The system may determine a credit authorization state in response to the PII element. The system may receive a first request to generate an offer from at least one of the customer device or the affiliate system. The system may generate the offer in response to an offer optimization model, the credit authorization state, and the first request to generate an offer. The system may hash the plurality of PII elements and determine a unique hash based on the plurality of PII elements. The system may associate the unique hash to the offer and store the offer as offer data.