Abstract: There are provided systems and methods for providing a merchant recommendation using multiple models. An example system may receive, at a product predictor, an input including a series of products and generate an output including a target product associated with the series of products. The system may generate, at a value evaluator, a value change associated with the target product based at least in part on the output, and generate, at the product predictor, a recommendation including the target product and the value change associated with the target product. The system may further generate, at a seasonal predictor, a seasonal prediction for the output in a future time frame based on the output, and generate, at the product predictor, an updated output including an updated target product based on the seasonal prediction for the output in the future time frame.

Abstract: There are provided systems and methods for streamlined and privacy protected data flows for entity onboarding with online data platforms. An online transaction processor or other service provider may provide computing services and platforms to entities including merchants for electronic transaction processing and other account services. To onboard entities with the transaction processor, the transaction processor may provide a merchant or user-specific experience and recommendations using a conversational AI service and chatbot. An AI engine may be trained to engage with users via chat dialogue, which may interact with users during onboarding and/or account lifecycle events based on the available services and products of the service provider. An intent of the entity may be classified by the AI engine and may be used to generate a recommendation including an action plan or the like of activities or steps for the entity to take.

Abstract: There are provided systems and methods for streamlined and privacy protected data flows for entity onboarding with online data platforms. An online transaction processor or other service provider may provide computing services and platforms to entities including merchants for electronic transaction processing and other account services. To onboard entities with the transaction processor, the transaction processor may provide a merchant or user-specific experience and recommendations using a conversational AI service and chatbot. An AI engine may be trained to engage with users via chat dialogue, which may interact with users during onboarding and/or account lifecycle events based on the available services and products of the service provider. An intent of the entity may be classified by the AI engine and may be used to generate a recommendation including an action plan or the like of activities or steps for the entity to take.

Abstract: There are provided systems and methods for providing a merchant recommendation using multiple models. An example system may receive, at a product predictor, an input including a series of products and generate an output including a target product associated with the series of products. The system may generate, at a value evaluator, a value change associated with the target product based at least in part on the output, and generate, at the product predictor, a recommendation including the target product and the value change associated with the target product. The system may further generate, at a seasonal predictor, a seasonal prediction for the output in a future time frame based on the output, and generate, at the product predictor, an updated output including an updated target product based on the seasonal prediction for the output in the future time frame.