Auditing data containing sensitive data are stored in a data structure comprising data objects. Each data object comprises one or more pairs of a name and a value. Pairs that are flagged or identified as containing sensitive data are partially encrypted; the value is encrypted using an asymmetric key and the name corresponding to the encrypted value remains unencrypted. Some pairs that are not flagged or identified as containing sensitive data are left unencrypted. Unencrypted data may be stored in the partially encrypted auditing data as plain text. The auditing data may be analyzed to generate business metrics and identify application errors. The auditing data may also be queried, and data objects containing unencrypted pairs and/or partially encrypted pairs may be returned based on matching unencrypted names and/or values to the data query.

Embodiments of the invention provide a method, system and computer program product for online ordering using conversational interfaces. In an embodiment of the invention, the method includes storing customer information corresponding to a customer and responsive to receiving a message with text or speech and an image from the customer, identifying an intent type from the text or speech using Natural Language Understanding, identifying a product or service from the image using image classification techniques and transmitting a product detail message to the customer with the product or service and corresponding pricing using Natural Language Generation. The method further includes responsive to receiving an affirmative message from the customer in response to the product detail message identified as affirmative using Natural Language Understanding, automatically completing a purchase of the product or service with the customer information and transmitting a receipt message to the customer with an order receipt.

A system for interfacing with a decisioning service from a third-party domain. A backend system may receive a request to interface with the decisioning service to generate a prequalification result for a user for a specified product, in response to the actuation of a button included in a third-party web domain rendering a product. The backend system may execute a call on a website of the decisioning service. The backend system may receive the product information from the button. The backend system may generate the website within the third-party domain, including a request for information about the user, in response to executing the call to the website. The backend system may transmit a request for generating prequalification result for the product to the decisioning service. The backend system may receive the prequalification result from the decisioning service.

A system for interfacing with a decisioning service from a third-party domain. A backend system may receive a request to interface with the decisioning service to generate a prequalification result for a user for a specified product, in response to the actuation of a button included in a third-party web domain rendering a product. The backend system may execute a call on a website of the decisioning service. The backend system may receive the product information from the button. The backend system may generate the website within the third-party domain, including a request for information about the user, in response to executing the call to the website. The backend system may transmit a request for generating prequalification result for the product to the decisioning service. The backend system may receive the prequalification result from the decisioning service.

Encryption is performed at the field level within a data object, in response to an encryption indicator. Encrypted fields are nulled or zeroed out and the encrypted values are stored in encryption metadata with a path identifying the locations of the encrypted fields. An encrypted data key is appended with a decryption identifier and stored in the encryption metadata. The encrypted data object may be reformatted while encrypted. The encrypted data key is extracted from the encryption metadata and the decryption identifier is used to identify a master key used to decrypt the encrypted data key. The data key is used to decrypt the encrypted values and the decrypted values are stored in the fields identified by the paths.

Disclosed herein are methods, systems, and apparatus, including computer programs encoded on computer storage media, for managing blockchain-based trustable transaction services. One of the methods includes: storing order data of an order between a buyer and a seller on a blockchain of a blockchain network, the order data including one or more payment conditions, verifying that the buyer has a trustable automatic payment service guaranteed by a buyer financial institution, generating a smart contract for the order based on the order data on the blockchain, and executing the smart contract to automatically instruct the buyer financial institution to make a payment of the order for the buyer to the seller according to the trustable automatic payment service in response to determining that a payment condition for the payment specified in the smart contract is met based on order status data uploaded to the blockchain.

A multi-lender architecture is configured to provide a loan applicant with automated pre-qualification and automobile loan eligibility evaluation for multiple candidate lenders. Lender output data may include sensitive data. The lender output data is stored in a data object of a first format and one or more fields of the data object are encrypted at the field level. The encrypted data object may be transmitted through multiple application layers or terminals. The encrypted data object may be reformatted at one or more application layers or terminals without decryption. A reformatted encrypted data object containing the lender output data may be decrypted at the last layer before forwarding the lender output data to the loan applicant.

Systems and methods are disclosed to provide flaw accentuation to an image in an e-commerce online marketplace. In some embodiments, a method may include receiving at an online marketplace, from a seller through the Internet, an image of an item being listed for sale at the online marketplace and text related to the item being listed for sale; determining that the item includes a flaw based on the text related to the item being listed for sale or the image of the item; creating a flaw accentuation to the image; and creating a listing in the online marketplace for the item that includes the image and the flaw accentuation to the image.

A multi-platform e-commerce system with a virtual cart is disclosed. The system includes one or more processors and a memory device storing a set of instructions that when executed by the one or more processors, causes the one or more processors to: create an internal virtual cart associated with the multi-platform e-commerce system; in response to the creation of the internal virtual cart, create an external virtual cart associated with one or more single e-commerce platforms; in response to every action taken in the internal virtual cart associated with the multi-platform e-commerce system, enable performance of an immediate corresponding action on the external virtual cart associated with the one or more single e-commerce platforms.

Embodiments of the invention provide a method, system and computer program product for online ordering using conversational interfaces. In an embodiment of the invention, the method includes storing customer information corresponding to a customer and responsive to receiving a message with text or speech and an image from the customer, identifying an intent type from the text or speech using Natural Language Understanding, identifying a product or service from the image using image classification techniques and transmitting a product detail message to the customer with the product or service and corresponding pricing using Natural Language Generation. The method further includes responsive to receiving an affirmative message from the customer in response to the product detail message identified as affirmative using Natural Language Understanding, automatically completing a purchase of the product or service with the customer information and transmitting a receipt message to the customer with an order receipt.