A system may learn what parameters are required for an item in order to compute tax for the item based on preliminary data regarding the item and/or the transaction. The system may determine a classification code based on such preliminary data and use that classification code to search or query a database storing information indicative of parameters required to compute tax for items having such a classification code. The system may map the received preliminary data into the learned required parameters and determine whether there are any required parameters for which there has not been any preliminary data mapped into them. The system may prompt the customer (e.g., seller of the item) or other user for data values of such missing required parameters or otherwise obtain data values of such parameters in order to compute the tax for the item.

In various embodiments a player of a gaming device or mobile gaming device is presented with an indication of a payout amount less any taxes that would be owed for the payout.

An online software platform (OSP) may look up one or more alignment digital rules that determine exemptibility of a relationship instance; apply the one or more alignment digital rules to the relationship instance based on one or more attributes of the relationship instance; determine the exemptibility of the relationship instance based on the application of the one or more alignment digital rules to the relationship instance; and transmit a notification regarding the exemptibility of the relationship instance, thus helping to prevent unnecessary or incorrect production of resources by automated systems.

Systems and methods electronically provide information regarding digital rules related to a potential relationship instance. Users often wish to know which digital rules apply to a specified item before engaging in a relationship instance with a host entity regarding the item. The system and methods described herein allow a computing facility to identify an item and receive resource information related to the item and the digital rules applicable to the item.

An online concierge system requests an image of a receipt of an order from a picker after the picker fulfills the order at a store. The online concierge system performs image processing on the image of the receipt and uses machine learning and optical character recognition to determine a tax amount paid for the order and a confidence score associated with the tax amount. The online concierge system may use the machine learning model for segmenting extracted text in the image of the receipt into tokens. The online concierge system may then determine at least one token associated with a tax item and the tax amount associated with the tax item. The online concierge system communicates the tax amount to the store for reimbursement based on the tax amount and the confidence score.

Systems and methods are provided for managing sales tax information. The information may be generated, for example, in connection with transactions involving financial accounts, such as a credit card account. The sales tax information may be received electronically from, for example, a merchant or a point of sale device. A determination may be made whether there is any missing sales tax information. If there is missing information a request may be generated and sent to a source having the information. The source may receive the request, retrieve the desired information, and transmit it to the requesting entity. The sales tax information may be stored and later retrieved for presentation to a user, such as the account holder. The account holder may use the information in completing a tax return.

A method, computer program product, and system are disclosed. The method, when implemented in a computer system, includes determining a change deposit amount, determining account information (the account information identifying an account), and initiating a deposit operation, where the deposit operation includes performing an electronic deposit of the change deposit amount to the account. The determining is performed by a digital change application that is installed in a mobile device. The digital change application is configured to initiate the electronic deposit of the change deposit amount to the account.

A computer implemented method of facilitating a consumption tax on a purchase of one or more goods and/or services by a buyer from a seller, wherein at least the buyer is a buyer-seller who makes an onward sale based on said goods and/or services. The method comprises, by the seller of the purchase, obtaining a first blockchain transaction that can be redeemed by a second blockchain transaction meeting either of two alternative conditions: a first condition requiring at least that the second blockchain transaction is signed with a cryptographic signature of the buyer, and a second condition requiring at least that the second blockchain transaction is signed with at least a cryptographic signature of a tax authority; and in response to receiving a payment of the consumption tax from the buyer, sending the first blockchain transaction to be recorded on a blockchain.

Aspects of the disclosure provide method and apparatus for video coding. In the method, which of a combination of vertical padding and horizontal padding is performed is determined to determine padded values of a reference block in a neighboring left coding tree unit (CTU) included in a fixed search range of blocks in a current CTU. The padded values are determined based on a block vector that points to the reference block and a position of a current block in the CTU. At least a sample of the current block is reconstructed based on one of (i) the padded values of the reference block and (ii) reconstructed samples of the reference block based on availability of the reference block in the fixed search range. The left CTU is padded using a combination of the vertical and the horizontal padding.

A computer system for mapping products to taxability categories includes one or more processors configured to execute, in a run-time inference phase, an artificial intelligence model, a taxability category mapping engine, and a taxability category driver record association engine. The artificial intelligence model is configured to receive product text including a product name and product description associated with a product catalog, and output a predicted tax category for a product associated with the product catalog. The taxability category mapping engine is configured to link a taxability driver to the product. The taxability category driver record association engine is configured to create a taxability category mapping drivers record including the taxability driver that is linked to the product. The predicted tax category output from the artificial intelligence model and the taxability category mapping drivers record are stored in a product taxability record.