Digitally cross-referencing community transaction data to determine commodity types and automatically assign tax codes to an invoice

One or more non-transitory computer-readable media storing instructions which, when processed by one or more processors, cause:

• storing, by at least one processor of a coding computer, sequences of rules processing instructions, parameter generating instructions, and tax code assignment instructions;
• executing, by the at least one processor, the rules processing instructions to cause receiving a set of rules for assigning one or more tax codes for an entity based on a plurality of parameters, and electronically storing the set of rules as one of an XML file, YAML file, JSON file, MessagePack file, or CSV file, in a digital data repository;
• executing, by the at least one processor, the parameter generating instructions to cause receiving from a buyer computer an invoice for the entity wherein the invoice comprises invoice data;
• determining, by the at least one processor, one or more commodity types for the invoice by digitally cross-referencing the invoice data with community transaction data using a machine learning algorithm;
• and
• executing, by the at least one processor, the tax code assignment instructions to cause the at least one processor to automatically assign one or more tax codes to the invoice using the one or more commodity types and the set of rules stored in the digital data repository and causing to display the one or more tax codes in a graphical user interface.

A computer system comprising:

• one or more processors;
• and
• one or more memories communicatively coupled to the one or more processors and storing instructions which, when processed by the one or more processors of a server computing device, cause:
• storing sequences of rules processing instructions, parameter generating instructions, tax code assignment instructions, and display instructions;
• executing, by the one or more processors the rules processing instructions to cause receiving a set of rules for assigning one or more tax codes for an entity based on a plurality of parameters, and electronically storing the set of rules as one of an XML file, YAML file, JSON file, MessagePack file, or CSV file, in a digital repository;
• executing, by the one or more processors the parameter generating instructions to cause receiving, from a buyer computer an invoice for the entity wherein the invoice comprises invoice data;
• determining, by the one or more processors one or more commodity types for the invoice by digitally cross-referencing the invoice data with community transaction data that is stored in a separate data repository using a machine learning algorithm;
• and
• executing, by the one or more processors the tax code assignment instructions to cause automatically assigning one or more tax codes to the invoice using the one or more commodity types and the set of rules and causing to display the one or more tax codes in a graphical user interface.