Categorically inductive taxonomy system, program product and method

• US 10,204,380 B1
• Filed: 06/16/2015
• Issued: 02/12/2019
• Est. Priority Date: 06/16/2015
• Status: Active Grant

• Current Assignee: Eezzdata, Inc.
• Original Assignee: Eezzdata, Inc.
• Inventors: Moore, Riley, Foulks, Wendy, Foulks, Thom, Moore, James Terrence, Gallegos, Andrew Anthony
• Primary Examiner(s): Goyea, Olusegun
• Application Number:
  US14/740,757
• Time in Patent Office: 1,337 Days
• Field of Search: 707661, 707827, 707754, 70799901, 707999009
• CPC Class Codes: G06F 16/2291 User-Defined Types; Storage management thereof
• CPC Class Codes: G06F 16/25 Integrating or interfacing systems involving database management systems
• CPC Class Codes: G06F 16/353 into predefined classes
• CPC Class Codes: G06Q 40/12 Accounting

Abstract

System, method and program product, the system configured to retrieve entity financial transaction data; receive for the financial transaction categorical transaction tags categorizing the financial transaction; access a taxonomy associated with the entity, wherein the taxonomy has a progression inductively backwards; determine an identification code for the financial transaction based on the categorical transaction tags, wherein the identification code references a particular data structures in the taxonomy; select one of the categorical transaction tags as the most granular element; assign a unique data tag in the particular data structure to the most granular element; identify, parse and transform the financial transaction data for use in logical functions; execute an inductive algorithm to propagate from the most granular element to a higher level in the one data structure to thereby determine and populate a location in a report based on the inductive algorithm; and transmit the report.

Claims

1. A method wherein human data entry activity and human errors from data entry can be reduced, comprising:

retrieving or having retrieved, by one or more computers, financial transaction data for a financial transaction for an entity;

receiving or obtaining or having obtained, by the one or more computers, for the financial transaction, a plurality of categorical transaction tags categorizing the financial transaction, and one or more items of financial transaction data selected from the group of transaction amount, account balance, account names, pending status, location, meta score, and geo-coordinates;

accessing, by the one or more computers, a taxonomy associated with the entity, wherein the taxonomy comprises a plurality of data structures that are vertical and/or flat, with each of the respective data structures having a progression inductively backwards to an upper level in the data structure, wherein each of the plurality of the data structures comprises a most granular element at a lower level, wherein the taxonomy is based on populating a report desired by a user, and wherein each of the data structures contains a level that references at least one location in the report to be populated;

determining, by the one or more computers, an identification code for the financial transaction based at least in part on the plurality of categorical transaction tags, wherein the identification code references a particular one of the data structures in the taxonomy, where the particular one of the data structures comprises a corresponding unique data tag associated with a given level in the particular data structure;

selecting, by the one or more computers, one from the plurality of the categorical transaction tags as the most granular element;

assigning, by the one or more computers, the unique data tag associated with the given level in the particular data structure to the one categorical transaction tag selected as the most granular element for the financial transaction;

organizing, by the one more computers, the financial transaction data based at least in part on the one categorical transaction tag, using one or more algorithms to identify, parse and transform the financial transaction data for use in logical functions that may comprise but not be limited to one selected from the group of inductive data structure propagation, accounting operations, and report creation;

executing, by the one or more computers, an inductive algorithm using the one data structure to propagate from the most granular element in the lower level to a higher level in the one data structure via one or more fixed relationships between each level of the one data structure where the fixed relationships are determined according to the unique data tag and the one categorical transaction tag assigned to the transaction, where the fixed relationships are based on inductive propagation;

determining, by the one or more computers, the at least one location in the report to be populated based at least in part on results from executing the inductive algorithm;

populating or revising the report, by the one or more computers, with data from the financial transaction based at least in part on the at least one location in the report to be populated; and

transmitting, by the one or more computers, the report to the user after one or more locations in the report have been populated.

2. The method as defined in claim 1, wherein the retrieving step is via an API call, where the API call includes access credentials to obtain and/or receive the financial transaction data of the entity, and where the API call is designed to categorize the financial transaction data with a plurality of categorical transaction tags.

3. The method as defined in claim 1, further comprising:

transmitting, by the one or more computers, a notification that a particular one of the locations in the report has been populated with the transaction data, wherein the notification comprises an electronic element for indicating approval or a correction of the populated transaction data at the particular location in the report.

4. The method as defined in claim 3, wherein the electronic element comprises an electronic ability to select from a drop-down menu comprising at least one selected from the group of re-categorizing and deleting.

5. The method as defined in claim 1, wherein there are a plurality of taxonomies, and further comprising:

executing, by the one or more computers, the operation steps of claim 1 for each of the plurality of taxonomies associated with the entity in order to populate a plurality of reports.

6. The method as defined in claim 1, wherein the report is an accounts payable statement, and further comprising:

triggering, by the one or more computers, initiation of a payment based at least in part on the transmission of the report where the payment method is an automated clearing house payment which may be initiated by multi-factor authentication which can be question based, code based, or selection based such that the routing number, and other account identifiers, are stored in a derivative table and accessed via a globally unique access token.

7. The method as defined in claim 1, wherein the report is an accounts receivable report, and further comprising:

scanning or inputting a purchase order, by the one or more computers, by employing optical character recognition; and

inputting some or all of the information present on the purchase order into a native accounting software for accounts receivable to populate the accounts receivable report.

8. The method as defined in claim 1, wherein the report is a financial statement.

9. The method as defined in claim 1, wherein the report is an internal revenue form.

10. The method as defined in claim 1, further comprising:

executing an API call, by the one or more computers, to retrieve, at least one transaction which has not been previously recorded and to parse a plurality of data points retrieved with that transaction; and

store for later use, by the one or more computers, the data points associated with the transaction in a derivative table using globally unique transaction identification codes.

11. The method as defined in claim 1, further comprising:

organizing, by the one or more computers, the financial transaction data according to a discrete histogram;

determining, by the one or more computers, a transactional frequency at which financial transactions for the entity occur; and

creating, by the one or more computers, a schedule to execute the API call based at least in part on the transactional frequency of the entity.

12. The method as defined in claim 1, further comprising:

retrieving a plurality of financial transactions including at least one financial transaction which has not been previously recorded;

queuing, by the one or more computers, the plurality of financial transactions;

storing, by the one or more computers, the financial transaction data for each of the financial transactions in tables with globally unique transaction identification codes; and

executing, by the one or more computers, one or more accounting operations.

13. The method as defined in claim 1, further comprising:

retrieving, by the one or more computers, a plurality of financial transactions including at least one financial transaction which has not been previously recorded by configuring a retrieval algorithm, to obtain, when executed, historical transaction data relating to at least one selected from the group of a checking account, a savings account, and a credit account, a mortgage account, a brokerage account, a loan account, or another account; and

performing, by the one or more computers, the steps of claim 1 on the historical transaction data; and

performing, by the one or more computers, one or more accounting operations.

14. The method as defined in claim 1, further comprising:

retrieving, when executed by the one or more computers, via an API call, an actual balance in an account and a current balance for the account after pending transaction amounts clear for one selected from the group of a checking account, a savings account, and a credit account;

populating, by the one or more computers, the actual balance and the current balance into respective locations in the report; and

sending, by the one or more computers, via an electronic network, an electronic notification that a particular one of the locations in the report has been populated with the actual balance and the current balance, wherein the notification comprises an electronic element.

15. The method as defined in claim 1, comprising:

wherein the financial transaction data comprises a transaction amount, an account balance, account names, and pending status,

queuing, by the one or more computers, a plurality of the financial transactions, and parsing the financial transaction data for each of the financial transactions into a table;

calculating a new transaction amount, by one or more computers, using one or more transaction amounts in the financial transaction data for at least one location in the report;

propagating, by the one or more computers, the new amount calculated throughout higher levels of the one data structure;

populating or revising the report, by the one or more computers, with the new amount based at least in part on the at least one location in the report to be populated; and

transmitting, by the one or more computers, the report to the user after one or more locations in the report have been populated.

16. The method as defined in claim 15,

wherein the financial transaction data is for an expense transaction for which payment was provided digitally, and

subtracting, by the one or more computers, the transaction amount from the account balance;

and

summing, by the one or more computers, the transaction amount with an amount from the most granular element of the lower element of the one data structure.

17. The method as defined in claim 15,

wherein the financial transaction data is for an expense transaction for which payment was provided as cash or check,

receiving, by the one or more computers, an assignment from the entity of one or more categorical transaction tags;

subtracting, by the one or more computers, the transaction amount from the account balance; and

summing, by the one or more computers, the transaction amount with the most granular element of the lowest level of the one data structure.

18. The method as defined in claim 15,

wherein the financial transaction data is for an income transaction for which payment was provided digitally, and

summing, by the one or more computers, the transaction amount with the account balance;

and

subtracting, by the one or more computers, the transaction amount from the most granular element of the lowest level of the one data structure.

19. The method as defined in claim 15,

wherein the financial transaction data is for an income transaction for which payment was provided as cash or check, and

receiving, by the one or more computers, an assignment from the entity, by the one or more computers, of one or more categorical transaction tags;

summing, by the one or more computers, the transaction amount for the income transaction with the account balance; and

subtracting, by the one or more computers, the transaction amount from the most granular element of the lowest level of the data structure.

20. The method as defined in claim 15, wherein one or more items of financial transaction data are selected, and further comprising:

receiving, by the one or more computers, an assignment from the entity of a remediation amount to remediate a bank error;

re-calculating a new amount, by one or more computers, using the remediation amount for at least one location in the report; and

re-propagating, by one or more computers, the new amount throughout higher levels of the one data structure.

21. The method as defined in claim 1, wherein there are a plurality of financial transactions, and further comprising:

placing, by the one or more computers, the plurality of financial transactions into a queue; and

running, by the one or more computers, the method of claim 1 on each of the financial transactions in the queue in an order.

22. A system, comprising:

one or more computers configured to to retrieve or have retrieved, by the one or more computers, financial transaction data for a financial transaction for an entity;

to receive or obtain or have obtained, by the one or more computers, for the financial transaction, a plurality of categorical transaction tags categorizing the financial transaction, and one or more items of financial transaction data selected from the group of transaction amount, account balance, account names, pending status, location, meta score, and geo-coordinates;

to access, by the one or more computers, a taxonomy associated with the entity, wherein the taxonomy comprises a plurality of data structures that are vertical and/or flat, with each of the respective data structures having a progression inductively backwards to an upper level in the data structure, wherein each of the plurality of the data structures comprises a most granular element at a lower level, wherein the taxonomy is based on populating a report desired by a user, and wherein each of the data structures contains a level that references at least one location in the report to be populated;

to determine, by the one or more computers, an identification code for the financial transaction based at least in part on the plurality of categorical transaction tags, wherein the identification code references a particular one of the data structures in the taxonomy, where the particular one of the data structures comprises a corresponding unique data tag associated with a given level in the particular data structure;

to select, by the one or more computers, one from the plurality of the categorical transaction tags as the most granular element;

to assign, by the one or more computers, the unique data tag associated with the given level in the particular data structure to the one categorical transaction tag selected as the most granular element for the financial transaction;

to organize, by the one more computers, the financial transaction data based at least in part on the one categorical transaction tag, using one or more algorithms to identify, parse and transform the financial transaction data for use in logical functions that may comprise but not be limited to one selected from the group of inductive data structure propagation, accounting operations, and report creation;

to execute, by the one or more computers, an inductive algorithm using the one data structure to propagate from the most granular element in the lower level to a higher level in the one data structure via one or more fixed relationships between each level of the one data structure where the fixed relationships are determined according to the unique data tag and the one categorical transaction tag assigned to the transaction, where the fixed relationships are based on inductive propagation;

to determine, by the one or more computers, the at least one location in the report to be populated based at least in part on results from executing the inductive algorithm;

to populate or revise the report, by the one or more computers, with data from the financial transaction based at least in part on the at least one location in the report to be populated; and

to transmit, by the one or more computers, the report to the user after one or more locations in the report have been populated.

23. A non-transitory computer-readable medium comprising computer-readable program code embodied therein, to be executed by one or more computers, comprising:

program code to retrieve or have retrieved, by the one or more computers, financial transaction data for a financial transaction for an entity;

program code to receive or obtain or have obtained, by the one or more computers, for the financial transaction, a plurality of categorical transaction tags categorizing the financial transaction, and one or more items of financial transaction data selected from the group of transaction amount, account balance, account names, pending status, location, meta score, and geo-coordinates;

program code to access, by the one or more computers, a taxonomy associated with the entity, wherein the taxonomy comprises a plurality of data structures that are vertical and/or flat, with each of the respective data structures having a progression inductively backwards to an upper level in the data structure, wherein each of the plurality of the data structures comprises a most granular element at a lower level, wherein the taxonomy is based on populating a report desired by a user, and wherein each of the data structures contains a level that references at least one location in the report to be populated;

program code to determine, by the one or more computers, an identification code for the financial transaction based at least in part on the plurality of categorical transaction tags, wherein the identification code references a particular one of the data structures in the taxonomy, where the particular one of the data structures comprises a corresponding unique data tag associated with a given level in the particular data structure;

program code to select, by the one or more computers, one from the plurality of the categorical transaction tags as the most granular element;

program code to assign, by the one or more computers, the unique data tag associated with the given level in the particular data structure to the one categorical transaction tag selected as the most granular element for the financial transaction;

program code to organize, by the one more computers, the financial transaction data based at least in part on the one categorical transaction tag, using one or more algorithms to identify, parse and transform the financial transaction data for use in logical functions that may comprise but not be limited to one selected from the group of inductive data structure propagation, accounting operations, and report creation;

program code to execute, by the one or more computers, an inductive algorithm using the one data structure to propagate from the most granular element in the lower level to a higher level in the one data structure via one or more fixed relationships between each level of the one data structure where the fixed relationships are determined according to the unique data tag and the one categorical transaction tag assigned to the transaction, where the fixed relationships are based on inductive propagation;

program code to determine, by the one or more computers, the at least one location in the report to be populated based at least in part on results from executing the inductive algorithm;

program code to populate or revise the report, by the one or more computers, with data from the financial transaction based at least in part on the at least one location in the report to be populated; and

program code to transmit, by the one or more computers, the report to the user after one or more locations in the report have been populated.