IP Library Granted Patent US 12,277,583
Granted Patent B1
US 12,277,583 · App. 18/435,765 · Granted Apr 15, 2025

Customs duty and tax estimation according to indicated risk tolerance

Inventors: Adrian Nistor (Toronto, CA); Craig Evan Reed (Toronto, CA); Amy E. Morgan (Seattle, WA); David Kempe (Auburn, WA); Mark Alan Withers (Bainbridge Island, WA); Jurgis KP Vilis (Toronto, CA)
Assignee: Avalara, Inc.
G06Q30/04G06F3/04847G06F16/285G06F16/953G06Q30/0635G06Q40/10H04L67/01
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Quick Facts
Patent No.
US 12,277,583
App. No.
18/435,765
Granted
Apr 15, 2025
Kind
B1
Abstract

A service engine of a processor-based system determines an estimated amount of taxes due in association with a proposed transaction based on a risk tolerance value specified by a party to the transaction, such as a seller. Multiple classification code queries are generated for classifying an item that is the subject of the proposed transaction, from which a plurality of classification code candidates are determined. Each such classification code candidate is considered in determination of multiple corresponding possible tax-due amounts, and the taxes due for the proposed transaction are determined by the service engine based on a statistical calculation corresponding to the specified risk tolerance value. The service engine provides the estimated tax due amount to one or more parties to the proposed transaction.

Claims (71)

1. A method for a server system, the method including at least:

electronically receiving, by a service engine application programming interface (API) that is in electronic communication with a service engine of the server system over a computer network, risk tolerance data from a seller client computer distinct from the server system, wherein the risk tolerance data is associated with potential tax information;

electronically receiving, by the service engine API, order data about a prospective sale of an item by the seller to a buyer in a buyer jurisdiction distinct from the seller jurisdiction;

electronically generating, from the order data, a classification code query for classifying the item for the prospective sale;

electronically retrieving a plurality of classification code candidates for the item for the prospective sale in response to the classification code query;

electronically determining a plurality of tax information that corresponds to respective classification code candidates;

electronically obtaining an estimated tax amount based on the plurality of tax information and the risk tolerance data; and

electronically causing, by the service engine API, the estimated tax amount to be transmitted to the seller client computer.

2. The method of claim 1 , in which the estimated tax amount is a customs duty.

3. The method of claim 1 , in which the estimated tax amount is an import tax.

4. The method of claim 1 , in which:

the risk tolerance data includes a first risk tolerance value, a second risk tolerance value and a third risk tolerance value,

the risk tolerance data is received via a selection input that indicates, in response to a presented option, a selection by the seller of one of the first risk tolerance value, the second risk tolerance value, and the third risk tolerance value, and

the estimated tax amount has a value responsive to the selection input indicating a selection of the third risk tolerance value.

5. The method of claim 1 , in which one or more classification code queries are formed based at least in part on the buyer jurisdiction.

6. The method of claim 1 , in which one or more classification code queries are formed based at least in part on item data.

7. The method of claim 1 , further including:

transmitting one or more classification code requests that encode the classification code query; and

inputting one or more classification code responses responsive to the transmitted one or more classification code requests;

wherein the plurality of classification code candidates are inputted from the inputted classification code responses.

8. The method of claim 1 , in which one of the classification code candidates includes a portion of a harmonized system (HS) code.

9. The method of claim 1 , in which the estimated tax amount is extracted from a maximum of a plurality of possible tax amounts.

10. The method of claim 1 , in which the estimated tax amount is extracted from a median of a plurality of possible tax amounts.

11. The method of claim 1 , in which the estimated tax amount is extracted from an average of a plurality of possible tax amounts.

12. The method of claim 1 , in which each classification code candidate of the plurality of classification code candidates is associated with a respective probability weight of a plurality of probability weights, and in which the estimated tax amount is extracted from an average of a plurality of possible tax amounts that have been adjusted in accordance with the plurality of probability weights.

13. The method of claim 1 , in which:

the risk tolerance data is based on a selection input that indicates a desired fraction of a prospective range,

a plurality of possible tax amounts define an actual range based on the risk tolerance data, and

the estimated tax amount is extracted from the desired fraction and from the actual range.

14. The method of claim 1 , in which the estimated tax amount is communicated to the seller client computer explicitly.

15. The method of claim 1 , in which the estimated tax amount is communicated to the seller client computer by being bundled with another value.

16. A system comprising:

at least one processor; and

a memory coupled to the at least one processor, the memory storing instructions that, when executed by the at least one processor, cause the system to perform operations that include to:

electronically receive, by a service engine application programming interface (API) that is in electronic communication with a service engine of a server system over a computer network, risk tolerance data from a seller client computer distinct from the server system, wherein the risk tolerance data is associated with potential tax information;

electronically receive, by the service engine API, order data about a prospective sale of an item by the seller to a buyer in a buyer jurisdiction distinct from the seller jurisdiction;

electronically generate, from the order data, a classification code query for classifying the item for the prospective sale;

electronically retrieve a plurality of classification code candidates for the item for the prospective sale in response to the classification code query;

electronically determine a plurality of tax information that corresponds to respective classification code candidates;

electronically obtain an estimated tax amount based on the plurality of tax information and the risk tolerance data; and

electronically cause, by the service engine API, the estimated tax amount to be transmitted to the seller client computer.

17. The system of claim 16 , in which the estimated tax amount is a customs duty or an import tax.

18. The system of claim 16 , in which:

the risk tolerance data includes a first risk tolerance value, a second risk tolerance value and a third risk tolerance value,

the risk tolerance data is received via a selection input that indicates, in response to a presented option, a selection by the seller of one of the first risk tolerance value, the second risk tolerance value, and the third risk tolerance value, and

the estimated tax amount has a value responsive to the selection input indicating a selection of the third risk tolerance value.

19. The system of claim 16 , in which one or more classification code queries are formed based at least in part on the buyer jurisdiction.

20. The system of claim 16 , in which one or more classification code queries are formed based at least in part on item data.

21. The system of claim 16 , in which instructions further cause the system to perform operations that include to:

transmit one or more classification code requests that encode the classification code query; and

input one or more classification code responses responsive to the transmitted one or more classification code requests;

wherein the plurality of classification code candidates are inputted from the inputted classification code responses.

22. The system of claim 16 , in which one of the classification code candidates includes a portion of a harmonized system (HS) code.

23. The system of claim 16 , in which the estimated tax amount is extracted from a maximum of a plurality of possible tax amounts.

24. The system of claim 16 , in which the estimated tax amount is extracted from a median of a plurality of possible tax amounts.

25. The system of claim 16 , in which the estimated tax amount is extracted from an average of a plurality of possible tax amounts.

26. The system of claim 16 , in which each classification code candidate of the plurality of classification code candidates is associated with a respective probability weight of a plurality of probability weights, and in which the estimated tax amount is extracted from an average of a plurality of possible tax amounts that have been adjusted in accordance with the plurality of probability weights.

27. The system of claim 16 , in which:

the risk tolerance data is based on a selection input that indicates a desired fraction of a prospective range,

a plurality of possible tax amounts define an actual range based on the risk tolerance data, and

the estimated tax amount is extracted from the desired fraction and from the actual range.

28. The system of claim 16 , in which the estimated tax amount is communicated to the seller client computer by being bundled with another value.

29. A non-transitory computer-readable storage medium having computer-executable instructions stored thereon that, when executed by at least one processor, cause the at least one processor to perform operations that include:

electronically receiving, by a service engine application programming interface (API) that is in electronic communication with a service engine of a server system over a computer network, risk tolerance data from a seller client computer distinct from the server system, wherein the risk tolerance data is associated with potential tax information;

electronically receiving, by the service engine API, order data about a prospective sale of an item by the seller to a buyer in a buyer jurisdiction distinct from the seller jurisdiction;

electronically generating, from the order data, a classification code query for classifying the item for the prospective sale;

electronically retrieving a plurality of classification code candidates for the item for the prospective sale in response to the classification code query;

electronically determining a plurality of tax information that corresponds to respective classification code candidates;

electronically obtaining an estimated tax amount based on the plurality of tax information and the risk tolerance data; and

electronically causing, by the service engine API, the estimated tax amount to be transmitted to the seller client computer.

30. The non-transitory computer-readable storage medium of claim 29 , in which the estimated tax amount is a customs duty or an import tax.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 7, 2024
From: NISTOR, ADRIAN; REED, CRAIG EVAN; KEMPE, DAVID; WITHERS, MARK ALAN; VILIS, JURGIS KP; MORGAN, AMY E.
To: AVALARA, INC.
Reel/Frame 066411/0788 →
Continuity (4)
Continuation 18372994 · Sep 26, 2023
Continuation 16803815 · Feb 27, 2020
Provisional Application 62943684 · Dec 4, 2019
Provisional Application 62930159 · Nov 4, 2019
References Cited (20)
US 7783536B2 · William et al. · 2010 [cited by applicant]
US 7933803B1 · Nadler et al. · 2011 [cited by applicant]
US 8620578B1 · Brown et al. · 2013 [cited by applicant]
US 8725401B2 · Daveze et al. · 2014 [cited by applicant]
US 8725407B2 · Hurley et al. · 2014 [cited by applicant]
US 9760915B2 · Pavlou et al. · 2017 [cited by applicant]
US 10445818B1 · Chowdhary · 2019 [cited by applicant]
US 10769611B2 · McNeel · 2020 [cited by applicant]
US 20020138765A1 · Fishman et al. · 2002 [cited by applicant]
US 20070136158A1 · Rawlings et al. · 2007 [cited by applicant]
US 20070136159A1 · Rawlings et al. · 2007 [cited by applicant]
US 20090187500A1 · Wilson · 2009 [cited by examiner]
US 20120124050A1 · Yang et al. · 2012 [cited by applicant]
US 20130013471A1 · Fishman · 2013 [cited by applicant]
US 20170004583A1 · Wang · 2017 [cited by examiner]
US 20180211322A1 · Lintner · 2018 [cited by examiner]
US 20190251501A1 · Reid · 2019 [cited by examiner]
D.-s. Liu, W. Chen and S.-w. Gao, “Gradual Tax Policies for China's E-commerce Based on Mode Classification,” 2009 International Joint Conference on Artificial Intelligence, Hainan, China, 2009, pp. 765-768, doi: 10.110… [cited by examiner]
U.S. Harmonized Tariff System Codes Duty Rates (HTS Codes), Foreign Trade Online, Revised Feb. 14, 2020. https://www.foreign-trade.com/reference/hscode-duty-rate.htm. 2 pages. [cited by applicant]
Uzuner and L. McKnight, “Sales taxes on the Internet: when and how to tax?,” Proceedings of the 34th Annual Hawaii International Conference on System Sciences, Maui, HI, USA, 2001, pp. 9 pp.-, doi: 10.1109/H ICSS.2001.9… [cited by applicant]