DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
This is in reply to communication filed on 01/20/2026.
Claims 1, 4, 13, 16-17 and 19-20 have been amended.
Claim 9 has been cancelled.
Claim 21 have been added.
Claims 1-8 and 10-21 are currently pending and have been examined.
Response to Arguments
In response to Applicant Arguments /Remarks made in an amendment filled on 01/20/2026:
Claim Rejections - 35 USC § 112:
Due to claim amendments the examiner withdraw the Claim Rejections - 35 USC § 112.
Regarding 35 USC § 101 rejection:
Applicant argument submitted under the title “Rejections Under 35 U.S.C. § 101” in pages 10-14, that:
“Claims 1-20 stand rejected under 35 U.S.C. § 101 as being directed to nonstatutory subject matter. Applicants respectfully traverse this rejection for at least the following reasons. The Claims Do Not Recite a Judicial Exception
With respect to claim 1, the Office states that the claim recites "Certain Methods of Organizing Activity" grouping of abstract ideas. (Office Action, p. 10 emphasis added). Applicant disagrees. Solely to advance prosecution and without acquiescing to the rejections, claim 1 has been amended …
At a minimum, the claims recite, for example, "determining, using a machine learning model and based on the at least one missing check number and the timestamp as input to the machine learning model, at least one outstanding check associated with the checking account" in claim 1. The claims further recite, for example, "re-training the machine learning model based on the feedback information and the missing check pattern associated with the one or more entities, wherein the feedback information is different from the input to the machine learning model."
Similar to Example 39, although these limitations may involve an abstract idea, claim 1 does not recite a judicial exception. While re-training the machine learning model may encompass a broad array of techniques or activities that could involve or rely upon mathematical concepts, the limitations do not set forth or describe any specific mathematical relationships …
These steps are not "organizing human activity" as alleged by the Office, because they recite interactions of the computing device and the user device, retrieving the scanned image via a first API to obtain sequential check information, using the machine learning model to determine the outstanding check information, retrieving compiled web information via a second API different from the first API, determining missing check pattern and retaining the machine learning model based on user feedback information and the missing check pattern, displaying a website for the user to make online payment for the outstanding check. This combination of technical features goes beyond the alleged abstract idea of "managing personal behavior or relationships or interactions between people" and do not fall within the organizing human activity of the abstract idea.
The Claimed Concept Has Practical Application Because It Recites A Particular Solution To A Problem Or A Particular Way To Achieve A Desired Outcome … The additional features recited in claim 1 integrate any possible judicial exception into a practical application. For example, claim 1 recites, inter alia, "causing a user interface to be displayed on the user device ... wherein the user interface comprises: a flag indicating the at least one outstanding check; and a field enabling the first user to input feedback information comprising an entity name associated with the at least one outstanding check; receiving ... from the user device, the feedback information comprising the entity name associated with the at least one outstanding check; updating the machine learning model based on the feedback information ... wherein the feedback information is different from the input to the machine learning model ... causing display, in the user interface of the user device, of a transaction summary for the checking account comprising: check numbers that have been processed within a period of time; and the missing check number, the corresponding entity and the flag indicating an outstanding check." At least these features integrate the claims into a practical application.
The memorandum also advises that "Examiners are cautioned not to oversimplify claim limitations" and should consider "[w]hether the claim recites only the idea of a solution or outcome, i.e., the claim fails to recite details of how a solution to a problem is accomplished, or the claim covers a particular solution to a problem or a particular way to achieve a desired outcome." (Memorandum, p. 3.)
Here, the claims recite a particular solution-namely, using the machine learning model to determine outstanding checks, using different APIs to receive and process scanned images and web information-to address specific technical challenges in electronic check processing systems …
Taken together, these steps are not "mere instructions to apply the exception using a generic computer component," as the Office alleges. Rather, the additional elements in claim 1 provide significantly more (i.e., provide an inventive concept) because they are a practical implementation of the alleged abstract idea, particularly to address data processing in the electronic payment processing network in a non-conventional and non-generic way, even though the steps use some well-known components (a processor and a computing device). The pending claims reflect an improvement in the technology and, thus, recite patent-eligible subject matter under § 101 for this reason.
Accordingly, the rejection under AIA 35 U.S.C. § 101 of claims 1-8 and 10-21 should be reconsidered and withdrawn”.
Applicant's arguments have been fully considered but they are not persuasive.
In response, the examiner respectfully disagrees and emphasizes none of the receiving, determining, displaying, receiving, retrieving, determining, providing, receiving, causing displaying steps, whether taken individually or collectively, have not been shown to affect any form of technical change or improvement whatsoever, and are abstract idea. Applicant's claims have not been shown to modify, reconfigure, manipulate, or transform the computer, computer software, or any technical elements in any discernible manner, much less yield an improvement thereto. There is simply no showing of implementing any of the claim steps, individually or in combination, amounts to a technological improvement, nor the alleged “the claims recite a particular solution-namely, using the machine learning model to determine outstanding checks, using different APIs to receive and process scanned images and web information-to address specific technical challenges in electronic check processing systems” suggested by Applicant. Although Applicant asserts that “A Particular Solution To A Problem Or A Particular Way To Achieve A Desired Outcome”, the examiner first notes that providing payment instruments choices is not reasonably understood as a technology, but instead involves organizing of human activity.
Furthermore, the recited “computing device”, “a user device and a first application programming interface (API)”, “a machine learning model”, “a user interface”, “a web scraping algorithm and via a second API different from the first API”, “in a browser of the user device of a website”, this recitation to the generic computer technology that is being used as a tool to execute the steps that define the abstract idea do not provide for integration at the 2nd prong and do not provide for significantly more at step 2B. In addition, “re-training the machine learning model based on the feedback information and the missing check pattern associated with the one or more entities, wherein the feedback information is different from the input to the machine learning model”, does not meaningfully limit the claimed as it recites a computer function at a high level of generality to training and re-training a machine learning model do not provide for integration at the 2nd prong and is not sufficient to amount to significantly more than the judicial exception.
For example, in Example 39, the Examiner emphasizes that the eligibility analysis provided for claim 1 of Example 39 does not indicate that eligibility hinges on “re-training the machine learning model based on the feedback information and the missing check pattern associated with the one or more entities, wherein the feedback information is different from the input to the machine learning model” The Examiner does acknowledge re-training a machine learning, and the like may be evaluated as additional elements if a judicial exception if recited in the claims during evaluation under Step 2A Prong 1. However, with respect to Example 39, the analysis under Step 2A Prong 1 plainly found that the claim “does not recite any of the judicial exceptions. ...the claim does not recite any mathematical relationships, formulas or equations... .the claim does not recite a mental process...the claim does not recite any method of organizing human activity... Thus, the claim is eligible because it does not recite a judicial exception.” In contrast, when evaluated under Step 2A Prong 1, Applicant's claims plainly set forth steps for managing personal behavior or relationships or interactions (e.g., provide a variety of payment options to a customer to pay for a purchase or service) under the “Certain Methods of Organizing Human Activity” abstract idea grouping, as discussed below in the §101 rejection.
Moreover, while claim 1 of Example 39 does involve training a machine learning, this technique is performed for improvement of the technological process of digital facial image detection. Although applicant’s claims involve re-training a machine learning, the re-training is recited at high level of generality and have not been shown to yield a technical improvement, but instead merely seek providing a variety of payment options to a customer which directly pertains to the abstract idea itself, which are results devoid of technical improvement comparable to the digital facial image detection of Example 39. Accordingly, Applicant’s reliance on the eligibility rationale of Example 39 is not persuasive.
For the reasons above along with the reasons set forth in the updated §101 rejection set forth below, Applicant's amendments and arguments concerning the §101 rejection are not sufficient to overcome the rejection.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-8 and 10-21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception without significantly more.
Step 1:
Claims 1-8, 10-12 and 21 recite a method, which is directed to a process.
Claims 13-18 recite a device, which is directed to a machine.
Claims 19-20 recite a non-transitory media storing instructions, which is directed to a manufacture.
Therefore, each claim falls within one of the four statutory categories.
Step 2A, Prong 1 (Is a judicial exception recited?):
The independent claims 1, 13 and 19 recite the abstract idea. This idea is described by the steps of:
receiving scanned images of the plurality of checks to obtain sequential check information comprising at least one missing check number associated with the checking account and a timestamp each check has been cleared;
determining based on the at least one missing check number and the timestamp as input at least one outstanding check associated with the checking account;
causing to be displayed to a first user:
a flag indicating the at least one outstanding check; and
a field enabling the first user to input feedback information comprising an entity name associated with the at least one outstanding check;
receiving the feedback information comprising the entity name associated with the at least one outstanding check;
retrieving compiled web information associated with entities in a geographical region;
determining, based on the compiled web information and transaction records from a plurality of checking accounts, a missing check pattern associated with one or more entities in the geographical region;
providing an option to select an alternative payment associated with the at least one outstanding check, wherein the alternative payment comprising an online payment;
receiving a selection of the alternative payment comprising the online payment;
causing display for the first user to make the online payment associated with the outstanding check; and
causing display of a transaction summary for the checking account comprising:
check numbers that have been processed within a period of time; and
the missing check number, the corresponding entity and the flag indicating an outstanding check
These claims recite a certain method of organizing human activity. The claims recite to a certain method of organizing human activity as the above abstract idea limitations are directed to managing personal behavior or relationships or interactions between people. The examiner finds the claims to simply recites steps of fundamental economic practices or principles of receiving payment instrument information (i.e., check), determining unprocessed payment (i.e., outstanding check), sending a notification to a customer, providing the customer with option to choose an alternative payment instrument based on the customer’s feedback, which is an abstract idea of personal behavior/relationships around managing payments by providing a variety of payment options to a customer. The Examiner additionally finds the claims to be similar to an example the courts have identified as being a certain method of organizing human activity:
1) local processing of payments for remotely purchased goods, Inventor Holdings, LLC v. Bed Bath Beyond, 876 F.3d 1372, 1378-79, 125 USPQ2d 1019, 1023 (Fed. Cir. 2017).
2) financial instruments that are designed to protect against the risk of investing in financial instruments, In re Chorna, 656 Fed. App'x 1016, 1021 (Fed. Cir. 2016) (non-precedential).
Offending clauses include:
re-training the machine learning model based on the feedback information and the missing check pattern associated with the one or more entities, wherein the feedback information is different from the input to the machine learning model;
In addition, These claims recite a certain method of organizing human activity. The claims recite to a certain method of organizing human activity as the above abstract idea limitations are directed to managing personal behavior or relationships or interactions between people. The examiner finds the claims to simply recites steps of managing personal behavior or relationships or interactions between people by following rules or instruction to provide a variety of payment options to a customer to pay for a purchase or service. The Examiner additionally finds the claims to be similar to an example the courts have identified as being a certain method of organizing human activity:
1) considering historical usage information while inputting data, BSG Tech. LLC v. Buyseasons, Inc., 899 F.3d 1281, 1286, 127 USPQ2d 1688, 1691 (Fed. Cir. 2018).
2) Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 115 USPQ2d 1636 (Fed. Cir. 2015). The patentee in this case claimed methods comprising storing user-selected pre-set limits on spending in a database, and when one of the limits is reached, communicating a notification to the user via a device. 792 F.3d. at 1367, 115 USPQ2d at 1639-40. The Federal Circuit determined that the claims were directed to the abstract idea of "tracking financial transactions to determine whether they exceed a pre-set spending limit (i.e., budgeting)", which "is not meaningfully different from the ideas found to be abstract in other cases before the Supreme Court and our court involving methods of organizing human activity." 792 F.3d. at 1367-68, 115 USPQ2d at 1640.
Offending clauses include:
re-training the machine learning model based on the feedback information and the missing check pattern associated with the one or more entities, wherein the feedback information is different from the input to the machine learning model;
Step 2A, Prong 2 (Is the exception integrated into a practical application?):
This judicial exception is not integrated into a practical application because the claims satisfy the following criteria, which indicate that the claims do not integrate the abstract idea into practical application:
The claimed additional limitations are:
Claim 1: a computing device, a user device and a first application programming interface (API), a machine learning model, a user interface, a web scraping algorithm and via a second API different from the first API, in a browser of the user device of a website, re-training the machine learning model based on the feedback information and the missing check pattern associated with the one or more entities, wherein the feedback information is different from the input to the machine learning model,
Claim 13: computing device comprising: one or more processors; and memory storing instructions that, when executed by the one or more processors, cause the computing device, a user device and via a first application programming interface (API), a machine learning model, a user interface, a web scraping algorithm and via a second API different from the first API, in a browser of the user device of a website, re-training the machine learning model based on the feedback information and the missing check pattern associated with the one or more entities, wherein the feedback information is different from the input to the machine learning model,
Claim 19: one or more non-transitory media storing instructions that, when executed by one or more processors, cause the one or more processors to perform steps, computing device from the user device and via a first application programming interface (API), a machine learning model, a user interface, a web scraping algorithm and via a second API different from the first API, in a browser of the user device of a website, re-training the machine learning model based on the feedback information and the missing check pattern associated with the one or more entities, wherein the feedback information is different from the input to the machine learning model,
The additional limitations are directed to using a generic computer to process information and perform the abstract idea. Therefore, the limitations merely amount to adding the words “apply it” (or an equivalent) to the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea, as discussed in MPEP 2106.05(f).
Step 2B (Does the claim recite additional elements that amount to significantly more that the judicial exception?):
1) The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
As for Step 2B analysis, knowing the consideration is overlapping with Step 2A, Prong 2. The Step 2B considerations have already been substantially addressed under Step 2A Prong 2, see Step 2A Prong 2 analysis above. As discussed above, the additional imitations amount to adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea, as discussed in MPEP 2106.05(f).
2) The recited “re-training the machine learning model based on the feedback information and the missing check pattern associated with the one or more entities, wherein the feedback information is different from the input to the machine learning model” recited at a high level of generality and perform programmed functions that represent conventional and generic operations for these devices, including inputting data, analyzing data, and updating data. Unlike the eligible claims in Diehr and Bascom, in which the elements limiting the exception were individually conventional but taken together provided an inventive concept because they improved a technical field, the claim here does not invoke any of the considerations that courts have identified as providing significantly more than an exception. The combination of elements is no more than the sum of their parts, and provides nothing more than mere automation of determining missing data on an issued check steps that were in years past performed mentally by service providers when engaging with a customer. Mere automation of an economic business practice does not provide significantly more (i.e., provide an inventive concept).
In addition, the dependent claims recite:
Step 2A, Prong 1 (Is a judicial exception recited?):
Dependent claims 2-8, 10-12, 14-18 and 20-21 recitations further narrowing the abstract idea recited in the independent claims 1, 13 and 19 and therefore directed towards the same abstract idea.
Step 2A, Prong 2 and Step 2B:
The dependent claims 2-8, 10-12, 14-18 and 20-21 further narrow the abstract idea recited in the independent claims 1, 13 and 19 and are therefore directed towards the same abstract idea.
The dependent claims recite the following additional limitations:
Claim 2: computer, a second machine learning model,
Claims 3, 4, 5, 6, 7, 8, 11: computer,
Claim 10: computer, the machine learning model
Claim 12: computer, the user device,
Claims 14, 17, 18: computing device, the instructions, when executed by the one or more processors, cause the computing device, a second machine learning model,
Claim 15: computing device, wherein the instructions, when executed by the one or more processors, cause the computing device
Claim 16: computing device,
Claim 20: the non-transitory media of claim 19, wherein the instructions, when executed by the one or more processors, cause the one or more processors to perform steps, the machine learning model,
Claim 21: computer, the machine learning model is trained based on first training data, the machine learning model is re-trained based on second training,
However, the examiner finds each of these additional elements to be directed to merely “apply it” or applying a generic technology to perform the recited abstract idea of receiving input information from a user and presenting received information, the recitation to the generic computer technology that is being used as a tool to execute the steps that define the abstract idea do not provide for integration at the 2nd prong and do not provide for significantly more at step 2B.
Therefore, the limitations on the invention of claims 1-8 and 10-21, when viewed individually and in ordered combination are directed to in-eligible subject matter.
Distinguished Over Prior Art
Examiner is in agreement with applicant’s amendments and arguments filed on 12/13/2024. The prior art on record, alone or in combination, neither anticipates, reasonably teaches, nor renders obvious the Applicant's claimed invention. Accordingly, the applicant needs to address the outstanding rejections above in order to issue an allowability notice. The reason to withdraw the 35 USC 103 rejection of claims 1-8 and 10-21 in the instant application is because the prior art of record fails to teach the overall combination as claimed. Therefore, it would not have been obvious to one of ordinary skill in the art to modify the prior art to meet the combination above without unequivocal hindsight and one of ordinary skill would have no reason to do so. Upon further searching the examiner could not identify any prior art to teach these limitations. The prior art on record, alone or in combination, neither anticipates, reasonably teaches, not renders obvious the Applicant’s claimed invention. Accordingly, the examiner recommends addressing the outstanding rejections above.
Conclusion
1. THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/AVIA SALMAN/Primary Patent Examiner, Art Unit 3627