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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 04/02/2026 has been entered.
Status of Claims
This action is in reply to the amendment filed on 04/03/2026.
Claims 1-20 are previously cancelled.
Claims 21, 30, and 39 are amended
Claims 21-40 are currently pending and have been examined.
Response to Arguments
Applicant's arguments filed 04/03/2026 regarding the 35 U.S.C. § 101 have been fully considered but they are not persuasive.
Applicant argus that the newly amended claims overcome the 101 rejections. Applicant argues the claims implementing a multi-modal matching architecture that performs both text-based matching and image-based matching to determine a set of relevant content. Id. at [0070]. This is not a generic application, but a coordinated technical process that enables the system to evaluate different data types using distinct computational techniques and then combine the results to generate a unified, relevance-ranked content set for presentation to a user. Id. at [0068]- [0069]. By doing so, the system improves the accuracy and completeness of retrieved content in a manner that prior systems, which are limited to single-modality processing, cannot achieve. Id. at [0082]. (Response at 19) Applicant further cites the claim elements on page 17.
Examiner respectfully disagrees, evaluating using text matching and image matching are equivalent to optical character recognition, which is Well-Understood, Routine, Conventional Activity (See MPEP 2106.05(d)(II)(v)). It does not integrate the claims into a practical application or provide significantly more. Furthermore, determining a set of relevant content to present to a user and executing a user interface module displaying relevant content to the user represent mere instruction to apply the exception to a computer environment.
Furthermore, applicant argues Ex Parte Desjardins on page 18 of the response.
Examiner respectfully disagrees, the claims do not improve upon machine learning technology, but as argues appear to display financial data to the user which is mere instruction to apple the exception to a computer environment. (See MPEP 2106.05(f)(1))
Therefore applicant's arguments under 35 U.S.C. § 101 are unpersuasive.
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 21-40 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
In the instant case, claims 21, 30, and 39 are directed to a method, system, and non-transitory computer-readable recording medium.
For the purposes of this analysis, representative claim 21 is addressed. (Step 2A, prong 1) Abstract ideas are in bold below, and represents a “tracking returns on staked tokens” which is a grouped under “Certain methods of organizing human activity — fundamental economic practices” in prong one of step 2A (MPEP 2106.04(a)).
The Examiner has identified method Claim 21 as the claim that represents the claimed invention for analysis and is substantially similar to system Claim 30 and product Claim 39. Claim 21 recites the limitations of:
A method comprising:
receiving, by one or more processors over a communication network, credential information associated with an account of a registered user;
tokenizing, by the one or more processors, the credential information to generate a token;
encrypting, by the one or more processors, the token via an encryption protocol, wherein the encrypted token is unique for each transaction;
authenticating, by the one or more processors utilizing an authentication module, the registered user based, at least in part, on verification of the credential information, wherein the encrypted token is decrypted during the authenticating of the registered user;
integrating, by the one or more processors utilizing a supervised machine learning model, the account associated with the registered user, an account associated with a service provider, and a settlement account, wherein the supervised machine learning model is trained using a combination of one or more stage inputs and known outcomes including one or more stage inputs from any applicable source including any one or more of text, visual representations, data, values, comparisons, and stage outputs;
generating, by the one or more processors utilizing the supervised machine learning model, a refined dataset based on the integrated account associated with the registered user, the account associated with the service provider, and the settlement account;
analyzing, by the one or more processors utilizing the supervised machine learning model, the refined dataset to predict a transaction pattern and determine a first preset time period;
synchronizing, in real-time, by the one or more processors utilizing the supervised machine learning model, transaction information for a plurality of transactions, an outstanding amount, and/or transmitted payments between the account associated with the registered user, the account associated with the service provider, and the settlement account during the first preset time period;
transmitting, by the one or more processors, a payment for the outstanding amount from the settlement account to the account associated with the service provider for the plurality of transactions during the first preset time period;
evaluating, by the one or more processors, using text matching and image matching, content associated with the account of the registered user, wherein the content includes a plurality of content from one or more devices associated with the account of the registered user;
determining, by the one or more processors, a set of relevant content to present to the registered user based on the evaluating;
generating, by the one or more processors utilizing the supervised machine learning model, a dynamic report based on the refined dataset and the transmitted payment for the outstanding amount; and
executing, by the one or more processors, a user interface module displaying the relevant content and the dynamic report on a device of the registered user; and
re-training, by the one or more processors, the supervised machine learning model to increase accuracy of synchronizing transaction information by applying a set of comparison results, wherein the set of comparison results include the synchronized transaction information between the integrated accounts.
The additional elements of claim 21 such as “…by one or more processors over a communication network…”, “ … by the one or more processors, the token via an encryption protocol …”, “…by the one or more processors utilizing an authentication module …”, “…by the one or more processors utilizing the supervised machine learning model…, wherein the supervised machine learning model is trained using a combination of one or more stage inputs and known outcomes including one or more stage inputs from any applicable source including any one or more of text, visual representations, data, values, comparisons, and stage outputs;”, “generating, by the one or more processors utilizing the supervised machine learning model, a refined dataset based on the integrated account associated with the registered user, the account associated with the service provider, and the settlement account”, “analyzing, by the one or more processors utilizing the supervised machine learning model, the refined dataset to predict a transaction pattern and determine a first preset time period”, “executing, by the one or more processors, a user interface module displaying the relevant content and the dynamic report on a device of the registered user,”, “re-training, by the one or more processors, the supervised machine learning model to increase accuracy of synchronizing transaction information by applying a set of comparison results, wherein the set of comparison results include the synchronized transaction information between the integrated accounts” represent the use of a computer as a tool to perform an abstract idea and/or does no more than generally link the abstract idea to a particular field of use. Furthermore, “re-training, …, the supervised machine learning model to increase the accuracy of synchronizing transaction information” lacks detail on how “re-training, …, the supervised machine learning model” is accomplished, therefore it amounts to no more than “apply it” (MPEP 2106.05(f)(1)). Therefore, the additional elements do not integrate the abstract idea into a practical application.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration into a practical application, the additional elements amount to no more than mere instructions to apply the abstract idea of using generic computer components. The claim elements when considered separately and in an ordered combination, do not add significantly more than implementing the abstract idea of aggregating transaction settlement data.
Hence, claim 21, 30 and 39 are not patent eligible.
Claims 22, 31, and 40 recites “aggregating the outstanding amount associated with the plurality of transactions during the first preset time period”, “aggregating the payment transaction during a second preset time period.” However, this does no more than describe the abstract idea. The additional elements of “natural language processing tools” does no more than use a computer as a tool to perform an abstract idea and do no more than generally link the abstract idea to a particular field of use. Therefore, as it is no more than apply it does not improve the functioning of a computer, or improve other technology or technical field.
Claims 23, and 32 recites “wherein the credential information include predefined values, a preset username and password, international mobile equipment identity (IMEI), an electronic serial number, a mobile equipment identity (MEID), and/or one or more identifiers unique to … of the registered user..” However, this does no more than describe the abstract idea. The additional elements of “…a device…” does no more than use a computer as a tool to perform an abstract idea and do no more than generally link the abstract idea to a particular field of use. Therefore, as it is no more than apply it does not improve the functioning of a computer, or improve other technology or technical field.
Claims 24, and 33 recites “processing historical transaction information associated with the registered user to determine a probability of expenses in a next instance of time, wherein the historical transaction information includes past payment transactions”, “determining the expenses for the registered user in the next instance of time exceeds account balance”, “determining one or more preset rules for the registered user based, at least in part, on the determination that the expenses in the next instance of time exceeds the account balance.” However, this does no more than describe the abstract idea.
Claims 25, and 34 recites “processing historical transaction information to determine a credit ranking and a credit score for the registered user, wherein the historical transaction information includes credit history information, income information, debt-to-income ratio information, or a combination thereof”, “determining the first preset time period, the second preset time period, and/or a pre-determined total outstanding amount threshold based on the credit ranking and the credit score.” However, this does no more than describe the abstract idea.
Claims 26, and 35 recites “processing the account of the registered user to determine an account balance is below a pre-determined minimum balance threshold”, “determining the aggregated outstanding amount exceeds the account balance”, “determining to transmit payments for the aggregated outstanding amount during the second preset time period based on historical transaction information of the registered user, wherein the historical transaction information includes a predicted income of the registered user, and wherein the predicted income is sufficient to settle the aggregated transmitted payments.” However, this does no more than describe the abstract idea.
Claims 27, 36, and 40 recites “determining a failure of at least one transaction from the plurality of transactions of the registered user”, “processing the at least one transaction to determine a reason for the failure”, “generating …, wherein … includes an alert on the reason for the failure of the at least one transaction..” However, this does no more than describe the abstract idea. The additional elements of “…a user interface…” does no more than use a computer as a tool to perform an abstract idea and do no more than generally link the abstract idea to a particular field of use. Therefore, as it is no more than apply it does not improve the functioning of a computer or improve other technology or technical field.
Claims 28 and 37 recites “processing historical transaction information associated with the registered user, wherein the historical transaction information includes past payment transactions, shopping basket contents, or a combination thereof”, “determining a benefit program for the registered user based, at least in part, on the processing, wherein the benefit program includes a loyalty program, a coupon redemption program, and/or a lottery program.” However, this does no more than describe the abstract idea.
Claims 29, and 38 recites “wherein the account associated with the registered user and the account associated with the service provider are associated with a same financial institution.” However, this does no more than describe the abstract idea.
The claims as a whole do not amount to significantly more than the abstract idea itself. This is because the claims do not affect an improvement to another technology or technical field, the claims do not amount to an improvement to the functioning of a computer system itself, and the claims do not move beyond a general link of the use of an abstract idea to a particular technological environment.
Accordingly, there are no meaningful limitations in the claims that transform the judicial exception into a patent eligible application such that the claims amount to significantly more than the judicial exception itself.
Prior Art of Record Not Currently Relied Upon
Caldwell (US 2016/0180466 A1) teaches: historical transaction-based account monitoring
Barrett et al (US 9,818,118 B2) teaches: transaction aggregator.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to GREGORY MARK JAMES whose telephone number is (571)272-5155. The examiner can normally be reached M-F 8:30am - 5:00pm EST.
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/GREGORY M JAMES/Examiner, Art Unit 3692
/RYAN D DONLON/Supervisory Patent Examiner, Art Unit 3692 June 26, 2026
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