Prosecution Insights
Last updated: April 19, 2026
Application No. 17/700,125

SYSTEMS AND METHODS FOR DATA AGGREGATION FOR TRANSACTION SETTLEMENT

Non-Final OA §101
Filed
Mar 21, 2022
Examiner
JAMES, GREGORY MARK
Art Unit
3692
Tech Center
3600 — Transportation & Electronic Commerce
Assignee
Worldpay LLC
OA Round
7 (Non-Final)
20%
Grant Probability
At Risk
7-8
OA Rounds
3y 7m
To Grant
33%
With Interview

Examiner Intelligence

Grants only 20% of cases
20%
Career Allow Rate
25 granted / 127 resolved
-32.3% vs TC avg
Moderate +13% lift
Without
With
+13.0%
Interview Lift
resolved cases with interview
Typical timeline
3y 7m
Avg Prosecution
45 currently pending
Career history
172
Total Applications
across all art units

Statute-Specific Performance

§101
48.7%
+8.7% vs TC avg
§103
29.6%
-10.4% vs TC avg
§102
4.1%
-35.9% vs TC avg
§112
13.3%
-26.7% vs TC avg
Black line = Tech Center average estimate • Based on career data from 127 resolved cases

Office Action

§101
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 01/02/2026 has been entered. Status of Claims This action is in reply to the amendment filed on 01/02/2026. Claims 1, 11, and 17 are currently amended. Claims 1-20 are currently pending and have been examined. Response to Arguments Applicant's arguments filed 01/02/2026 have been fully considered but they are not persuasive. Applicant's response the 35 U.S.C. § 101. Applicant argues "claims improve on the current technological infrastructure by generating a refined data set based on a plurality of transactions recorded in the blockchain and using a machine learning model to determine a first preset time period and a second preset time period. The claims describe a method for efficient and accurate "routing of the aggregated data for the settlement of payments" as described in the Specification. (Specification, [0005].)" (response at 19). Examiner respectfully disagrees, the "generating a refined data set based on a plurality of transactions recorded in the blockchain" amounts to fundamental economic practice because the refined data set represents financial data for the purpose of transaction settlement. The machine learning is taught as a method of doing so, but no improvement to machine learning is claimed. Therefore applicant’s argument is not persuasive. Applicant further argues "Second, the claims further improve upon the current technological infrastructure in at least "analyzing . . . context information associated with the registered user to determine relevant content, wherein the context information includes associated with at least one of: computing environment data, a data environment, a plurality of online activities, historical data, preference data, or a combination thereof; executing . . . a user interface module displaying the relevant content based on the context information, wherein the executing of the user interface module is automatically triggered by analyzing the context information; transmitting ... the notification message to the device associated with the registered user via the user interface module, wherein the user interface module displays the notification and relevant content on the device." These claims features describe improvement to the communication infrastructure to provide the registered user with a notification of their routed and processed transactions, as well as relevant content related to context information that is personal to the registered user via the user interface module." Examiner respectfully disagrees, analyzing contextual information and executing a user interface module amount to mere instructions to apply the exception to a computer environment as 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. (See MPEP 2106.05(f)(1)) For at least the reasons stated above applicant’s 101 arguments 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 1-20 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 1, 11, and 17 are directed to a method, system, and non-transitory computer-readable recording medium. For the purposes of this analysis, representative claim 1 is addressed. Abstract ideas are in bold below, and represents tracking repayment status of group payments which is a grouped under “Certain methods of organizing human activity — fundamental economic practices” in prong one of step 2A (MPEP 2106.04(a)). A computer-implemented method comprising: receiving, by one or more processors of a transaction processing system, in real- time, a plurality of transactions associated with an account of a registered user; recording and validating, by the one or more processors of the transaction processing system, the plurality of transactions between the registered user and a merchant in a blockchain, wherein the plurality of transactions are cryptographically secured, timestamped, and added to a decentralized ledger replicated across multiple nodes; generating, by the one or more processors of the transaction processing system using a trained machine learning model, a refined data set based on the plurality of transactions recorded in the blockchain, wherein the trained 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; analyzing, by the one or more processors of the transaction processing system using the trained machine learning model, the refined data set to predict a transaction pattern and determine a first preset time period and a second preset time period; determining, by the one or more processors of the transaction processing system ,an outstanding amount associated with the plurality of transactions within the first preset time period is within a payment threshold level according to a set of rules applied to the account of the registered user; transmitting, by the one or more processors of the transaction processing system, payments for the outstanding amount from a settlement account to an account associated with the merchant to the plurality of transactions based on the first preset time; aggregating, by the one or more processors of the transaction processing system, the transmitted payments based, at least in part, on the second preset time period; determining, by the one or more processors of the transaction processing system, the transmitted payments within the second preset time period are within the payment threshold level according to a set of rules applied to the account of the registered user; transmitting, by the one or more processors of the transaction processing system, an amount that equals the aggregated transmitted payments from the account associated with the registered user to the settlement account based, at least in part, on the second preset time period; synchronizing, in real-time, by the one or more processors of the transaction processing system, transaction information of the plurality of transactions that are cryptographically secured, timestamped, and added to the decentralized ledger replicated across multiple nodes for at least one of: the account associated with the registered user, the account associated with the merchant, and the settlement account; generating, by the one or more processors of the transaction processing system, a notification message including a deduction of the transmitted payments and a request to renew or update the payment threshold level based on the data of the generated refined data set, wherein the notification message is configured to be displayed via a user interface element in a user interface of a device associated with the registered user; analyzing, by the one or more processors of the transaction processing system, context information associated with the registered user to determine relevant content, wherein the context information includes at least one of: computing environment data, a data environment, a plurality of online activities, historical data, preference data, or a combination thereof; executing, by the one or more processors of the transaction processing system, a user interface module displaying the relevant content based on the context information, wherein the executing of the user interface module is automatically triggered by analyzing the context information; transmitting, by the one or more processors of the transaction processing system, the notification message to the device associated with the registered user via the user interface module, wherein the user interface module displays the notification and relevant content on the device; and re-training, by the one or more processors of the transaction processing system, the trained machine learning model with the predicted aggregated outstanding amount, the first time period, and the aggregated outstanding amount to increase processing efficiency for a future plurality of transactions. The additional elements of claim 1 such as “by the one or more processors of the transaction processing system” and “the trained machine learning model,” “generating, by the one or more processors of the transaction processing system, a notification message including a deduction of the transmitted payments and a request to renew or update the payment threshold level based on the data of the generated refined data set, wherein the notification message is configured to be displayed via a user interface element in a user interface of a device associated with the registered user”, “executing, by the one or more processors of the transaction processing system, a user interface module displaying the relevant content based on the context information, wherein the executing of the user interface module is automatically triggered by analyzing the context information”, “transmitting, by the one or more processors of the transaction processing system, the notification message to the device associated with the registered user via the user interface module, wherein the user interface module displays the notification and relevant content on the device”, 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. 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 tracking repayment status of group payments. Hence, claim 1, 8 and 15 are not patent eligible. Dependent claims 2-7, 9-14, and 16-20 recited additional details which only further narrow the abstract idea and do not add any additional features, alone or in combination, that would provide a practical application or provide significantly more. Claims 2, and 18, recites the additional elements of “receiving, over a communication network, access credentials of the registered user”, “wherein the access credentials include predefined values, a preset username and password, international mobile equipment identity (IMEI), an electronic serial number, a mobile equipment identity (MEID), one or more identifiers unique to the device, or a combination thereof”, and “authenticating the registered user based, at least in part, on verification of the access credentials.” represents the use of 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. And, therefore, does not improve the functioning of a computer, or improve other technology or technical field. Claim 7, recites “generating a second user interface element in the user interface, wherein the second user interface element includes an alert on the reason for the failure of the at least one transaction.” represents the use of 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. And, therefore, does not improve the functioning of a computer, or improve other technology or technical field. Claim 10, recites “wherein the user interface element includes a notification...” represents the use of 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. And, therefore, does not improve the functioning of a computer, or improve other technology or technical field. Claim 12, recites the additional elements of “receive, over a communication network, access credentials of the registered user”, “wherein the access credentials include predefined values, a preset username and password, international mobile equipment identity (IMEI), an electronic serial number, a mobile equipment identity (MEID), one or more identifiers unique to the device, or a combination thereof”, and “authenticate the registered user based, at least in part, on verification of the access credentials.” represents the use of 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. And, therefore, does not improve the functioning of a computer, or improve other technology or technical field. 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. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ryan Donlon can be reached at 571-270-3602. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /GREGORY M JAMES/Examiner, Art Unit 3692 /RYAN D DONLON/Supervisory Patent Examiner, Art Unit 3692 March 23, 2026
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Prosecution Timeline

Mar 21, 2022
Application Filed
Jun 17, 2023
Non-Final Rejection — §101
Sep 25, 2023
Response Filed
Jan 26, 2024
Final Rejection — §101
Apr 15, 2024
Response after Non-Final Action
Apr 26, 2024
Response after Non-Final Action
May 15, 2024
Request for Continued Examination
May 16, 2024
Response after Non-Final Action
Jun 14, 2024
Non-Final Rejection — §101
Sep 17, 2024
Applicant Interview (Telephonic)
Sep 17, 2024
Examiner Interview Summary
Sep 24, 2024
Response Filed
Jan 06, 2025
Final Rejection — §101
Feb 28, 2025
Applicant Interview (Telephonic)
Mar 04, 2025
Examiner Interview Summary
Mar 20, 2025
Response after Non-Final Action
Apr 21, 2025
Request for Continued Examination
Apr 28, 2025
Response after Non-Final Action
May 17, 2025
Non-Final Rejection — §101
Sep 19, 2025
Response Filed
Sep 29, 2025
Final Rejection — §101
Dec 12, 2025
Response after Non-Final Action
Jan 02, 2026
Request for Continued Examination
Jan 20, 2026
Response after Non-Final Action
Feb 07, 2026
Non-Final Rejection — §101 (current)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

7-8
Expected OA Rounds
20%
Grant Probability
33%
With Interview (+13.0%)
3y 7m
Median Time to Grant
High
PTA Risk
Based on 127 resolved cases by this examiner. Grant probability derived from career allow rate.

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