DETAILED ACTION
Status of Claims
This action is in reply to amendment and response filed on 12/1/25. Claim 1 was amended. Claims 1-2, 5-7, 9, 12-14, 22 and 24-25 are pending and examined.
Response to Arguments
101: Applicant’s amendments and arguments were considered but are not persuasive.
The Applicant essentially argues that the amended claims overcome the rejection.
The Examiner disagrees.
prong 1 step 2A, page 9, section A,
1: Examiner disagrees with Applicant’s not a mathematical concept argument in relation to training and executing machine learning models. Training and use of machine learning models is directed to mathematical concepts in particular mathematical relationships because mere use of machine learning is “organizing information and manipulating information through mathematical correlations”, see MPEP 2106.04(a)(2)(A)(iv).
2: Examiner agrees, furthermore the rejections never have, nor the current rejection mentions mental processes.
3: Examiner disagrees with Applicant’s not organizing human activity argument because at least the following limitations in representative claim 1 recite an abstract idea: “… to generate a genuineness score for a wire payment, wherein the set of training data comprises pre-validation data for payment transactions”, “determining, …, a genuineness rating for a proposed wire payment from a payer to a payee, wherein determining the genuineness rating comprises”, “receiving, …, the proposed wire payment from the payer …”, “obtaining, …, a first set of pre-validation data for the proposed wire payment …, wherein obtaining the first set of pre-validation data comprises …”.
prong 2 step 2A, pp. 7-8, section B,
1. Applicant argues that training and deploying a machine learning model integrates the abstract idea into a practical application. The examiner disagrees. In the representative claim 1, the limitations “training, by a training computer system, through machine learning, on a set of training data, a machine learning model to generate a genuineness score” and “after training the machine learning model, determining, by a deployment computer system, by executing the machine learning model on the deployment computer system, a genuineness rating” recite the abstract idea of fraud determination for a pre-stage wire transfer that encompasses generating a genuineness rating of the pre-stage wire transfers with additional elements.
The additional elements do not integrate the abstract idea into a practical application as they are no more than “apply it” because “training, by a training computer system, through machine learning, on [a set of training data, a] machine learning [model]” are mere “[u]se of a computer or other machinery in its ordinary capacity for economic or other tasks”, see MPEP 2106.05(f)(2). Furthermore, these additional elements also do not integrate the abstract idea into a practical application because they are no more than “apply it” as the claim fails to recite the details of how “a machine learning model” is trained with “a set of training data” to generate “a genuineness score”, see MPEP 2106.05(f)(1). “machine learning” is also general linking as it does no more than link the use of the abstract idea to a particular technological environment or field of use, see MPEP 2106.05(h).
The additional elements also do not integrate the abstract idea into a practical application as they are no more than “apply it” because “after training …, [determining], by a deployment computer system, by executing [the] machine learning [model] on the deployment computer system, [a genuineness rating]” are mere “[u]se of a computer or other machinery in its ordinary capacity for economic or other tasks”, see MPEP 2106.05(f)(2). Furthermore, these additional elements also do not integrate the abstract idea into a practical application because they are no more than “apply it” as the claim fails to recite the details of how “executing the machine learning model” determines the “genuineness rating”, see MPEP 2106.05(f)(1).
2. Applicant argues additional improvements with which the Examiner disagrees.
- Real time transformation of information is not an improvement as it is merely “apply it” because it is mere “[u]se of a computer or other machinery in its ordinary capacity for economic or other tasks”, see MPEP 2106.05(f)(2).
- Reducing false positives and false negatives merely furthers the abstract idea. Mere use of machine learning to implement the abstract idea is not an improvement and does not integrate the abstract idea into a practical application because they are no more than “apply it” as the claim fails to “recite the details of a solution to how a problem is accomplished”, see MPEP 2106.05(f)(1).
- automating pre-validation checks is not an improvement as it is merely “apply it” because it is mere “[u]se of a computer or other machinery in its ordinary capacity for economic or other tasks”, see MPEP 2106.05(f)(2).
- enabling more secure and efficient routing of payment information is not an improvement and does not integrate the abstract idea into a practical application because they are no more than “apply it” as the claim fails to “recite the details of how a solution to a problem is accomplished”, see MPEP 2106.05(f)(1).
3. The additional elements recited in the Applicant’s claims do not integrate the abstract idea into a practical application and/or provide an improvement as a whole as they are merely “apply it” because it is mere “[u]se of a computer or other machinery in its ordinary capacity for economic or other tasks”, see MPEP 2106.05(f)(2) and/or they are no more than “apply it” as the claim fails to “recite the details of how a solution to a problem is accomplished”, see MPEP 2106.05(f)(1).
As such, the claims as a whole merely recite an improvement to a business a process not technology.
Step 2B, p. 9, sections C, D,
As previously stated, the claims as a whole do not integrate the abstract idea into a practical application and are not improvement as a whole because the additional elements such as the use of machine learning in the claims amounts to mere “apply it” because the additional elements are mere “[u]se of a computer or other machinery in its ordinary capacity for economic or other tasks”, see MPEP 2106.05(f)(2) and/or they are no more than “apply it” as the claims fail to “recite the details of how a solution to a problem is accomplished”, see MPEP 2106.05(f)(1).
As such, the rejection is maintained and an updated rejection is provided that addresses the amended claims.
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 1-2, 5-7, 9, 12-14, 22 and 24-25 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. (Step 1) The claims recite a process (claims 1-2, 5-7, 9, 12-14, 22 and 24-25). For the purposes of this analysis, representative claim 1 is addressed. (Step 2A, prong 1) Abstract ideas are in bold below, and represent organizing human activity as a method of fraud determination for a pre-stage wire transfer, as are all a form of commercial or legal interactions and managing personal behavior or relationships or interactions between people.
training, by a training computer system, through machine learning, on a set of training data, a machine learning model to generate a genuineness score for a wire payment, wherein the set of training data comprises pre-validation data for payment transactions from an intra-bank payment network, compliance data, and user transaction history; and
after training the machine learning model, determining, by a deployment computer system, by executing the machine learning model on the deployment computer system, a genuineness rating for a proposed wire payment from a payer to a payee, wherein determining the genuineness rating comprises:
receiving, by the deployment computer system, the proposed wire payment from the payer via a request-response application protocol over a network;
obtaining, by the deployment computer system, a first set of pre-validation data for the proposed wire payment from the intra-bank payment network, wherein obtaining the first set of pre-validation data comprises making API calls to the intra-bank payment network, wherein the API calls comprise: a payment account-format API call; an account verification API call; a payment financial institution identity API call; a payment purpose code API call; a payment purpose API call; and a payment category purpose API call;
obtaining, by the deployment computer system, a second set of data via internal compliance databases;
determining, by the deployment computer system, a genuineness score for the proposed wire payment based on at least a transformation of the first set of data and the second set of data by the machine learning model;
generating, by the deployment computer system, a data structure indicating whether the proposed wire payment is to: (i) proceed, (ii) be reviewed, or (iii) be rejected based on thresholding the genuineness score.
(Step 2A prong 2) The additional elements are as follows:
“training, by a training computer system, through machine learning, on [a set of training data, a] machine learning [model to generate a genuineness score …] from an intra-bank payment network […]”. The additional elements do not integrate the abstract idea into a practical application as they are no more than “apply it” because “training, by a training computer system, through machine learning, on [a set of training data, a] machine learning [model]” and the “intra-bank payment network” are mere “[u]se of a computer or other machinery in its ordinary capacity for economic or other tasks”, see MPEP 2106.05(f)(2). Furthermore, these additional elements also do not integrate the abstract idea into a practical application because they are no more than “apply it” as the claim fails to recite the details of how “a machine learning model” is trained with “a set of training data” to generate “a genuineness score”, see MPEP 2106.05(f)(1). “machine learning” is also general linking as it does no more than link the use of the abstract idea to a particular technological environment or field of use, see MPEP 2106.05(h).
“[determining], by a deployment computer system, by executing [the] machine learning [model] on the deployment computer system, [a genuineness rating…]”. The additional elements do not integrate the abstract idea into a practical application as they are no more than “apply it” because the “deployment computer system” and “executing [the] machine learning [model] on the deployment computer system” are mere “[u]se of a computer or other machinery in its ordinary capacity for economic or other tasks”, see MPEP 2106.05(f)(2). Furthermore, these additional elements also do not integrate the abstract idea into a practical application because they are no more than “apply it” as the claim fails to recite the details of how “executing the machine learning model” determines the “genuineness rating”, see MPEP 2106.05(f)(1).
[receiving], by the deployment computer system, […], via a request-response application protocol over a network […]. The additional elements do not integrate the abstract idea into a practical application as they are no more than “apply it” because “a request-response application protocol over a network” is mere “[u]se of a computer or other machinery in its ordinary capacity for economic or other tasks”, see MPEP 2106.05(f)(2).
“[determining], by the deployment computer system, […] based on at least a transformation of [the first set of data and the second set of data] by the machine learning model”. The additional elements do not integrate the abstract idea into a practical application as they are no more than “apply it” because “transformation of [the first set of data and the second set of data]” is mere “[u]se of a computer or other machinery in its ordinary capacity for economic or other tasks”, see MPEP 2106.05(f)(2).
(Step 2B) The claim does 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 do no more than provide mere instructions to apply the abstract idea 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 fraud determination for a pre-stage wire transfer, over a generic computer network with generic computing elements, and generic hardware.
Analysis of dependent claims 2 and 9 recite additional elements that include:
“wherein the intra-bank payment network comprises a global intra-bank payment network”. The additional elements do not integrate the abstract idea into a practical application as they are no more than “apply it” because the “global intra-bank payment network” is mere “[u]se of a computer or other machinery in its ordinary capacity for economic or other tasks”, see MPEP 2106.05(f)(2).
The claims also 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 do no more than provide mere instructions to apply the abstract idea 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 fraud determination for a pre-stage wire transfer, over a generic computer network with generic computing elements, and generic hardware.
Analysis of dependent claims 5 and 12 recite “wherein the second set of data comprises user transaction history information stored in a financial institution transaction database” additional details which further narrow the abstract idea and additional elements that include:
“[…] stored in a financial institution transaction database”. The additional elements do not integrate the abstract idea into a practical application as they are no more than “apply it” because “stored in a financial institution transaction database” is mere “[u]se of a computer or other machinery in its ordinary capacity for economic or other tasks”, see MPEP 2106.05(f)(2).
The claims also 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 do no more than provide mere instructions to apply the abstract idea 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 fraud determination for a pre-stage wire transfer, over a generic computer network with generic computing elements, and generic hardware.
Analysis of dependent claims 6 and 13 recite “wherein a user interface displays the genuineness score rating in rating categories, wherein a first rating category signifies that the proposed wire payment can proceed, a second rating category signifies that the proposed wire payment should be reviewed, and a third rating category signifies that the proposed wire payment should be rejected” additional details which further narrow the abstract idea and additional elements that include:
“a user interface displays […]”. The additional elements do not integrate the abstract idea into a practical application as they are no more than “apply it” because the “user interface displays” is mere “[u]se of a computer or other machinery in its ordinary capacity for economic or other tasks”, see MPEP 2106.05(f)(2).
The claims also 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 do no more than provide mere instructions to apply the abstract idea 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 fraud determination for a pre-stage wire transfer, over a generic computer network with generic computing elements, and generic hardware.
Analysis of dependent claims 7 and 14 recite additional elements that include:
“wherein the machine learning model comprises a linear regression model”. The additional elements do not integrate the abstract idea into a practical application as they are no more than “apply it” because the “linear regression model” is mere “[u]se of a computer or other machinery in its ordinary capacity for economic or other tasks”, see MPEP 2106.05(f)(2).
The claims also 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 do no more than provide mere instructions to apply the abstract idea 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 fraud determination for a pre-stage wire transfer, over a generic computer network with generic computing elements, and generic hardware.
Analysis of dependent claim 24 recites “wherein obtaining the second set of data via internal compliance databases comprises obtaining, by the deployment computer system, the second set of data from the internal compliance databases via Java database connectivity APIs” additional details which further narrow the abstract idea and additional elements that include:
“[obtaining], …, [the second set of data] … via Java database connectivity APIs”. The additional elements do not integrate the abstract idea into a practical application as they are no more than “apply it” because the “Java database connectivity APIs” is mere “[u]se of a computer or other machinery in its ordinary capacity for economic or other tasks”, see MPEP 2106.05(f)(2).
The claims also 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 do no more than provide mere instructions to apply the abstract idea 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 fraud determination for a pre-stage wire transfer, over a generic computer network with generic computing elements, and generic hardware.
Analysis of dependent claim 25 recites “displaying, by a web server, a web-based user interface that displays [the genuineness score rating …]” additional details which further narrow the abstract idea and additional elements that include:
“displaying, by a web server, a web-based user interface that displays”. TThe additional elements do not integrate the abstract idea into a practical application as they are no more than “apply it” because “displaying, by a web server, a web-based user interface that displays” is mere “[u]se of a computer or other machinery in its ordinary capacity for economic or other tasks”, see MPEP 2106.05(f)(2).
The claims also 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 do no more than provide mere instructions to apply the abstract idea 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 fraud determination for a pre-stage wire transfer, over a generic computer network with generic computing elements, and generic hardware.
Analysis of dependent claim 22 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.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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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/BROCK E TURK/Examiner, Art Unit 3692
/RYAN D DONLON/Supervisory Patent Examiner, Art Unit 3692 June 2, 2026
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