DETAILED ACTION
Status of Claims
1. This office action is in response to amendment filed 2/26/2026.
2. Claims 25-36, 39, 41-45, 48, 50, 84 are pending.
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 .
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 25-36, 39, 41-45, 48, 50, 84
Claims 25-36, 39, 41-45, 48, 50, 84 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.
Step 1: Claims 25-33, 84 are directed to a method; claims 34-42 are directed to a system; claims 43-50 are directed to a non-transitory computer-readable medium – each of which is one of the statutory categories of inventions.
Step 2A: A claim is eligible at revised Step 2A unless it recites a judicial exception and the exception is not integrated into a practical application of the application.
Prong 1: Prong One of Step 2A evaluates whether the claim recites a judicial exception (an abstract idea enumerated in the 2019 PEG, a law of nature, or a natural phenomenon).
Groupings of Abstract Ideas:
I. MATHEMATICAL CONCEPTS
A. Mathematical Relationships
B. Mathematical Formulas or Equations
C. Mathematical Calculations
II. CERTAIN METHODS OF ORGANIZING HUMAN ACTIVITY
A. Fundamental Economic Practices or Principles (including hedging, insurance, mitigating risk)
B. Commercial or Legal Interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations)
C. Managing Personal Behavior or Relationships or Interactions between People (including social activities, teaching, and following rules or instructions)
III. MENTAL PROCESSES.
Concepts performed in the human mind (including an observation, evaluation, judgment, opinion).
See MPEP 2106.04 (a) (2) Abstract Idea Groupings [R-10.2019]
The limitations of the independent claims 25, 34 and 43 – examining contents of the payment transaction, wherein the contents of the payment transaction includes a transaction type; examining metadata associated with the payment transaction, wherein the metadata includes a payment rail preference; determining whether the payment rail preference is available for processing the payment transaction; selecting an alternative payment rail on a condition that the payment rail preference is unavailable; reformatting the payment transaction to match the format of the selected alternative payment rail on a condition that the payment transaction is not in the format of the selected alternative payment rail; and routing the payment transaction to the selected alternative payment rail for processing – fall under the abstract idea groupings Mental Process and/or Certain Methods of Organizing Human Activity.
The dependent limitations recite limitations –
(Claims 26, 35) determining whether the payment rail preference matches a payment rail associated with the transaction type; and reformatting the payment transaction to match the format of the payment rail preference on a condition that the payment rail associated with the transaction type does not match the payment rail preference.
(Claim 27) wherein the payment rail preference includes a payment rail having a lowest cost based on the transaction type.
(Claim 28) wherein the payment rail preference includes a payment rail having a shortest completion time based on the transaction type.
(Claim 29) wherein the payment rail preference includes a caller-preferred route.
(Claim 30) wherein the payment rail preference is based on a type of caller.
(Claim 31) wherein the caller is one of a bank, a fintech, or a corporation.
(Claim 32, 41) training a decision-type machine learning model based on previous routes for a given transaction type; and
using the trained machine learning model to determine a payment rail for routing the payment transaction based on the transaction type and the payment rail preference.
(Claim 33, 42) wherein the trained machine learning model is configured to reformat the payment transaction to match a format of the determined payment rail.
(Claim 36, 45) wherein the payment rail preference includes any one of: a payment rail having a lowest cost based on the transaction type; a payment rail having a shortest completion time based on the transaction type; or a caller-preferred route.
(Claim 39, 48) the payment rail preference is based on a type of caller; and the caller is one of a bank, a fintech, or a corporation.
(Claim 44) determining whether the payment rail preference matches a payment rail associated with the transaction type; and reformatting the payment transaction to match the format of the payment rail preference on a condition that the payment rail associated with the transaction type does not match the payment rail preference.
(Claim 50) training a decision-type machine learning model based on previous routes for a given transaction type; using the trained machine learning model to determine a payment rail for routing the payment transaction based on the transaction type and the payment rail preference; and reformatting the payment transaction, by the trained machine learning model, to match a format of the determined payment rail.
(Claim 84) wherein the payment rail preference is unavailable based on a transaction cost or a transaction completion time not meeting metadata associated with the payment transaction.
– that also fall under Mental Process and/or Certain Methods of Organizing Human Activity.
Hence under Prong One of Step 2A, claims 25-36, 39, 41-45, 48, 50, 84 recite a combination of judicial exceptions.
Prong 2: Prong Two of Step 2A evaluates whether the claim recites additional elements that integrate the judicial exception into a practical application of the exception.
Limitations that are indicative of integration into a practical application include:
Improvements to the functioning of a computer or to any other technology or technical field – see MPEP 2106.05(a)
Applying the judicial exception with, or by use of, a particular machine – see MPEP 2106.05(b)
Effecting a transformation or reduction of a particular article to a different state or thing – see MPEP 2106.05(c)
Applying or using the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception – see MPEP 2106.05(e)
Limitations that are not indicative of integration into a practical application include:
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 – see MPEP 2106.05(f)
Adding insignificant extra-solution activity to the judicial exception – see MPEP 2106.05(g)
Generally linking the use of the judicial exception to a particular technological environment or field of use – see MPEP 2106.05(h)
Additional elements recited by the claims, beyond the abstract idea, include: a system comprising processor and memory; non- transitory computer-readable medium; and machine learning model. Examiner finds that any additional element(s), beyond the judicial exception, has been recited at a high level of generality such that the claim limitations amount to no more than mere instructions to apply the exception using generic components (see MPEP 2106.05(f)) or insignificant data gathering activities (see MPEP 2106.05(g)). The combination of additional elements does not purport to improve the functioning of a computer or effect an improvement in any other technology or technical field. Instead, the additional elements do no more than “use the computer as a tool” and/or “link the use of the judicial exception to a particular technological environment or field of use.” The focus of the claims is not on improvement in computers, but on certain independently abstract ideas – examining contents of the payment transaction, wherein the contents of the payment transaction includes a transaction type; examining metadata associated with the payment transaction, wherein the metadata includes a payment rail preference; determining whether the payment rail preference is available for processing the payment transaction; selecting an alternative payment rail on a condition that the payment rail preference is unavailable; reformatting the payment transaction to match the format of the selected alternative payment rail on a condition that the payment transaction is not in the format of the selected alternative payment rail; and routing the payment transaction to the selected alternative payment rail for processing – that merely uses generic computers as tools. Steps that do no more than spell out what it means to “apply it on a computer” cannot confer patent eligibility. Indeed, nothing in claim 1 improves the functioning of the computer, makes it operate more efficiently, or solves any technological problem. See Trading Techs. Int’l, Inc. v. IBG LLC, 921 F.3d 1378, 1384-85 (Fed. Cir. 2019).
Hence, the additional elements, individually and in combination, do not integrate the judicial exception into a practical application.
Hence, the claims are ineligible under Step 2A.
Step 2B: In Step 2B, the evaluation consists of whether the claim recites additional elements that amount to an inventive concept (aka “significantly more”) than the recited judicial exception.
As discussed in Prong Two, the additional elements in the claims amount to no more than mere instructions to apply the exception using generic components. When considered individually or as an ordered combination, the additional elements fail to transform the abstract idea of – examining contents of the payment transaction, wherein the contents of the payment transaction includes a transaction type; examining metadata associated with the payment transaction, wherein the metadata includes a payment rail preference; determining whether the payment rail preference is available for processing the payment transaction; selecting an alternative payment rail on a condition that the payment rail preference is unavailable; reformatting the payment transaction to match the format of the selected alternative payment rail on a condition that the payment transaction is not in the format of the selected alternative payment rail; and routing the payment transaction to the selected alternative payment rail for processing – into significantly more.
See MPEP 2106.05(f) Mere Instructions To Apply An Exception [R-10.2019].
(2) Whether the claim invokes computers or other machinery merely as a tool to perform an existing process. Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more.
Hence, the claims are ineligible under Step 2B.
Therefore, the claim(s) are rejected under 35 U.S.C. 101 as being directed to a judicial exception without significantly more.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 25-36, 39, 41-45, 48, 50, 84
Claims 25-36, 39, 41-45, 48, 50, 84 are rejected under 35 U.S.C. 103 as being unpatentable over Chistolini et al. (US20240242224) in view of Yusin (US20040128240A1).
Claim 25:
A method for routing a payment transaction in a real-time payments system, comprising:
receiving the payment transaction;
examining contents of the payment transaction, wherein the contents of the payment transaction includes a transaction type;
(See Chistolini: Para [0027] (“Data that a payment method selection model 213 may use to select a payment rail for a transaction include, as described above: (i) payee risk profiles 212; (ii) payment origination risk profiles 232; (iii) payer (and optionally payee) preference data 211; and/or (iv) global rail characteristics 234 (which are described in more detail below in the discussion of FIG. 3 ). The payer (or payee) preference data 211, global rail characteristics 234, and/or the payee risk profile 212 may identify or contain information that is relevant to its corresponding entity's preferred payment rails, and the model may consider this data when selecting the payment rail for the transaction.”)
examining metadata associated with the payment transaction, wherein the metadata includes a payment rail preference;
(See Chistolini: Para [0025] (“The risk profiles described above, along with preference information 211 provided by (or available in a profile of) the payer 101 and/or payee 102, will be fed to a payment method selection model 213. The preference information 211 may include information such as the payer's preferred payment rail(s), identification of payment rails that are supported by both the payer's account and the payee's account, cost and delivery windows associated with use of the payment rail, and a minimum or maximum amount that each payment rail or account permits. The preference information 211 also may include other data, objectives, or constraints.”)
determining whether the payment rail preference is available for processing the payment transaction;
(See Chistolini: Para [0048] (“At 313 the system will use the payee account risk profile to validate that the payee account will successfully process on the selected payment rail. If the system cannot validate this, then it may not continue with the transaction. Instead, the system may select an alternative payee account or ask the user to select an alternative account, and the system may then attempt to validate the alternative account. Alternatively or in addition, the system may inform a user that the selected payee account could not be validated.”)
selecting an alternative payment rail on a condition that the payment rail preference is unavailable;
(See Chistolini: Para [0042] (“Alternatively, at 308 the system may classify multiple candidate payment rails that most closely satisfy payer preferences and/or risk criteria, and the system may present all such candiate rails to a user for selection of the final rail to be used. When doing so, optionally the system may classify one of the presented rails as optimal and the other rail(s) as alternative(s).”)
…
routing the payment transaction to the selected alternative payment rail for processing.
(See Chistolini: Para [0049] (“If the user selects an alternate payee account or payment rail as the payment method, the system may declassify the optimal payee account or transaction rail that the transaction model selected and include the alternate payee account and/or transactional rail in the payment initialization data as the selected payment method. The payment initialization data will be a digital file, a data feed, a message, or other data structure that is be in a format that a financial entity can use to complete the transfer of assets from a payer account that associated with the payer to the selected payee account, using the selected payment rail. At 315 the system will transmit the payment initialization data to the financial institution that holds the payer's account so that the institution can use the file/data feed to initiate the payment via the payment rail.”)
Chistolini does not specifically disclose:
reformatting the payment transaction to match the format of the selected alternative payment rail on a condition that the payment transaction is not in the format of the selected alternative payment rail; and
However, Yusin discloses the above limitation
(See Yusin: Para [0052] (“Detail Records for U.S. transactions are preferably converted into a U.S. standard formatted file. Currently, the standard format for U.S. transactions is the National Automated Clearing House Association (“NACHA”) format, which is known in the art. Detail Records for international transactions are converted into an international formatted file. Currently, the standard format for international transactions is the United Nations Electronic Data Exchange Administration, Commerce and Transport format (“UN/EDIFACT”), which is also known in the art. If the Clearing Network is ABN AMRO Bank, Amsterdam Netherlands (“ABN AMRO”), the Detail Records in the Basic Funding File for all transactions are converted into the UN/EDIFACT format for all cash transfers, including transfers of U.S. dollars to a U.S. bank account. The converted Basic Funding Files, formatted for U.S. and for international transactions, are referred to herein as a “Worldwide Funding Files.””)
Therefore, it would have been obvious to a person having ordinary skills in the art before the effective filing date of the invention to modify the above noted disclosure of Chistolini as it relates to payment rail verification to include Yusin as it relates to managing and monitoring cash transfers. The motivation for combining the references would have been to train the machine learning model on country level wire transfer monetary threshold.
Claims 34, 43 are similar to claim 25 and hence rejected on similar grounds.
Claim 26:
determining whether the payment rail preference matches a payment rail associated with the transaction type; and
reformatting the payment transaction to match the format of the payment rail preference on a condition that the payment rail associated with the transaction type does not match the payment rail preference.
(See Yusin: Para [0052])
Claims 35, 44 are similar to claim 26 and hence rejected on similar grounds.
Claim 27:
wherein the payment rail preference includes a payment rail having a lowest cost based on the transaction type.
(See Chistolini: Para [0061])
Claim 28:
wherein the payment rail preference includes a payment rail having a shortest completion time based on the transaction type.
(See Chistolini: Para [0026])
Claim 29:
wherein the payment rail preference includes a caller-preferred route.
(See Chistolini: Para [0025])
Claim 30:
wherein the payment rail preference is based on a type of caller.
(See Chistolini: Para [0013])
Claim 31:
wherein the caller is one of a bank, a fintech, or a corporation.
(See Chistolini: Para [0013])
Claim 32:
training a decision-type machine learning model based on previous routes for a given transaction type; and
using the trained machine learning model to determine a payment rail for routing the payment transaction based on the transaction type and the payment rail preference.
(See Chistolini: Para [0027])
Claim 41 is similar to claim 32 and hence rejected on similar grounds.
Claim 33:
wherein the trained machine learning model is configured to reformat the payment transaction to match a format of the determined payment rail.
(See Chistolini: Para [0042])
Claim 42 is similar to claim 33 and hence rejected on similar grounds.
Claim 36:
wherein the payment rail preference includes any one of:
a payment rail having a lowest cost based on the transaction type;
a payment rail having a shortest completion time based on the transaction type; or
a caller-preferred route.
(See Chistolini: Para [0026])
Claim 45 is similar to claim 36 and hence rejected on similar grounds.
Claim 39:
the payment rail preference is based on a type of caller; and
the caller is one of a bank, a fintech, or a corporation.
(See Chistolini: Para [0013])
Claim 48 is similar to claim 39 and hence rejected on similar grounds.
Claim 50:
training a decision-type machine learning model based on previous routes for a given transaction type;
using the trained machine learning model to determine a payment rail for routing the payment transaction based on the transaction type and the payment rail preference; and
reformatting the payment transaction, by the trained machine learning model, to match a format of the determined payment rail.
(See Chistolini: Para [0026])
Claim 84:
wherein the payment rail preference is unavailable based on a transaction cost or a transaction completion time not meeting metadata associated with the payment transaction.
(See Chistolini: Para [0025], [0026])
Response to Arguments
Applicant's arguments filed 2/26/2026 have been fully considered but they are not persuasive.
101
Applicant argues that “reformatting the payment transaction to match the format of the selected alternative payment rail on condition that the payment rail preference is unavailable” is not an abstract idea or insignificant extra solution activity.
Examiner respectfully disagrees.
Examiner notes that the claimed “reformatting” has been described in the claims at a high level of generality where the claim recites only the idea of a solution or outcome without reciting how such “reformatting” is accomplished. See MPEP 2106.05 (f) (1) (“By way of example, in Intellectual Ventures I v. Capital One Fin. Corp., 850 F.3d 1332, 121 USPQ2d 1940 (Fed. Cir. 2017), the steps in the claims described “the creation of a dynamic document based upon ‘management record types’ and ‘primary record types.’” 850 F.3d at 1339-40; 121 USPQ2d at 1945-46. The claims were found to be directed to the abstract idea of “collecting, displaying, and manipulating data.” 850 F.3d at 1340; 121 USPQ2d at 1946. In addition to the abstract idea, the claims also recited the additional element of modifying the underlying XML document in response to modifications made in the dynamic document. 850 F.3d at 1342; 121 USPQ2d at 1947-48. Although the claims purported to modify the underlying XML document in response to modifications made in the dynamic document, nothing in the claims indicated what specific steps were undertaken other than merely using the abstract idea in the context of XML documents. The court thus held the claims ineligible, because the additional limitations provided only a result-oriented solution and lacked details as to how the computer performed the modifications, which was equivalent to the words “apply it”. 850 F.3d at 1341-42; 121 USPQ2d at 1947-48 (citing Electric Power Group., 830 F.3d at 1356, 1356, USPQ2d at 1743-44 (cautioning against claims “so result focused, so functional, as to effectively cover any solution to an identified problem”)).”).
Examiner also points out that the Federal Circuit has held that “converting information from one format to another … is an abstract idea.” See AI Visualize v. Nuance (quoting Hawk Tech. Sys., LLC v. Castle Retail, LLC, 60 F.4th 1349 (Fed. Cir. 2023).). See also Adaptive Streaming Inc. v. Netflix, Inc., 836 F. App’x 900, 903 (Fed. Cir. 2020) (non-precedential) (holding that “format conversion” generally, without “any specific advance in coding or other techniques for implementing that idea” is abstract).
For the above reasons, the Applicant’s arguments are not persuasive.
103
Applicant’s arguments with respect to claim(s) Claims 25-36, 39, 41-45, 48, 50, 84 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ARUNAVA CHAKRAVARTI whose telephone number is (571)270-1646. The examiner can normally be reached 9 AM - 5 PM ET.
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.
/ARUNAVA CHAKRAVARTI/Primary Examiner, Art Unit 3692
Prosecution Insights