DETAILED ACTION
Status of Claims
1. This office action is in response to amendment fild 2/27/2026.
2. Claims 1, 2, 4-11, 13-20, 22-27 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 1, 2, 4-11, 13-20, 22-27
Claims 1, 2, 4-11, 13-20, 22-27 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 1-9 are directed to a method, 10-18 are directed to a system, 19-27 to a computer readable storage 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]
Independent claims 1, 10 and 19 recite the limitations –
receiving user pre-qualification request and preferences associated with secured and unsecured payment instruments;
receiving a preliminary credit evaluation corresponding to the user, wherein the preliminary credit evaluation is received using the user information;
processing the user information, the set of preferences, and the preliminary credit evaluation through an offer generation machine learning algorithm to identify one or more recommended payment instruments, wherein the one or more recommended payment instruments are identified based on a cluster of users identified by the offer generation machine learning algorithm according to a set of similarity vectors corresponding to features of preliminary credit evaluations, and wherein the offer generation machine learning algorithm is trained using an offer dataset of historical data including previous pre-qualification determinations and corresponding feedback;
[updating an interface implemented on a user device associated with the user] to display one or more recommended offers corresponding to the one or recommended payment instruments;
receiving an application for a payment instrument associated with an offer selected from the one or more recommended offers, [wherein the application is received through an interface];
processing the application through an approval machine learning algorithm to determine that the user is approved for the payment instrument, wherein the approval machine learning algorithm is trained using an approval dataset of historical applications for different payment instruments and corresponding application determinations;
updating the offer dataset and the approval dataset according to real-time credit performance corresponding to the user and with other users associated with other issued secured and unsecured payment instruments;
retraining the offer generation machine learning algorithm and the approval machine learning algorithm using the updated offer dataset and the updated approval dataset; and
processing new user information, new preferences, and new preliminary credit evaluations associated with different users through the retrained offer generations machine learning algorithm to identify new recommended payment instruments for the different users.
– that fall under the abstract idea groupings of Mathematical Concepts (machine learning algorithm) and Certain Methods of Organizing Human Activity (credit evaluation, recommended payment instruments, offer generation, user approval).
The dependent claims further limit the abstract idea to –
processing a complete credit evaluation associated with the user and the information through the offer generation machine learning algorithm to identify a new set of offers corresponding to different payment instruments; processing the new set of offers through the approval machine learning algorithm to identify an alternative set of offers corresponding to an alternative set of payment instruments and a set of incentives for selecting from the alternative set of offers; and updating the interface to present the alternative offers and the set of incentives;
tracking the real-time credit performances associated with the user and other users wherein the real-time credit performance corresponds to usage of the payment instrument and to usage of the other issued secured and unsecured payment instruments;
wherein the one or more recommended offers include an offer corresponding to a secured dual-feature payment instrument, and wherein the offer indicates a security deposit for the dual-feature payment instrument;
wherein the one or more recommended offers include details corresponding to benefits and terms associated with the one or more recommended payment instruments;
receiving another application for an alternative payment instrument, wherein the alternative payment instrument does not correspond to the one or more recommended offers and updating the offer dataset using the other application for the alternative payment instrument, wherein the offer dataset is updated, the offer dataset is used to further retrain the offer generation machine learning algorithm;
wherein the historical data further includes previously issued payment instrument corresponding to the user; wherein the historical data further includes previously issued payment instruments corresponding to other users
– that also constitute Mathematical Concepts and Certain Methods of Organizing Human Activity.
Hence under Prong One of Step 2A, the claims recite a combination of judicial exception(s). See RecogniCorp, LLC v. Nintendo Co., 855 F.3d 1322, 1327 (Fed. Cir. 2017) (“Adding one abstract idea (math) to another abstract idea (encoding and decoding) does not render the claim non-abstract.”).
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:
Merely reciting the words “apply it” (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using the 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 processors and memory; a non-transitory computer readable storage medium; interface implemented on a user device; and training/retraining machine learning algorithm(s). Examiner thus 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 (MPEP 2106.05(f)) or recite insignificant data gathering activities (MPEP 2106.05(g)).
The combination of additional elements – receiving, transmitting, processing, identifying, updating, monitoring, retraining – 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 – receiving user pre-qualification request and preferences associated with secured and unsecured payment instruments; receiving a preliminary credit evaluation corresponding to the user, wherein the preliminary credit evaluation is received using the user information; processing the user information, the set of preferences, and the preliminary credit evaluation through an offer generation machine learning algorithm to identify one or more recommended payment instruments, wherein the one or more recommended payment instruments are identified based on a cluster of users identified by the offer generation machine learning algorithm according to a set of similarity vectors corresponding to features of preliminary credit evaluations, and wherein the offer generation machine learning algorithm is trained using an offer dataset of historical data including previous pre-qualification determinations and corresponding feedback; updating an interface implemented on a user device associated with the user to display one or more recommended offers corresponding to the one or recommended payment instruments; receiving an application for a payment instrument associated with an offer selected from the one or more recommended offers, wherein the application is received through an interface; processing the application through an approval machine learning algorithm to determine that the user is approved for the payment instrument, wherein the approval machine learning algorithm is trained using an approval dataset of historical applications for different payment instruments and corresponding application determinations; updating the offer dataset and the approval dataset according to real-time credit performance corresponding to the user and with other users associated with other issued secured and unsecured payment instruments; retraining the offer generation machine learning algorithm and the approval machine learning algorithm using the updated offer dataset and the updated approval dataset; and processing new user information, new preferences, and new preliminary credit evaluations associated with different users through the retrained offer generations machine learning algorithm to identify new recommended payment instruments for the different users – 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). See also Recentive Analytics v Fox (Fed. Cir. 2025) (“Today, we hold only that patents that do no more than claim the application of generic machine learning to new data environments, without disclosing improvements to the machine learning models to be applied, are patent ineligible under § 101.”).
Hence under Prong 2, the additional elements, individually or in combination, do not integrate the judicial exception(s) into a practical application.
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, which is insufficient to provide an inventive concept.
When considered individually or as an ordered combination, the additional elements fail to transform the abstract idea of – receiving user pre-qualification request and preferences associated with secured and unsecured payment instruments; receiving a preliminary credit evaluation corresponding to the user, wherein the preliminary credit evaluation is received using the user information; processing the user information, the set of preferences, and the preliminary credit evaluation through an offer generation machine learning algorithm to identify one or more recommended payment instruments, wherein the one or more recommended payment instruments are identified based on a cluster of users identified by the offer generation machine learning algorithm according to a set of similarity vectors corresponding to features of preliminary credit evaluations, and wherein the offer generation machine learning algorithm is trained using an offer dataset of historical data including previous pre-qualification determinations and corresponding feedback; updating an interface implemented on a user device associated with the user to display one or more recommended offers corresponding to the one or recommended payment instruments; receiving an application for a payment instrument associated with an offer selected from the one or more recommended offers, wherein the application is received through an interface; processing the application through an approval machine learning algorithm to determine that the user is approved for the payment instrument, wherein the approval machine learning algorithm is trained using an approval dataset of historical applications for different payment instruments and corresponding application determinations; updating the offer dataset and the approval dataset according to real-time credit performance corresponding to the user and with other users associated with other issued secured and unsecured payment instruments; retraining the offer generation machine learning algorithm and the approval machine learning algorithm using the updated offer dataset and the updated approval dataset; and processing new user information, new preferences, and new preliminary credit evaluations associated with different users through the retrained offer generations machine learning algorithm to identify new recommended payment instruments for the different users – 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.
Response to Arguments
101
Applicant's arguments filed 2/27/2026 have been fully considered but they are not persuasive.
The pending claims are directed to a combination of abstract ideas. The combination of limitations in the pending claims does not bring about (i) an improvement to the functionality of a computer or other technology or technical field; (ii) a “particular machine” to apply or use the judicial exception; (iii) a particular transformation of an article to a different thing or state; or (iv) any other meaningful limitation. See MPEP 2106.05(a)-(c), (e)-(h). Hence, the additional elements fail to integrate the recited combination of abstract idea(s) into a practical application or provide significantly more. See MPEP 2106.05(f).
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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/ARUNAVA CHAKRAVARTI/Primary Examiner, Art Unit 3692
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