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 . This office action is in response to Applicant’s RCE filed August 27, 2026 in which claims 1, 9, 18 and 20 are amended. Claims 2 and 10 are cancelled. Thus, claims 1, 3-9, and 11-20 are pending in the application.
Continued Examination Under 37 CFR 1.114
2. 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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 08/27/2026 has been entered.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
3. 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, 3-9, and 11-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
The Examiner has identified independent system Claim 9 as the claim that represents the claimed invention for analysis and is similar to independent Claim 1.
The claims 1, 3-8 and 17-18 are directed to a method and claims 9, 11-16 and 19-20 are directed to a system which are one of the statutory categories of invention (Step 1: YES).
The claim 9 recites : a memory storing instructions and a predictive machine-learning model trained to identify patterns within a plurality of item level features for a client account and generate a prediction that a transaction is fraudulent for the client account based on a comparison of the identified patterns from the client account with current information from the client account; and a processor operatively connected to the memory and configured to execute the instructions to perform operations including: capturing, by the processor, a plurality of historical transaction data of the client account from a batched list of transactions of the client account associated with a specific time frame; filtering, by the processor, the batched list of transactions using one or more rules-based detection algorithms to generate a filtered batched list of transactions in which one or more transactions are flagged as suspected to be fraudulent based on rule-based logic, the rule-based logic including one or more predetermined rules related to at least one of a transaction amount, a transaction type, a transaction location, or a transaction time; extracting, by the processor, the plurality of item level features from the plurality of historical transaction data; providing, by the processor, the plurality of item level features of the filtered batched list of transactions to the predictive machine-learning model; transmitting the prediction that the transaction is fraudulent to a user interface by the processor; and executing, by the processor, automatically on the client account, transaction decline actions based on the prediction that the transaction is fraudulent, the transaction decline actions including declining the fraudulent transaction. These limitations (with the exception of italicized portions), are a process that covers Certain methods of organizing human activity such as fundamental economic principles or practices (including insurance, mitigating risk, and hedging). Fraud detection using rules-based modeling is a way of mitigating a risk and mitigating a risk is a Fundamental Economic Practice. The claim also recites additional elements (as shown above in italics) which do not necessarily restrict the claim from reciting an abstract idea. That is, other than, the recited additional elements (as shown above in italics), nothing in the claim precludes the steps from being performed as a method of organizing human activity. If the claim limitations, under the broadest reasonable interpretation, covers methods of organizing human activity, but for the recitation of generic computer components, then it falls within the “Certain methods of organizing human activity” grouping of abstract ideas. Accordingly, the claim 9 recites an abstract idea (Step 2A: Prong 1: YES).
This judicial exception is not integrated into a practical application. The additional elements of “a memory storing instructions”, “a processor operatively connected to the memory”, “by the processor” and a user interface result in no more than simply applying the abstract idea using generic computer elements. The limitation, “A predictive machine-learning model trained to identify patterns” amounts to generic computer implementation. The specification describes the additional elements of “a memory storing instructions”, “a processor operatively connected to the memory” and a user interface to be generic computer elements (see Fig. 5, [0040]). Hence, the additional elements in the claim are generic components suitably programmed to perform their respective functions. The additional elements are recited at a high level of generality and under their broadest reasonable interpretation comprises a generic computer arrangement. The presence of a generic computer arrangement is nothing more than mere instructions to implement the abstract idea on a computer (MPEP 2106.05(f)). Accordingly, these additional elements, when considered separately and as an ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Hence, the claims as a whole are not integrated into a practical application. Therefore, the claim 9 is directed to an abstract idea (Step 2A - Prong 2: NO).
The claim 9 does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements are recited at a high level of generality in that it results in no more than simply applying the abstract idea using generic computer elements. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements amount to no more than mere instructions to apply the exception using a generic computer component (MPEP 2106.05(f)). The additional elements, when considered separately and as an ordered combination, do not add significantly more (also known as an “inventive concept”) to the exception. Automatically executing a transaction decline action is simply the automated implementation of the business logic result, which is not considered as "inventive." The additional elements of the instant underlying process, when taken in combination, together do not amount to significantly more than the sum of the functions of the elements when each is taken alone. Thus, claim 9 is not patent eligible (Step 2B: NO).
Similar analysis can be extended to other independent claim 1 and hence the claim 1 is rejected on similar grounds as claim 9.
The dependent claims have been given the full two-part analysis including analyzing the additional limitations both individually and in combination. Dependent claims 3-8 and 11-20 are held to be patent ineligible under 35 U.S.C. 101 because the additional recited limitations narrow the abstract idea further and thus correspond to Certain Methods of Organizing Human Activity and hence are abstract for the reasons presented above. Dependent claims 3, 6, 8, 11, 14 and 16 recite new additional elements that are not present in independent claims 1 or 9 and require further analysis under Prong Two of Step 2A and Step 2B.
Claims 3 and 11 recite the additional element of an artificial intelligence model. An artificial intelligence model, recited in the claims, is recited at a high level of generality and amounts to generic computer implementation. Hence, it does not integrate the abstract idea into a practical application or provide significantly more than the abstract idea when considered individually and as an ordered combination.
Claims 6 and 14 recite the additional element of a generative machine-learning model trained to identify patterns. A generative machine-learning model trained to identify patterns, recited in the claims, is recited at a high level of generality and amounts to generic computer implementation. Hence, it does not integrate the abstract idea into a practical application or provide significantly more than the abstract idea when considered individually and as an ordered combination.
Claims 8 and 16 recite the additional element of a natural language machine-learning model. A natural language machine-learning model, recited in the claims, is recited at a high level of generality and amounts to generic computer implementation. Hence, it does not integrate the abstract idea into a practical application or provide significantly more than the abstract idea when considered individually and as an ordered combination.
Viewing the claim limitations as an ordered combination does not add anything further than looking at the claim limitations individually. When viewed either individually, or as a combination, the additional limitations do not amount to a claim as a whole that is significantly more than the abstract idea. Accordingly, claim(s) 1, 3-9, and 11-20 are ineligible.
Prior art
4. The prior art rejection was withdrawn in the Final Rejection dated May 28, 2026 based on the claim amendments. An updated search was conducted but does not result in a prior art rejection at this time.
Response to Arguments
5. Applicant's arguments filed July 27, 2026 have been fully considered but they are not persuasive due to the following reasons:
6. With respect to the rejection of all claims under 35 U.S.C. 101 (pages 9-12), Applicant argues that, “independent claim 1 demonstrates integration of any judicial exception into a practical application.”
The Examiner respectfully disagrees. The Examiner would like to point out that according to 2019 Patent Eligibility Guidelines (2019 PEG), 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 or using a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition - see Vanda Memo
• 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) and Vanda Memo
In the instant case, the judicial exception is not integrated into a practical application, because none of the above criteria is met. The amendments to the claims only further define the data being used however a specific abstract idea is still an abstract idea. The amended limitations of the claims do not result in computer functionality improvement or technical/technology improvement when the underlying abstract idea is implemented using technology. The trained predictive machine-learning model is simply used as a tool to determine the fraud detection. All the features in the Applicant’s claims can at best be considered an improvement in the abstract idea. The advantages over conventional systems are directed towards improving the abstract idea. An improvement in abstract idea is still abstract (SAP America v. Investpic *2-3 (“We may assume that the techniques claimed are “groundbreaking, innovative, or even brilliant,” but that is not enough for eligibility. Association for Molecular Pathology v. Myriad Genetics, Inc., 569 U.S. 576, 591 (2013); accord buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1352 (Fed. Cir. 2014). The specification describes the additional elements of “a memory storing instructions”, “a processor operatively connected to the memory” and a user interface to be generic computer elements (see Fig. 5, [0040]). The limitation, “A predictive machine-learning model trained to identify patterns” amounts to generic computer implementation. Hence, the additional elements in the claim are generic components suitably programmed to perform their respective functions. The additional elements are recited at a high level of generality and under their broadest reasonable interpretation comprises a generic computer arrangement. The presence of a generic computer arrangement is nothing more than mere instructions to implement the abstract idea on a computer (MPEP 2106.05(f)). Accordingly, these additional elements, when considered separately and as an ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The additional elements of the instant underlying process, when taken in combination, together do not amount to substantially more than the sum of the functions of the elements when each is taken alone. Hence, the claims as a whole are not integrated into a practical application.
7. Applicant further states that (pages 11-12), the currently amended claims are analogous to Example 47.
The Examiner does not see the parallel between the claims of the instant case and those of Claim 3 of Example 47. Claim 3 is eligible because the claim as a whole integrates the judicial exception into a practical application by improving network security. Claim 3 of Example 47 provides for improved network security using the information from the detection to enhance security by taking proactive measures to remediate the danger by detecting the source address associated with the potentially malicious packets. Thus, the claim as a whole integrates the judicial exception into a practical application such that the claim is not directed to the judicial exception. As discussed above and in the rejection, the Applicant’s claims deal with detecting fraud using rules-based modeling and are not directed to any improvements to another technology, technical field, or improvements to the functioning of the computer itself. Automatically executing a transaction decline action is simply the automated implementation of the business logic result and does not reflect a technical improvement. Looking at the limitations of Applicant’s claimed invention as an ordered combination adds nothing that is not already present when looking at the elements taken individually. Thus, claim 3 of Example 47 is not applicable.
For these reasons and those discussed in the rejection, the rejections under 35 USC § 101 are maintained.
Examiner Request
8. The Applicant is request to indicate where in the specification there is support for amendments to claims should Applicant amend. The purpose of this is to reduce potential 35 U.S.C. §112(a) or §112 1st paragraph issues that can arise when claims are amended without support in the specification. The Examiner thanks the Applicant in advance.
Conclusion
9. Any inquiry concerning this communication or earlier communications from the examiner should be directed to BHAVIN SHAH whose telephone number is (571)272-2981. The examiner can normally be reached on M-F 9AM-6PM.
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/BHAVIN D SHAH/Examiner, Art Unit 3694
September 04, 2026
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