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 response filed January 30, 2026 in which claims 1 and 11 are amended. Claims 6, 7, 16 and 17 have been canceled. Thus, claims 1-5, 8-15 and 18-20 are pending in the application.
Claim Rejections - 35 USC § 101
2. 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 1-5, 8-15 and 18-20 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 1 as the claim that represents the claimed invention for analysis and is similar to independent Claim 11.
The claims 1-5 and 8-10 are directed to a method and claims 11-15 and 18-20 are directed to a system which are one of the statutory categories of invention (Step 1: YES).
The claim 1 recites : receiving an indication of a merchant under consideration; identifying one or more web pages likely to have information associated with travel exposure for the merchant under consideration based on the indication; employing a large language model (LLM) stage to conduct data scraping on the identified one or more web pages to attempt to obtain scraped travel exposure data; responsive to obtaining the scraped travel exposure data, employing a machine learning module to determine a travel risk exposure estimate based on the scraped travel exposure data; and responsive to not obtaining the scraped travel exposure data, determining the risk exposure estimate based on a predefined travel risk estimate associated with an industry classification of the merchant under consideration, wherein the LLM stage includes multiple LLMs and different ones of the multiple LLMs are associated with respective different forms of information conveyance run in parallel on the identified one or more web pages.
These limitations (with the exception of italicized portions), under their broadest reasonable interpretation, when considered collectively as an ordered combination, is a process that covers Certain methods of organizing human activity such as Fundamental economic principles or practices. Determining the risk exposure estimate based on a predefined travel risk estimate associated with an industry classification of the merchant under consideration is a way of mitigating risk and mitigating a risk is a Fundamental Economic Practice. The claim also recites a machine learning module and web pages which do not necessarily restrict the claim from reciting an abstract idea. That is, other than, a machine learning module a large language model (LLM) and web pages, 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 1 recites an abstract idea (Step 2A: Prong 1: YES).
This judicial exception is not integrated into a practical application. The additional elements of a machine learning module, a large language model (LLM) and web pages result in no more than simply applying the abstract idea using generic computer elements. The specification describes the additional elements of a machine learning module, a large language model (LLM) and web pages to be generic computer elements (see Fig. 2, Fig. 3, Fig. 6). Hence, the additional elements in the claim are generic components suitably programmed to perform their respective functions. The additional element of a machine learning module, a large language model (LLM) and web pages 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 1 is directed to an abstract idea (Step 2A - Prong 2: NO).
The claim 1 does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional element of a machine learning module, a large language model (LLM) and web pages 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, does not add significantly more (also known as an “inventive concept”) to the exception. The additional elements of the instant underlying process, when taken in combination, together do not offer significantly more than the sum of the functions of the elements when each is taken alone. Thus, claim 1 is not patent eligible (Step 2B: NO).
Similar arguments can he extended to other independent claim 11 and hence the claim 11 is rejected on similar grounds as claim 1.
Dependent claims 2-5, 8-10, 12-15 and 18-20 are held to be patent ineligible under 35 U.S.C. 101 because the additional recited limitations only narrow the abstract idea further and thus correspond to Certain Methods of Organizing Human Activity and hence are abstract for the reasons presented above. Claims 2-5, 8-10, 12-15 and 18-20 do not recite any new additional elements that are not present in independent claims 1 and 11.
Viewing the claim limitations as a 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) 1-5, 8-15 and 18-20 are ineligible.
No Prior Art Rejections
3. Based on the prior art search results, the prior art of record fails to anticipate or render obvious the claimed subject matter of claims 1-5, 8-15 and 18-20. While some individual features of claims 1-5, 8-15 and 18-20 may be shown in the prior art of record, no known reference, alone or in combination, would provide the invention of claims 1-5, 8-15 and 18-20. The prior art most closely resembling the applicant’s claimed invention are :
Chebrole (US 2019/0026826 A1) – This invention relates generally to determining a credit risk score for an online merchant. The system includes a transaction database including transaction data relating to payment card transactions performed by customers at multiple merchants, a financial performance database including financial data relating to multiple merchants selling merchandise through an e-commerce marketplace, and a risk assessment component. The risk assessment component is configured for: i) receiving, from a requester, an electronic request for a credit risk score for an online merchant, ii) extracting transaction data for the merchant and/or for similar merchants from the transaction database, iii) extracting financial data for the merchant and/or for similar merchants from the financial performance database, iv) combining the extracted transaction data and financial data in a statistical model to determine the credit risk score for the merchant, and v) transmitting the credit risk score to the requester.
Chang (US 2022/0005041 A1) - This invention generally relates to determining risks associated with an electronic payment service, and more specifically, to determining a risk of fraud or a financial risk posed by a merchant enrolled in the electronic payment service. The risk assessment system determines a pseudo-SHAP score for each group of features by summing the SHAP scores determined for the features in the respective group of features, and then determines a financial risk or a risk of fraud posed by the merchant based on the determined risk score and the pseudo-SHAP scores.
Lewis (US 2008/0140576 A1) - This invention relates to an electronic system and method for evaluating fraud risk in an electronic commerce transaction between consumer and a merchant over a network is disclosed. The merchant requests service from the system over the network using a secure, open messaging protocol. An e-commerce transaction or electronic purchase order is received from the merchant, the level of risk associated with each order is measured, and a risk score is returned to the merchant. In one embodiment, data validation, highly predictive artificial intelligence pattern matching, network data aggregation and negative file checks are used to examine numerous factors to calculate fraud risk. The fraud screening system performs analysis that utilizes data elements submitted with the order, and includes data integrity checks and correlation analyses based on the characteristics of the transaction. Other analysis includes a comparative comparison of the current transaction against past known fraudulent transactions, and a search of a transaction history database to identify abnormal velocity patterns, name and address changes, and known defrauders. A risk score is generated and compared to the merchant's specified risk threshold. The result is returned to the merchant for order disposition. In one alternative, scoring algorithms are regularly refined through the use of a closed-loop risk modeling process that enables the service provided by the system to be fine-tuned to adapt to new or changing fraud patterns.
Response to Arguments
4. Applicant's arguments filed dated 01/30/2026 have been fully considered but they are not persuasive due to the following reasons:
5. With respect to Step 2A, Prong 2, Applicant argues that (pages 7-9), “the claimed invention integrates any alleged 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 limitations of the claims do not result in computer functionality improvement or technical/technology improvement when the underlying abstract idea is implemented using technology. 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. The specification describes the additional elements of a machine learning module, a large language model (LLM) and web pages to be generic computer elements (see Fig. 2, Fig. 3, Fig. 6). Hence, the additional elements in the claims are all generic components suitably programmed to perform their respective functions. Large language model is used as a tool to implement the abstract idea. The additional elements of a machine learning module, a large language model (LLM) and web pages 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.
6. Applicant further states that (page 9), the present case is analogous to Desjardins.
The Examiner does not see the parallel between the claims of the instant case and the claims in Desjardins. The invention in Desjardins improved the operation of the machine learning model. Hence, when considered as a whole, independent claim 1 integrated an abstract idea into a practical application. In Desjardins, “when evaluating the claim as a whole, we discern at least the following limitation of independent claim 1 that reflects the improvement: "adjust the first values of the plurality of parameters to optimize performance of the machine learning model on the second machine learning task while protecting performance of the machine learning model on the first machine learning task." We are persuaded that constitutes an improvement to how the machine learning model itself operates, and not, for example, the identified mathematical calculation.” On the other hand, the focus of the invention in the instant claims is not on improving machine learning model, but simply using LLM as a tool to implement the abstract idea. Hence, Desjardins is not applicable.
7. With respect to the rejection of all claims under 35 U.S.C. 101 with regards to Step 2B, Applicant states that (pages 9-10), “the claims still provide an inventive concept.”
One of the guidelines issued by the Office to determine if the claims recite additional elements which are not well understood, routine or conventional and hence, amount to significantly more than an abstract idea, is the USPTO guidelines of April 19, 2018 incorporating the Berkheimer memo (Berkheimer memo, hereinafter).
According to the Berkheimer memo,
In a step 2B analysis, an additional element (or combination of elements) is not well understood, routine or conventional unless the examiner finds, and expressly supports a rejection in writing with, one or more of the following:
1. A citation to an express statement in the specification or to a statement made by an applicant during prosecution that demonstrates the well-understood, routine, conventional nature of the additional element(s).
2. A citation to one or more of the court decisions discussed in MPEP § 2106.05(d)(II) as noting the well-understood, routine, conventional nature of the additional element(s).
3. A citation to a publication that demonstrates the well-understood, routine, conventional nature of the additional element(s).
4. A statement that the examiner is taking official notice of the well-understood, routine, conventional nature of the additional elements). This option should
be used only when the examiner is certain, based upon his or her personal knowledge, that the additional elements) represents well-understood, routine, conventional activity engaged in by those in the relevant art, in that the additional elements are widely prevalent or in common use in the relevant field, comparable to the types of activity or elements that are so well-known that they do not need to be described in detail in a patent application to satisfy 35 U.S.C. § 112(a).
The claim simply applies the abstract idea using generic computer elements as a tool (see MPEP 2106.05(f)). The additional elements in the claim are a payment processing platform, a payment application, the third-party applications, a trained machine learning model, a third-party platform, a merchant device and an interactive user interface. As per the rejection above, the specification describes the additional elements of a machine learning module, a large language model (LLM) and web pages to be generic computer elements (see Fig. 2, Fig. 3, Fig. 6). Hence, the additional elements in the claims are all generic components suitably programmed to perform their respective functions. There is no indication in Applicants’ claims that any specialized hardware or other inventive computer components are required. The fact that a general purpose computing system, suitably programmed, may be used to perform the claimed method and the fact that the claims at issue do not require any nonconventional computer, network, or other components, or even a “non-conventional and non-generic arrangement of known, conventional pieces” but merely call for performance of the claimed functions “on a set of generic computer components, satisfies the Berkheimer memo requirement that the additional elements are conventional elements (as outlined in criterion 1 of the Berkheimer memo). The additional elements of the instant underlying process, when taken in combination, together do not offer substantially more than the sum of the functions of the elements when each is taken alone. Hence, the claims do not recite significantly more than an abstract idea.
For these reasons and those discussed in the rejection, the rejections under 35 U.S.C. 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. 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 extension fee 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 date of this final action.
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.
If attempts to reach the examiner by telephone are unsuccessful, the examiner's supervisor, Bennett Sigmond can be reached on 303-297-4411. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/B.D.S./Examiner, Art Unit 3694
March 20, 2026
/BENNETT M SIGMOND/Supervisory Patent Examiner, Art Unit 3694