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 May 21, 2026 in which claims 1, 10, 13, and 22 are amended. Claims 9, 11, 21, and 23 are cancelled. Thus, claims 1-8, 10, 12-20, 22 and 24 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 1-8,10, 12-20, 22 and 24 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 Claim 1 as the claim that represents the claimed invention for analysis and is similar to independent Claim 13.
The claims 1-8, 10, and 12 are directed to a system and claims 13-20, 22 and 24 are directed to a method which are one of the statutory categories of invention (Step 1: YES).
The claim 1 recites : one or more databases; one or more computing devices adapted to: query a generative-artificial-intelligence-based (“GenAI-based”) application, via real-time interaction with the one or more alert investigation agents, for one or more insights concerning the received financial crime alert; wherein the GenAI-based application is based on a large language model ("LLM") adapted to execute the real-time interaction with the one or more alert investigation agents by: understanding one or more inputs from the one or more alert investigation agents; creating a plan of action based on the one or more inputs, including determining which of the one or more databases to query; executing the plan of action, including parsing one or more results from the queried one or more databases; and responding to the one or more alert investigation agents; generate the one or more insights concerning the received financial crime alert by accessing, using the queried GenAI-based application, the one or more databases for: (i) information associated with the MLM’s development and creation of the financial crime alert by the MLM; (ii) information regarding disposition of one or more historical financial crime alerts comparable to the received financial crime alert; or (iii) both (i) and (ii); and one or more output devices each accessible by the one or more alert investigation agents, and adapted to visualize, audibilize, or both, the generated one or more insights concerning the received financial crime alert. 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. Evaluating a financial crime alert is a way of mitigating the risk and mitigating the risk is a Fundamental Economic Practice. The claim also recites a databases, computing devices, a generative-artificial-intelligence-based (“GenAI-based”) application, a large language model ("LLM"), a machine learning model (MLM), and output devices which do not necessarily restrict the claim from reciting an abstract idea. That is, other than, a databases, computing devices, a generative-artificial-intelligence-based (“GenAI-based”) application, a large language model ("LLM"), a machine learning model (MLM), and output devices, 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 databases, computing devices, a generative-artificial-intelligence-based (“GenAI-based”) application, a large language model ("LLM"), a machine learning model (MLM), and output devices, result in no more than simply applying the abstract idea using generic computer elements. The specification describes the additional elements of a databases, computing devices, a generative-artificial-intelligence-based (“GenAI-based”) application, a large language model ("LLM"), a machine learning model (MLM), and output devices, to be generic computer elements (see Fig. 1, Fig. 2A, [0078]). Hence, the additional elements in the claim are generic components suitably programmed to perform their respective functions. The additional elements (as described above) 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 elements of a databases, computing devices, a generative-artificial-intelligence-based (“GenAI-based”) application, a large language model ("LLM"), a machine learning model (MLM), and output devices 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 amount to 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 13 and hence the claim 13 is rejected on similar grounds as claim 1.
Dependent claims 2-8, 10, 12, 14-20, 22 and 24 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 and 14 recite new additional elements that are not present in independent claim 1.
Claims 2 and 14 recite the additional element of machine learning (“ML”) algorithms. Machine learning (“ML”) algorithms, 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 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) 1-8, 10, 12-20, 22 and 24 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 1-8, 10, 12-20, 22 and 24. While some individual features of claims 1-8, 10, 12-20, 22 and 24 may be shown in the prior art of record, no known reference, alone or in combination, would provide the invention of claims 1-8, 10, 12-20, 22 and 24. The prior art most closely resembling the applicant’s claimed invention are :
1) B’far (US 2023/0289559 A1) – This invention relates generally to generating insights for the operations of a trained neural network. The neural network is trained to identify fraudulent transactions in financial data. The data set represents data points having the same attributes as the historical data set, but having varying attribute values. The neural network is provided historical data associated with financial transactions. The neural network is trained to identify a particular financial transaction as being fraudulent or not.
2) Reddy (2019/0311367 A1) - This invention generally relates to using a data genome to identify suspicious financial transactions. In one embodiment, the method comprises receiving a data set of financial activity data of multiple participants; configuring a deep neural network and thresholds, wherein the thresholds enable detection of what is within abnormal range of financial activity, patterns, and behavior over a period of time; converting the data set to a genome containing a node for each participant among the multiple participants; computing threat vectors for each node within a graphical representation of the genome that represents behavioral patterns of participants in financial activities, including determining when a key risk indicator (KRI) value computed for a particular threshold within the data set falls outside of a dynamically determined range bounded by thresholds, wherein the threat vectors automatically identify one or more of suspicious participants and suspicious activities in a provided financial activity pattern; and determining a particular edge in the network whose behavior falls outside the dynamically determined range associated with normal activity as a suspicious.
3) Mehta (US 2024/0037559 A1) - This invention relates to providing systems and methods which improve upon these prior approaches to reduce the total overall number of fraudulent transactions which are successfully executed by fraudsters and/or which go undetected, and hence to reduce the damage caused by such fraudsters to legitimate merchants and consumers. In particular, the present invention relates to improvements in the testing and evaluation of rules and models for detection of fraudulent electronic transactions, such as improvements in the speed of such testing and evaluation.
Response to Arguments
4. Applicant's arguments filed dated 05/21/2026 have been fully considered but they are not persuasive due to the following reasons:
5. With respect to the rejection of all claims under 35 U.S.C. 101 with regards to Step 2A, Prong 1 (pages 9-11), Applicant argues that, “independent claims 1 and 13 do not recite "certain methods of organizing human activity."
Examiner respectfully disagrees and notes that as explained in the 101 analysis above, the steps of the amended claim, is a process that, under their broadest reasonable interpretation, covers Certain methods of organizing Human activity such as Fundamental economic principles or practices. Evaluating a financial crime alert is a way of mitigating the risk and mitigating the risk is a Fundamental Economic Practice. The claim also recites a databases, computing devices, a generative-artificial-intelligence-based (“GenAI-based”) application, a large language model ("LLM"), a machine learning model (MLM), and output devices which do not necessarily restrict the claim from reciting an abstract idea. That is, other than, a databases, computing devices, a generative-artificial-intelligence-based (“GenAI-based”) application, a large language model ("LLM"), a machine learning model (MLM), and output devices, 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.
6. With respect to the rejection of all claims under 35 U.S.C. 101 with regards to Step 2A, Prong 2 (pages 11-13), Applicant argues that, “the alleged abstract idea is sufficiently integrated 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 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 amendments to the claims only further define the data being used however a specific abstract idea is still an abstract idea. The GenAI-based application based on a large language model ("LLM") amounts to generic computer implementation. Applicant’s arguments are based on the application of machine learning to a particular business environment as opposed to improving the machine learning or technical improvement. 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 databases, computing devices, a generative-artificial-intelligence-based (“GenAI-based”) application, a large language model ("LLM"), a machine learning model (MLM), and output devices, to be generic computer elements (see Fig. 1, Fig. 2A, [0078]), to be generic computer elements. Hence, the additional elements in the claims are all 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)). 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. 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.
7. With respect to the rejection of all claims under 35 U.S.C. 101, Step 2B, Applicant states that (pages 13-14), “amended claims 1 and 13 amount to "significantly more" than an abstract idea.”
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 databases, computing devices, a generative-artificial-intelligence-based (“GenAI-based”) application, a large language model ("LLM"), a machine learning model (MLM), and output devices, to be generic computer elements. As per the rejection above, the specification describes the additional elements of a databases, computing devices, a generative-artificial-intelligence-based (“GenAI-based”) application, a large language model ("LLM"), a machine learning model (MLM), and output devices, to be generic computer elements (see Fig. 1, Fig. 2A, [0078]). 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 amount to 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.
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/B.D.S./Examiner, Art Unit 3694
/BENNETT M SIGMOND/ Supervisory Patent Examiner, Art Unit 3694
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