DETAILED ACTION
Notice of Pre-AIA or AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
2. The Amendment filed on January 06, 2026 has been entered. Claims 1, 14, and 18 have been amended. Claim 11 was previously cancelled. Claims 2, 15, 16, and 19 are now cancelled. No claims have been added. Thus, claims 1, 3-10, 12-14, 17-18, and 20 are pending and rejected for the reasons set forth below.
Claim Rejections - 35 USC § 101
3. 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.
4. Claims 1, 3-10, 12-14, 17-18, and 20 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.
In sum, claims 1, 3-10, 12-14, 17-18, and 20 are rejected under 35 U.S.C. §101 because the claimed invention is directed to a judicial exception to patentability (i.e., a law of nature, a natural phenomenon, or an abstract idea) and do not include an inventive concept that is something “significantly more” than the judicial exception under the January 2019 patentable subject matter eligibility guidance (2019 PEG) analysis which follows.
Under the 2019 PEG step 1 analysis, it must first be determined whether the claims are directed to one of the four statutory categories of invention (i.e., process, machine, manufacture, or composition of matter). Applying step 1 of the analysis for patentable subject matter to the claims, it is determined that the claims are directed to the statutory category of a process, (claims 1, 3-10, and 12-13), a machine (claims 14 and 17), and a manufacture (claims 18 and 20), where the machine and manufacture are substantially directed to the subject matter of the process. (See, e.g., MPEP §2106.03). Under the 2019 PEG step 2A, Prong 1 analysis, it must be determined whether the claims recite an abstract idea that falls within one or more designated categories of patent ineligible subject matter (i.e., organizing human activity, mathematical concepts, and mental processes) that amount to a judicial exception to patentability. Here, the claims recite the abstract idea of gathering transaction data to determine fraudulent activity by:
accessing a transaction graph associated with a particular time duration from a database, the transaction graph comprising a plurality of nodes and a plurality of edges, the plurality of nodes indicating a plurality of transactions and timestep information, and further wherein and the plurality of edges indicate different entities involved in the plurality of transactions;
determining a set of local features and a set of aggregate features associated with each node of the transaction graph based, at least in part, on labeled data associated with the each node; and
training,...,in an adversarial manner by:
generating a set of intermediate node representations associated with each of the plurality of nodes based, at least in part, on the set of local features and the set of aggregate features;
generating via,…, a fraud classification loss and a timestep classification loss based, at least in part, on the set of intermediate node representations;
incorrectly classifying, via a timestep,…, timesteps of the digital asset transactions based on the set of intermediate node representations, wherein the timesteps are a measure of transaction time stamps associated with the digital asset transactions;
generating,…, a timestep classification loss for the timestep model based, at least in part, on the incorrect classification of the timesteps by the timestep model;
generating a reverse gradient polarity of the timestep classification loss;
updating weights of the timestep model by back-propagating the reverse gradient polarity so that the timestep model increases misclassifications of the timesteps;
determining an adversarial loss value based, at least in part, on the fraud classification loss and the reverse gradient polarity of the timestep classification loss that optimizes the classification of the fraud labels correctly and the classification of the timesteps incorrectly; and
forcing the machine learning,…, to learn the weights of the timestep model that make the timestep model increase the misclassification,…, by back-propagating the adversarial loss value to the machine learning,…, to generate an optimized machine learning….
Here, the recited abstract idea falls within one or more of the three enumerated 2019 PEG categories of patent ineligible subject matter, to wit: the category of certain methods of organizing human activity, which includes fundamental economic practices or principles and commercial or legal interactions (e.g., gathering transaction data to determine fraudulent activity).
Under the 2019 PEG step 2A, Prong 2 analysis, the identified abstract idea to which the claim is directed does not include limitations that integrate the abstract idea into a practical application, since the recited features of the abstract idea are being applied on a computer or computing device or via software programming that is simply being used as a tool (“apply it”) to implement the abstract idea. (See, e.g., MPEP §2106.05(f)). Therefore, the claim is directed to an abstract idea.
Under the 2019 PEG step 2B analysis, the additional elements are evaluated to determine whether they amount to something “significantly more” than the recited abstract idea. (i.e., an innovative concept). Here, the additional elements, such as: a “model,” and “system,” do not amount to an innovative concept since, as stated above in the step 2A, Prong 2 analysis, the claims are simply using the additional elements as a tool to carry out the abstract idea (i.e., “apply it”) on a computer or computing device and/or via software programming. (See, e.g., MPEP §2106.05(f)). The additional elements are specified at a high level of generality to simply implement the abstract idea and are not themselves being technologically improved. (See, e.g., MPEP §2106.05 I.A.); (see also, paragraph [0006] of the specification).
Dependent claims 2–13, 15–17, and 19–20 have all been considered and do not integrate the abstract idea into a practical application. Dependent claims 2, 15, and 19 recite nearly identical limitations that further define the abstract idea noted in claim 1 in that they describe the process of determining the adversarial loss value. Dependent claim 3 recites limitations that further define the abstract idea noted in claim 1 in that it describes what the labeled data comprises (“a set of information…”). Dependent claims 4, 16, and 19 recite nearly identical limitations that further define the abstract idea noted in claim 1 in that they describe generating an optimized machine learning model based on a set of optimized parameters. Dependent claims 5, 17, and 20 recite nearly identical limitations that further define the abstract idea noted in claim 1 in that they describe generating a set of updated intermediate node representations and then classifying a transaction as one of a licit or an illicit transaction based on these updated intermediate node representations. Dependent claim 6 recites limitations that further define the abstract idea noted in claim 1 in that it describes that the plurality of transactions is digital asset transactions. Dependent claim 7 recites limitations that further define the abstract idea noted in claim 1 in that it describes that the different entities includes at least one of a customer and a merchant. Dependent claim 8 recites limitations that further define the abstract idea noted in claim 1 in that it describes what the set of local features comprises. Dependent claim 9 recites limitations that further define the abstract idea noted in claim 1 in that it describes how the set of aggregate features is determined. Dependent claim 10 recites limitations that further define the abstract idea noted in claim 1 in that it describes what the set of aggregate features comprises. Dependent claim 11 recites limitations that further define the abstract idea noted in claim 1 in that it describes that the machine learning model is a graph neural network model. Dependent claim 12 recites limitations that further define the abstract idea noted in claim 1 in that it describes what the fraud and timestep models are. Dependent claim 13 recites limitations that further define the abstract idea noted in claim 1 in that it describes that the server system is a payment server in a payment network.
The elements of the instant process steps when taken in combination do not offer substantially more than the sum of the functions of the elements when each is taken alone. The claims as a whole, do not amount to significantly more than the abstract idea itself because the claims do not effect an improvement to another technology or technical field (e.g., the field of computer coding technology is not being improved); the claims do not amount to an improvement to the functioning of an electronic device itself which implements the abstract idea (e.g., the general purpose computer and/or the computer system which implements the process are not made more efficient or technologically improved); the claims do not perform a transformation or reduction of a particular article to a different state or thing (i.e., the claims do not use the abstract idea in the claimed process to bring about a physical change. See, e.g., Diamond v. Diehr, 450 U.S. 175 (1981), where a physical change, and thus patentability, was imparted by the claimed process; contrast, Parker v. Flook, 437 U.S. 584 (1978), where a physical change, and thus patentability, was not imparted by the claimed process); and the claims do not move beyond a general link of the use of the abstract idea to a particular technological environment (e.g., simply claiming the use of a computer and/or computer system to implement the abstract idea).
Prior Art Not Relied Upon
5. The prior art made of record and not relied upon is considered pertinent to Applicant’s disclosure. (See MPEP §707.05). The Examiner considers the following reference pertinent for disclosing various features relevant to the invention, but not all the features of the invention, for at least the following reasons:
Ye et al. (U.S. Pat. No. 12,093,245) teaches a method for improving computing efficiency of a computing device for temporal directed cycle detection in a transaction graph based on a plurality of transactions. Although the invention in Ye describes use of cycle detection in transaction graphs to reveal unauthorized transactions, it fails to disclose the following limitations of the current invention:
generating, by the server system via a fraud model and a timestep model, a fraud classification loss and a timestep classification loss based, at least in part, on the set of intermediate node representations;
determining, by the server system, an adversarial loss value based, at least in part, on the fraud classification loss and the timestep classification loss; and
determining, by the server system, a set of optimized parameters for the machine learning model based, at least in part, on the adversarial loss value. However, Ye does not teach generating both a fraud model and a timestep model based on a set of intermediate node representations and then determining an adversarial loss value based on both the fraud classification loss and the timestep classification loss. This is then used to determine a set of optimized parameters for improving the adversarial loss value.
Response to Arguments
6. Applicant’s arguments filed on January 06, 2026 have been fully considered.
Applicant’s arguments concerning the 35 U.S.C. §101 rejection of the claims, including supposed deficiencies in the rejection, are not persuasive.
Applicant argues that “…Applicant submits that that the claims are at least integrated into a practical application.” (See Applicant’s Arguments, p. 10). However, the identified abstract idea to which the claim is directed does not include limitations that integrate the abstract idea into a practical application, since the recited features of the abstract idea are being applied on a computer or computing device or via software programming that is simply being used as a tool (“apply it”) to implement the abstract idea. (See, e.g., MPEP §2106.05(f)). Merely using a generic machine learning model and training it does not integrate the abstract idea into a practical application. All of the limitations of this invention are geared towards the backend of the system being used to carry out the fraud analysis. Nothing interactive is being done by this invention. There is no specialized hardware or software that is being used in this invention. Using various models to classify fraud labels correctly isn’t a technological improvement, no matter the number of models being utilized to do so. Applicant also states that “Thus, claim I improves existing designs with a more robust and fast adapting model. Indeed, the above combination of features imparts a new functionality (e.g., an enhanced GNN that is temporally unbiased and more accurate) into a computing system. As such, the claims are integrated into a practical application.” (See Applicant’s Arguments, p. 15). However, it is unclear how the models here actually are being improved upon.
Therefore, the rejection under 35 U.S.C. §101 is maintained.
Conclusion
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 Amit Patel whose telephone number is (313) 446-4902. The Examiner can normally be reached Mon - Thu 8 AM - 6 PM EST. If attempts to reach the Examiner by telephone are unsuccessful, the Examiner’s supervisor, Matthew Gart, can be reached at (571) 272-3955. The Examiner’s fax number is (571) 273-6087. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/Amit Patel/
Examiner
Art Unit 3696
/EDWARD CHANG/Primary Examiner, Art Unit 3696