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 .
Status of Claims
This action is in reply to the Response to Office Action filed on 3/5/2026 without amended claims. Therefore the claims remain as in the original claim set dated 5/30/24, wherein:
Claims 1-26 are currently pending and have been examined.
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 1-26 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claims recite a method for fraud prevention which is considered a judicial exception because it falls under Certain Methods of Organizing Human Activity such as fundamental economic principles or practices, including mitigating risk. This judicial exception is not integrated into a practical application as discussed below and the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception as discussed below.
This rejection follows the 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed Reg 4, January 7, 2019, pp. 50-57 (“2019 PEG”)(MPEP 2106).
Analysis
Step 1 (Statutory Categories) – 2019 PEG pg. 53 (See MPEP 2106.03)
Claims 1-26 are directed to the statutory category of a process.
Step 2A, Prong 1 (Do the claims recite an abstract idea?) – 2019 PEG pg. 54 (See MPEP 2106.04(a)-(c))
For independent claim 1, the claim recites an abstract idea of: fraud prevention. The steps of independent claim 1 recite the abstract idea (in bold below) of: A computer-implemented method of real-time fraud prevention, using a fraud prevention system on a transaction, comprising: accessing real-time data from a device, by a central processing unit (CPU) of an application server of an integrated decision engine, from a device; processing a risk profile input and the real-time data by a decision tree model located in the application server to generate a decision tree model output; constructing a heuristics model by the CPU of the application server by synthesizing the decision tree model output with historical data; processing the heuristics model and decision tree model output by the decision tree model located in the application server to generate a structured narrative; providing the structured narrative from the application server to a predictive server comprising a transformer network and a predictive risk model via a network interface; generating a prediction by processing the structured narrative using the predictive risk model located in the predictive server; processing the structured narrative and the prediction by the CPU of the application server to generate a decision; and providing the decision to the device. Independent claim 1, as drafted, is a process that, under the broadest reasonable interpretation, covers Certain Methods of Organizing Human Activity, since they recite fundamental economic principles or practices including mitigating risk. If the claim limitations, under the broadest reasonable interpretation, covers methods of organizing human activity but for the recitation of additional elements including generic computer components, then it falls within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas. Other than reciting the abstract idea, the independent claims recite additional elements including generic computer components such as “a fraud prevention system, a device, a CPU of an application server or an integrated decision engine, a decision tree model, a heuristics model, a structured narrative, a predictive server comprising a transformer network and a predictive risk model, and a network interface”, and nothing in the claims precludes the steps from being performed as a method of organizing human activity. Accordingly, the independent claims recite an abstract idea.
Dependent claims 2-26 recite similar limitations as independent claim 1; and when analyzed as a whole are held to be patent ineligible under 35 U.S.C 101 because the additional recited limitations only refine the abstract idea further. Other than reciting the abstract idea, the dependent claims recite similar additional elements including generic computer components as the independent claims, such as “the decision tree model, a hysteresis model, the CPU of the application server, a memory of the application server, a source detector, the application server of the integrated decision engine, a database of the application server, a risk profiler, the heuristics model, the transformer network of the predictive server, a decision tree predictor in the CPU of the application server, a decision interpreter, the predictive risk model comprises a trained risk model, a Generational Adversarial Network (GAN) located on a simulated data server, a model training server, a CPU of the model training server, a transformer training engine located on the Graphics Processing Unit (GPU) of the model training server, the transformer training engine on the GPU of the model training server, the database of the predictive server, a memory of the simulated data server, a CPU of the simulated data server, a GPU of the simulated data server, a GAN on the GPU of the simulated data server, the GAN on the simulated data server comprises a GAN regularization engine comprises a discriminator and a generator, a data pre-processing engine, a refined GAN regularization data engine, a training model of the transformer training engine located on the GPU of the model training server, the updated training model, an optimizer, an updated training model, a vector model, the device, a POS, E-commerce, a plurality of devices”. If a claim limitation, under its broadest reasonable interpretation, covers fundamental economic principles or practices, but for the recitation of generic computer components, then it falls within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas.
Step 2A, Prong 2 (Does the claim recite additional elements that integrate the judicial exception into a practical application?) – 2019 PEG pg. 54 (See MPEP 2106.04(d)-(c))
This judicial exception is not integrated into a practical application. In particular, independent claim 1, only recite the additional elements of “a fraud prevention system, a device, a CPU of an application server or an integrated decision engine, a decision tree model, a heuristics model, a structured narrative, a predictive server comprising a transformer network and a predictive risk model, and a network interface”. A plain reading of the Figures and associated descriptions in the specification reveals that generic processors may be used to execute the claimed steps. The additional elements are recited at a high level of generality (i.e., as a generic processor performing generic computer functions) such that it amounts to no more than mere instructions to apply the exception using generic computer components (See MPEP 2106.05(f)) and limits the judicial exception to a particular environment (See MPEP 2106.05(h)). Mere instructions to apply an exception using a generic computer component and limiting the judicial exception to a particular environment doesn’t integrate the abstract idea into a practical application in Step 2A. Accordingly, these additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. Hence, independent claim 1 is directed to an abstract idea.
Dependent claims 2-26, recite similar additional elements as the independent claims including generic computer components, such as “the decision tree model, a hysteresis model, the CPU of the application server, a memory of the application server, a source detector, the application server of the integrated decision engine, a database of the application server, a risk profiler, the heuristics model, the transformer network of the predictive server, a decision tree predictor in the CPU of the application server, a decision interpreter, the predictive risk model comprises a trained risk model, a Generational Adversarial Network (GAN) located on a simulated data server, a model training server, a CPU of the model training server, a transformer training engine located on the Graphics Processing Unit (GPU) of the model training server, the transformer training engine on the GPU of the model training server, the database of the predictive server, a memory of the simulated data server, a CPU of the simulated data server, a GPU of the simulated data server, a GAN on the GPU of the simulated data server, the GAN on the simulated data server comprises a GAN regularization engine comprises a discriminator and a generator, a data pre-processing engine, a refined GAN regularization data engine, a training model of the transformer training engine located on the GPU of the model training server, the updated training model, an optimizer, an updated training model, a vector model, the device, a POS, E-commerce, a plurality of devices”. The judicial exception is not integrated into a practical application because the additional elements in the dependent claims are also recited at a high-level of generality such that it amounts to more no more than mere instructions to apply the exception using generic computer components. Therefore, the additional elements do not integrate the abstract idea into a practical application because they also do not impose any meaningful limits on practicing the abstract idea. Also, the claims do not affect an improvement to another technology or technical field; the claims do not amount to an improvement of the functioning of a computer system itself; the claims do not effect a transformation or reduction of a particular article to a different state or thing; and the claims do not move beyond a general link of the use of an abstract idea to a particular technological environment.
Step 2B (Does the claim recite additional elements that amount to significantly more than the judicial exception?) – 2019 PEG pg. 56 (See MPEP 2106.05)
Independent claim 1 does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the recited additional elements amount to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)) and limits the judicial exception to the particular environment of computers (See MPEP 2106.05(h)). The additional elements of the instant underlying process, when taken in combination, together do not offer substantially more than the sum of the function of the elements when each is taken alone. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept in Step 2B.
In addition, the dependent claims 2-26 do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of the dependent claims to perform the claimed limitations, amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)). Similar to the independent claims, mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Also, for the same reasoning as the independent claims, the additional elements of the limitations of the dependent claims, when considered individually and as an ordered combination, together do not offer significantly more than the sum of the functions of the elements when each is taken alone and the dependent claims as a whole, do not amount to significantly more than the abstract idea itself. For these reasons, the dependent claims also are not patent eligible.
Subject Matter Overcoming 35 USC §102/§103
Claims 1-26 would be allowable if rewritten to overcome the rejections under 35 U.S.C. 101 set forth in this Office Action.
The following is an examiner’s statement of reasons for subject matter of independent clams 1, 9, and 15 overcoming the prior art rejections under 35 USC §102/§103.
The closest prior art of record is US 20250148482 to Albright et al. (hereinafter referred to as Albright), US 20250117797 to Ruan et al. (hereinafter referred to as Ruan), and US 12124435 to Alves et al. (hereinafter referred to as Alves). Allowable subject matter is indicated because none of the prior art of record, alone or in combination, appears to teach or fairly suggest or render obvious the combination set forth in independent claims 1, 9, and 15. For independent claim 1, the prior art of Albright, Ruan, and Alves specifically do not disclose: “processing a risk profile input and the real-time data by a decision tree model located in the application server to generate a decision tree model output; constructing a heuristics model by the CPU of the application server by synthesizing the decision tree model output with historical data; processing the heuristics model and decision tree model output by the decision tree model located in the application server to generate a structured narrative; providing the structured narrative from the application server to a predictive server comprising a transformer network and a predictive risk model via a network interface; generating a prediction by processing the structured narrative using the predictive risk model located in the predictive server; processing the structured narrative and the prediction by the CPU of the application server to generate a decision; and providing the decision to the device”. Dependent claims 2-26 are allowable over the prior art by virtue of their dependency on an allowed claim.
Response to Arguments
Applicant’s arguments with respect to the rejections of claims 1-26 under 35 USC 101 have been fully considered by the Examiner. However, the Examiner does not find the Applicant’s arguments persuasive, and therefore the rejections of claims 1-26 under 35 USC 101 are maintained.
The Applicant argues that under Prong 1 of Step 2A that the claims do not recite an abstract idea because the claims recite a specific, multi model machine learning pipeline that converts transaction data into intermediate representations used to generate transaction decisions; and the claims are therefore not directed to risk mitigation or any other method of human organization. The Applicant further states on pages 2-5 of their Remarks, that the limitations of the independent claims under Prong 2 of Step 2A are indicative of integration into a practical application because they provide improvements to the operation of the machine learning system. Applicant states the claimed limitations address a technical problem for producing accurate decisions in real time while continuously updating the models which improve the functioning of the machine learning system for analyzing real time transactions. Applicant further argues that similar to Desjardins, the claims provide for an improvement to a machine learning model.
Examiner respectfully disagrees with Applicant’s argument that the claimed limitations do not recite risk mitigation or any of the groupings of abstract ideas such as certain methods of organizing human activity. Under Prong 1 of the 2019 PEG, the claims do fall under the abstract idea of Certain Method of Organizing Human Activity. If a claim limitation, under its broadest reasonable interpretation, covers fundamental economic principles or practices, including mitigating risk, but for the recitation of additional elements including generic computer components, then it falls within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas. Under the broadest reasonable interpretation, the claims recite fundamental economic principles or practices including mitigating risk. Analyzing acquired transaction data to detect fraud is mitigating risk.
Examiner respectfully disagrees with Applicant’s argument that the claimed limitations are indicative of integration into a practical application under Prong 2 of Step 2A of the PEG. Using a CPU to: access transaction data, process data using a decision tree model, feed the output to a heuristics model with historical data to generate a structured narrative, feed the structured narrative to a predictive risk model to generate a prediction, and process the structured narrative and prediction by the CPU to generate a decision that is sent to the device; is nothing more than executing instructions to apply the exception to a computer. This is interpreted by the Examiner as using a computer as a tool to perform an abstract idea (See MPEP 2106.05(f)). The additional elements of “a fraud prevention system, a device, a CPU of an application server or an integrated decision engine, a decision tree model, a heuristics model, a structured narrative, a predictive server comprising a transformer network and a predictive risk model, and a network interface” are recited at a high level of generality such that it amounts to no more than mere instructions to apply the exception using generic computer components (See MPEP 2106.05(f)). There is no improvement to the claimed computer elements, a machine learning model, or to any other technology or technical field. Applicant’s argument that the claimed limitations continuously update the models to improve the machine learning system is not persuasive because the independent claims do not include any limitations for updating the models. Applicant’s arguments that the claims improve the machine learning model similar to Desjardins is also not persuasive. Applicant’s claims are similar to claim 2 of Example 47 which included receiving continuous training data, using the computer to discretize the continuous training data to generate input data, training the artificial neural network using the input data, and detecting anomalies using the trained artificial neural network; which represented mere instructions to implement an abstract idea on a computer. Furthermore, the Federal Circuit in Recentive Analytics, Inc., v. Fox Corp., Appeal No. 2023-2437 (Fed. Cir. Apr. 18, 2025), held 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”. Similar to Recentive Analytics, Applicant’s limitations only claim the application of machine learning models and not an improvement to the models themselves. The claimed limitations do not meet the criteria or considerations as indicative of integration into a practical application. Therefore, the rejections of the claims pursuant to 35 USC 101 are maintained.
Conclusion
THIS ACTION IS MADE FINAL. 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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/PAUL S SCHWARZENBERG/Primary Examiner, Art Unit 3695 3/26/2026