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 .
Response to Arguments
Applicant's arguments filed 3 April 2026 with respect to the 101 rejection have been fully considered but they are not persuasive. Applicant argues on pages 12-14 that the claims do not recite an abstract idea. The Examiner disagrees and restates the reasoning as well as the findings of the PTAB decision dated 9/11/2025 on pages 6-14. As to the amendments directed to the linear regression model, the Examiner points to page 13 of the PTAB decision specifically addressing the training of the predictive model as well as the multiple linear regressions and multicollinearity, which the PTAB determined to be a mathematical concept. Applicant argues the claims do not recite any of the enumerated abstract idea, but the PTAB affirmation clearly comes to a different conclusion, which is instructive because the claim amendments have not overcome or removed the PTAB affirmed abstract idea of certain methods of organizing human activity of commercial or legal interaction of processing financial data to determine BIN utilization for the purpose of determining fees. Applicant further argues on pages 14-17 that the claims do not recite certain methods of organizing human activity, but the Examiner disagrees. The prior rejections correctly identified the abstract idea which was affirmed by the PTAB in the decision dated 9/11/2025. And as stated by the PTAB on page 8 of the decision, claiming the concept of organizing the financial activities of financial institutions and payment processors based on historical data records and mathematical aclaulations of ratios and the like (see Spec. paras. [0054]-[0058] for linear regressions of BIN use), merely combines the abstract ideas as another abstract idea. See RecogniCorp, 855 F.3d at 1327. Applicant argues on pages 18-21 that the amended claims integrate the abstract idea into a practical application, specifically that the claims do not merely apply a generic machine learning model and recite a specific improvement to how the model is trained and operates. The claims do not contain specific limitations as to how the model operates and modifying the inputs to reduce redundancy amounts to no more than manipulating gathered information/data, see MPEP 2106.05(g). Computer efficiency is not recited in the claims or discussed in the specification and the claim limitations are not similar to the subject matter of Enfish. These additional elements are also part of the abstract idea which the PTAB wrote on page 16 of the decision cannot integrate an abstract idea into a practical application. Applicant argues on pages 21-24 that the claims as a whole recite significantly more than the alleged abstract idea, but the Examiner disagrees because the claim amendments do not provide an inventive concept and the as aspects of the mathematical relationship, which is an abstract idea affirmed by the PTAB decision dated 9/11/2025 pages 12-14. The specific sequence of operations involves manipulating gathered data, which is not significantly more than the abstract idea and does not integrate the abstract idea into a practical application, see MPEP 2106.05(g).
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 1-8, 10-18, and 20-22 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. In the instant case, claim 1 is directed to a “computer implemented method”.
Claim 1 is directed to the concept of “processing financial data to determine BIN utilization for the purpose of determining fees” which is grouped under “organizing human activity…commercial or legal interactions (The background section of the Applicant's specification, paragraphs [0004]-[0007], describes the that financial institutions buy the right to use a BIN from a payment processor, and then the payment processors may charge "hefty fees for BINs that are under-utilized" which is a contractual relationship between the financial institution and the payment processor and clearly a commercial interaction under the "rent-a-BIN" scheme. Please see MPEP 2106.04(a)(2)(II)(B) which gives "managing a stable value protected life insurance policy via performing calculations" as an example of subject matter where the commercial or legal interaction is an agreement in the form of contracts” in prong one of step 2A (See MPEP 2106.04(a)(2)). Claim 1 recites obtaining at least one historical data record associated with a financial institution; aggregating the at least one historical data record based on related attributes in the at least one historical data record; normalizing the at least one historical data record to a predetermined format; training [a predictive model comprising a linear regression model] to predict future bank identification number (BIN) utilization, wherein training [the predictive model] comprises: providing the at least one historical data record as input to the [linear regression model]; determining features of the at least one historical data record; determining correlation relationships between the features of the historical data record; identifying multicollinear input variables based on the determined correlation relationships; modifying the identified multicollinear input variables to reduce redundancy among the multicollinear input variables by at least one of: (i) removing one or more of the identified multicollinear input variables, or (ii) generating one or more variables based on a linear combination of the identified multicollinear input variables; and training [the linear regression model] the modified input variables to generate a trained [predictive model] configured to predict the future BIN utilization; calculating a ratio of active and issued payment cards associated with one or more BINs owned by the financial institution; calculating a ratio of inactive and issued payment cards associated with one or more BINs owned by the financial institution; using the at least one historical data record, the ratio of active and issued payment cards associated with one or more BINs, and the ratio of inactive and issued payment cards associated with one or more BINs, for training [the predictive model]; obtaining, from at least one data store, at least one non-historical data record associated with the financial institution; determining, by applying the [predictive model] to the at least one non-historical data record, one or more BINs that do not meet a predetermined utilization; and generating a visualization of at least one of the at least one non-historical or at least one historical data record, wherein the visualization comprises: an indication of BINs that do not meet the predetermined utilization; an indication of utilization of one or more BINs owned by the financial institution based on the ratio of active and issued payment cards associated with the one or more BINs; and an indication of utilization of one or more BINs owned by the financial institution based on the ratio of inactive and issued payment cards associated with the one or more BINs. Additionally, the claims recite a mathematical relationship of training a predictive model to predict future BIN utilization by providing the at least one historical data record as input to the linear regression model, determining features of the at least one historical data record, determining correlation relationships between the features of the historical data record, identifying multicollinear input variable, modifying the identified multicollinear input variables to reduce redundancy…, and training the linear regression model. See also the PTAB decision dated 9/11/2025 pages 12-14 discussing the mathematical relationship and training the model. Accordingly, the claim recites an abstract idea (See MPEP 2106.04(a)(2)).
This judicial exception is not integrated into a practical application because, when analyzed under prong two of step 2A (See MPEP 2106.04(d)), the additional elements of the claim such as the non-transitory computer readable medium, at least one processor, at least one data store represent the use of a computer as a tool to perform an abstract idea and/or does no more than ‘Apply it’ the abstract idea to a particular field of use (MPEP 2106.05(f)&(h)). The predictive model comprising a linear regression model is no more than insignificant extra-solution activity amount to no more than manipulating gathered information, see MPEP 2106.05(g). Therefore, the additional elements do not integrate the abstract idea into a practical application as they do no more than represent a computer performing functions that correspond to (i.e. implement) the acts of processing financial data to determine BIN utilization for the purpose of determining fees.
When analyzed under step 2B (See MPEP 2106.05), the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception itself. Viewed as a whole, the combination of elements recited in the claims merely describe the concept of processing financial data to determine BIN utilization for the purpose of determining fees using computer technology (e.g.at least one processor). The computer components implementing the abstract idea appear to be generic in view of at least Applicant's specification, [0039]. Focusing on the additional element of "predictive model comprising a linear regression model" identified as extra solution activity above, evidence that this element is well understood, routine and conventional can be found in Guven Kaya (US 2015/0294246) ([0040], [0041]); and Basch (US 6,119,103) (11:51-12:2). Therefore, the use of these additional elements does no more than employ a computer as a tool to automate and/or implement the abstract idea, which cannot provide significantly more than the abstract idea itself (MPEP 2106.05(I)(A)(f) & (h)).
Dependent claims 2-8, 10, 12-18, and 20-22 do not remedy the deficiencies of the independent claims and are rejected accordingly. The dependent claims further refine the abstract idea of the independent claims and do not integrate the abstract idea into a practical application. Specifically, claims 2-8, 10, 12-18 and 20-22 merely refine the abstract idea (2A1) by invoking a computer as a tool to perform an existing process (2A2, 2B). Regarding the further additional elements in the dependent claims including the GUI (claims 2, 12); and network (claims 3, 13), please see MPEP 2106.05(f)(2) discussing when the claim invokes computers or other machinery merely as a tool to perform an existing process including use of a computer or other machinery for economic tasks this does not show integration into a practical application or provide significantly more. With respect to the machine learning additional elements, please also see Recentive Analytics, Inc. V. Fox Corp., No. 2023-2437 (Fed. Cir. Apr. 18, 2025), which affirmed the District of Delaware's dismissal of Recentive's infringement suit on the ground that the asserted patents were directed to ineligible subject matter under 35 U.S.C. § 101. The decision reinforces the courts' view that applying generic machine learning techniques to known problems - without technical innovation in the machine learning methods themselves - is insufficient for patent eligibility. In this case, all claims have been reviewed and are found to be substantially similar and linked to the same abstract idea (see Content Extraction and Transmission LLC v. Wells Fargo (Fed. Cir. 2014)).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Russo US 3576976 discussing linear regressions; Lister US WO 2018/013080A1
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 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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DAVID P SHARVIN whose telephone number is (571)272-9863. The examiner can normally be reached M-F 9 am - 5 pm EST.
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/DAVID P SHARVIN/Primary Examiner, Art Unit 3692
