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 communications filed on 08/20/2026.
Claims 1, 7, 9, 11, 17, and 19 have been amended and are hereby entered.
Claims 6, 8, 10, 16, 18, and 20 have been canceled.
Claims 1-5, 7, 9, 11-15, 17, and 19 are currently pending and have been examined.
This action is made Non-Final.
Examiner Request
The Applicant is requested to indicate where in the specification there is support for future claim amendments to avoid U.S.C 112(a) issues that can arise. The Examiner thanks the Applicant in advance.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 08/20/2026 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 08/20/2026 has been entered.
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 1-5, 7, 9, 11-15, 17, and 19 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea of identifying a set of optimized financing programs by estimating and determining the rating of cash flow of the financing programs, and without significantly more.
Claim 1 is directed to a method, which is one of the statutory categories of invention; and Claim 11 is directed to an apparatus, which is one of the statutory categories of invention (Step 1: YES).
Claim 1 is directed to a method for improving user interface elements to be presented in association with identifying a set of optimized financing programs to provide to a computing device of a merchant, the method comprising: receiving historical loan application data defining historical parameters associated with corresponding historical loan applications; replacing at least a portion of the historical parameters of the historical loan application data with new parameters associated with a plurality of different loan terms to define a simulated loan data set defining simulated financing programs, wherein the simulated loan data set comprises billions of simulated loan applications generated by applying each of the plurality of different loan terms to the historical loan application data; determining a selection probability score for each of the simulated financing programs by applying each of the simulated financing programs to a take-up and terms selection model, the selection probability score indicating a likelihood of customer selection of each respective one of the simulated financing programs; determining a cash flow rating for each of the simulated financing programs by applying each of the simulated financing programs to a loan transition model that models, on a loan-by- loan basis, a probability of transitioning into any of a plurality of states of a loan from a current state, the cash flow rating estimating cash flow over time for the each respective one of the simulated financing programs, wherein determining the selection probability score, determining the cash flow rating, and determining a valuation score are each performed using simulation scaling comprising in-memory distributed computation tools and monotonicity constraints added to the take-up and terms selection model and the loan transition model to prevent the models from overfitting to noise; generating a display interface screen at a client device, the display interface screen including entry fields for entering merchant business metrics including a first text box receiving entry of industry information by the merchant, a second text box receiving entry of product information associated with the merchant, and a third text box receiving definition of an objective or goal of the merchant; determining the valuation score based on the selection probability score and the cash flow rating of the each respective one of the simulated financing programs; identifying an efficient frontier of the simulated financing programs as a set of optimal financing parameters that maximize return on assets for a given gross merchandise volume for the merchant, based on the valuation score and the merchant business metrics; determining the set of optimized financing programs based on the identified efficient frontier; and employing a multi-arm bandit (MAB) optimization algorithm to define testing to determine an optimal user interface widget to employ for customer engagement with respect to the determined set of optimized financing programs, wherein the MAB optimization algorithm is an offline batch framework executed on batch data at a selected cadence for each experiment to dynamically allocate traffic for experimentation for checkout flow and repayment messages using Thompson Sampling, wherein, after each iteration of collecting feedback, arm weights are updated using Thompson Sampling and traffic is assigned to cohorts based on the updated arm weights, to speed convergence of experiments associated with the defined testing and employ perpetual learning adaptive to external environment changes to determine the optimal user interface widget based on user context with respect to obtaining or paying back a loan to minimize cost instead of optimizing loan volume, wherein the MAB optimization algorithm receives user context information and adaptively selects which checkout funnel to direct a given user to, or what message content to send a user based on a particular context or situation of the user, wherein different widgets defining respective different webpages, buttons, and colors are tested corresponding to respective different tasks, and wherein each experiment is assigned a budget to define boundaries for exploration of feature space relative to data collection in terms of cost. These limitations describe the abstract idea of identifying a set of optimized financing programs by estimating and determining the rating of cash flow of the financing programs, (with the exception of the italicized and bolded terms above), which is mitigating risk by determining an optimized set of financing programs to offer to a merchant to enable the merchant to offer one or more of the financing programs from the optimized set to prospective customers, while also minimizing risk or maximizing revenue to the underwriter; therefore, corresponding to a fundamental economic principle or practice (including mitigating risk). Hence, a fundamental economic principle or practice (mitigating risk) is a Certain Methods of Organizing Human Activity. The abstract idea is also the enabling of the merchant to offer one or more financing programs to prospective customers, which is a commercial interaction. Therefore, a commercial interaction is also a Certain Methods of Organizing Human Activity. The system limitations, e.g., a computing device of a merchant; user interface elements, take-up and terms selection model, loan transition model, in-memory distributed computation tools, models, display interface screen, client device, simulation scaling, multi-arm bandit (MAB) optimization algorithm, offline batch framework, optimal user interface widget, perpetual learning, and different widgets do not necessarily restrict the claim from reciting an abstract idea. Thus, Claim 1 recites an abstract idea (Step 2A-Prong 1: YES).
This judicial exception is not integrated into a practical application because the additional elements of a computing device of a merchant; user interface elements, take-up and terms selection model, loan transition model, in-memory distributed computation tools, models, display interface screen, client device, simulation scaling, multi-arm bandit (MAB) optimization algorithm, offline batch framework, optimal user interface widget, perpetual learning, and different widgets, are no more than simply applying the abstract idea using generic computer elements. The additional elements listed above are all recited at a high level of generality and under their broadest reasonable interpretation comprises a generic computing arrangement. The presence of a generic computer arrangement is nothing more than to implement the claimed invention (MPEP 2106.05(f)). Therefore, the recitations of additional elements do not meaningfully apply the abstract idea and hence do not integrate the abstract idea into a practical application. Thus, claim 1 does not integrate the abstract idea into a practical application (Step 2A-Prong 2: NO).
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 computing device of a merchant; user interface elements, take-up and terms selection model, loan transition model, in-memory distributed computation tools, models, display interface screen, client device, simulation scaling, multi-arm bandit (MAB) optimization algorithm, offline batch framework, optimal user interface widget, perpetual learning, and different widgets 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. The additional elements when considered separately and as an ordered combination do not amount to add significantly more as these limitations provide nothing more than to simply apply the exception in a generic computer environment (Step 2B: NO). Thus, claim 1 is not patent eligible.
Dependent claims 2-5, 7, and 9 are directed to a method, which recites a series of steps that describe the abstract idea of identifying a set of optimized financing programs by estimating and determining the rating of cash flow of the financing programs. Furthermore, dependent claims 2-5, 7, and 9 are directed to a method, which recites a series of steps that describe the abstract idea of identifying a set of optimized financing programs by estimating and determining the rating of cash flow of the financing programs, which is mitigating risk by determining an optimized set of financing programs to offer to a merchant to enable the merchant to offer one or more of the financing programs from the optimized set to prospective customers, while also minimizing risk or maximizing revenue to the underwriter; therefore, corresponding to a fundamental economic principle or practice (including mitigating risk). Hence, a fundamental economic principle or practice (mitigating risk) is a Certain Methods of Organizing Human Activity. The abstract idea is also the enabling of the merchant to offer one or more financing programs to prospective customers, which is a commercial interaction. Therefore, a commercial interaction is also a Certain Methods of Organizing Human Activity. Thus, claims 2-5, 7, and 9 are directed to an abstract idea. The additional elements of a computing device of a merchant; user interface elements, take-up and terms selection model, loan transition model, in-memory distributed computation tools, models, display interface screen, client device, simulation scaling, multi-arm bandit (MAB) optimization algorithm, offline batch framework, optimal user interface widget, perpetual learning, and different widgets are no more than simply applying the abstract idea using generic computer elements. The presence of a generic computer arrangement is nothing more than to implement the claimed invention (MPEP 2106.05(f)). Therefore, the recitations of additional elements do not meaningfully apply the abstract idea and hence do not integrate the abstract idea into a practical application. Furthermore, the additional elements: a computing device of a merchant; user interface elements, take-up and terms selection model, loan transition model, in-memory distributed computation tools, models, display interface screen, client device, simulation scaling, multi-arm bandit (MAB) optimization algorithm, offline batch framework, optimal user interface widget, perpetual learning, and different widgets, do not amount to add significantly more as these limitations provide nothing more than to simply apply the exception in a generic computer environment.
Claim 11 is directed to an apparatus for improving user interface elements to be presented in association with identifying a set of optimized financing programs to provide to a computing device of a merchant, the apparatus comprising processing circuitry configured to: receive historical loan application data defining historical parameters associated with corresponding historical loan applications; replace at least a portion of the historical parameters of the historical loan application data with new parameters associated with a plurality of different loan terms to define a simulated loan data set defining simulated financing programs, wherein the simulated loan data set comprises billions of simulated loan applications generated by applying each of the plurality of different loan terms to the historical loan application data; determine a selection probability score for each of the simulated financing programs by applying each of the simulated financing programs to a take-up and terms selection model, the selection probability score indicating a likelihood of customer selection of each respective one of the simulated financing programs; determine a cash flow rating for each of the simulated financing programs by applying each of the simulated financing programs to a loan transition model that models, on a loan-by- loan basis, a probability of transitioning into any of a plurality of states of a loan from a current state, the cash flow rating estimating cash flow over time for the each respective one of the simulated financing programs, wherein determining the selection probability score, determining the cash flow rating, and determining a valuation score are each performed using simulation scaling comprising in-memory distributed computation tools and monotonicity constraints added to the take-up and terms selection model and the loan transition model to prevent the models from overfitting to noise; generate a display interface screen at a client device, the display interface screen including entry fields for entering merchant business metrics including a first text box receiving entry of industry information by the merchant, a second text box receiving entry of product information associated with the merchant, and a third text box receiving definition of an objective or goal of the merchant; determine the valuation score based on the selection probability score and the cash flow rating of the each respective one of the simulated financing programs; identify an efficient frontier of the simulated financing programs as a set of optimal financing parameters that maximize return on assets for a given gross merchandise volume for the merchant, based on the valuation score and the merchant business metrics; determine the set of optimized financing programs based on the identified efficient frontier; and employ a multi-arm bandit (MAB) optimization algorithm to define testing to determine an optimal user interface widget to employ for customer engagement with respect to the determined set of optimized financing programs, wherein the MAB optimization algorithm is an offline batch framework executed on batch data at a selected cadence for each experiment to dynamically allocate traffic for experimentation for checkout flow and repayment messages using Thompson Sampling, wherein, after each iteration of collecting feedback, arm weights are updated using Thompson Sampling and traffic is assigned to cohorts based on the updated arm weights, to speed convergence of experiments associated with the defined testing and employ perpetual learning adaptive to external environment changes to determine the optimal user interface widget based on user context with respect to obtaining or paying back a loan to minimize cost instead of optimizing loan volume, wherein the MAB optimization algorithm receives user context information and adaptively selects which checkout funnel to direct a given user to, or what message content to send a user based on a particular context or situation of the user, wherein different widgets defining respective different webpages, buttons, and colors are tested corresponding to respective different tasks, and wherein each experiment is assigned a budget to define boundaries for exploration of feature space relative to data collection in terms of cost. These limitations describe the abstract idea of identifying a set of optimized financing programs by estimating and determining the rating of cash flow of the financing programs, (with the exception of the italicized and bolded terms above), which is mitigating risk by determining an optimized set of financing programs to offer to a merchant to enable the merchant to offer one or more of the financing programs from the optimized set to prospective customers, while also minimizing risk or maximizing revenue to the underwriter; therefore, corresponding to a fundamental economic principle or practice (including mitigating risk). Hence, a fundamental economic principle or practice (mitigating risk) is a Certain Methods of Organizing Human Activity. The abstract idea is also the enabling of the merchant to offer one or more financing programs to prospective customers, which is a commercial interaction. Therefore, a commercial interaction is also a Certain Methods of Organizing Human Activity. The system limitations, e.g., an apparatus, computing device of a merchant; user interface elements, processing circuitry, take-up and terms selection model, loan transition model, in-memory distributed computation tools, models, display interface screen, client device, simulation scaling, multi-arm bandit (MAB) optimization algorithm, offline batch framework, optimal user interface widget, perpetual learning, and different widgets do not necessarily restrict the claim from reciting an abstract idea. Thus, Claim 11 recites an abstract idea (Step 2A-Prong 1: YES).
This judicial exception is not integrated into a practical application because the additional elements of an apparatus, computing device of a merchant; user interface elements, processing circuitry, take-up and terms selection model, loan transition model, in-memory distributed computation tools, models, display interface screen, client device, simulation scaling, multi-arm bandit (MAB) optimization algorithm, offline batch framework, optimal user interface widget, perpetual learning, and different widgets are no more than simply applying the abstract idea using generic computer elements. The additional elements listed above are all recited at a high level of generality and under their broadest reasonable interpretation comprises a generic computing arrangement. The presence of a generic computer arrangement is nothing more than to implement the claimed invention (MPEP 2106.05(f)). Therefore, the recitations of additional elements do not meaningfully apply the abstract idea and hence do not integrate the abstract idea into a practical application. Thus, claim 11 does not integrate the abstract idea into a practical application (Step 2A-Prong 2: NO).
Claim 11 does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements of an apparatus, computing device of a merchant; user interface elements, processing circuitry, take-up and terms selection model, loan transition model, in-memory distributed computation tools, models, display interface screen, client device, simulation scaling, multi-arm bandit (MAB) optimization algorithm, offline batch framework, optimal user interface widget, perpetual learning, and different widgets 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. The additional elements when considered separately and as an ordered combination do not amount to add significantly more as these limitations provide nothing more than to simply apply the exception in a generic computer environment (Step 2B: NO). Thus, claim 11 is not patent eligible.
Dependent claims 12-15, 17, and 19 are directed to an apparatus, which performs a series of steps that describe the abstract idea of identifying a set of optimized financing programs by estimating and determining the rating of cash flow of the financing programs. Furthermore, dependent claims 12-15, 17, and 19 are directed to an apparatus, which performs a series of steps that describe the abstract idea of identifying a set of optimized financing programs by estimating and determining the rating of cash flow of the financing programs, which is mitigating risk by determining an optimized set of financing programs to offer to a merchant to enable the merchant to offer one or more of the financing programs from the optimized set to prospective customers, while also minimizing risk or maximizing revenue to the underwriter; therefore, corresponding to a fundamental economic principle or practice (including mitigating risk). Hence, a fundamental economic principle or practice (mitigating risk) is a Certain Methods of Organizing Human Activity. The abstract idea is also the enabling of the merchant to offer one or more financing programs to prospective customers, which is a commercial interaction. Therefore, a commercial interaction is also a Certain Methods of Organizing Human Activity. Thus, claims 12-15, 17, and 19 are directed to an abstract idea. The additional elements of an apparatus, computing device of a merchant; user interface elements, processing circuitry, take-up and terms selection model, loan transition model, in-memory distributed computation tools, models, display interface screen, client device, simulation scaling, multi-arm bandit (MAB) optimization algorithm, offline batch framework, optimal user interface widget, perpetual learning, and different widgets are no more than simply applying the abstract idea using generic computer elements. The presence of a generic computer arrangement is nothing more than to implement the claimed invention (MPEP 2106.05(f)). Therefore, the recitations of additional elements do not meaningfully apply the abstract idea and hence do not integrate the abstract idea into a practical application. Furthermore, the additional elements: an apparatus, computing device of a merchant; user interface elements, processing circuitry, take-up and terms selection model, loan transition model, in-memory distributed computation tools, models, display interface screen, client device, simulation scaling, multi-arm bandit (MAB) optimization algorithm, offline batch framework, optimal user interface widget, perpetual learning, and different widgets, do not amount to add significantly more as these limitations provide nothing more than to simply apply the exception in a generic computer environment.
Dependent claims 2-5, 7, 9, 12-15, 17, and 19 have further defined the abstract idea that is present in their respective independent claims 1 and 11; and thus correspond to Certain Methods of Organizing Human Activity, and hence are abstract in nature for the reason presented above. The dependent claims 2-5, 7, 9, 12-15, 17, and 19 do not include any additional elements that integrate the abstract idea into a practical application or are sufficient to amount to significantly more than the judicial exception when considered both individually and as an ordered combination. Therefore, claims 2-5, 7, 9, 12-15, 17, and 19 are directed to an abstract idea without significantly more.
Thus, claims 1-5, 7, 9, 11-15, 17, and 19 are not patent-eligible.
Response to Arguments
With respect to the claim objections of claims 1, 11, and 15, the objections are withdrawn in view of Applicant’s arguments/remarks made in an amendment filed on 08/20/2026.
Applicant's arguments filed on 08/20/2026 have been fully considered, but are not persuasive due to the following reasons:
With respect to the rejection of claims 1-20 under 35 U.S.C. 101, Applicant arguments are moot in view of the grounds of rejections presented above in this office action. The arguments are addressed to the extent they apply to the amended claims.
Applicant argues that “at least some of the additional material added includes additional elements that cannot fairly be construed as being recited only "at a high level of generality.” In this regard, for example, independent claims 1 and 11 recite determining the selection probability score, determining the cash flow rating, and determining a valuation score are each performed using simulation scaling comprising in-memory distributed computation tools and monotonicity constraints added to the take-up and terms selection model and the loan transition model to prevent the models from overfitting to noise. This additional detail makes clear that the invention improves the technology area by ensuring that the models do not overfit to noise in a context in which billions of simulated loan applications are being considered. Moreover, the detail is neither recited at a high level of generality, nor simply performance of generic steps on a computer that amounts to no more than merely "applying it" at the generic computer. ….. These additional details are neither recited at a high level of generality, nor merely apply an abstract idea on a general purpose computer. Moreover, all of these details, when considered in totality, amount to significantly more than any alleged abstract idea. Thus, as presently recited, independent claims 1 and 11 result in computer functionality or technical improvement, and not merely a business solution. Thus, the claimed invention provides a practical application by improving a technology (i.e., efficient information gathering in a context of massive amounts of information all on one screen while avoiding susceptibility to noise), and also includes additional elements that amount to substantially more than any abstract idea (i.e., speeding testing and experimentation convergence and employing perpetual learning) since the tool described is key to the solution. As such, independent claims 1 and 11 are each directed to applications or functions that are patent eligible at least by reciting an inventive concept and practical application. Once independent claims 1 and 11 are appreciated to be patent eligible, dependent claims 2-5, 7, 9, 12-15, 17 and 19 should also be considered patent eligible. Accordingly, Applicants respectfully submit that the rejections of claims 1-5, 7, 9, 11-15, 17 and 19 on statutory grounds are overcome. For all the reasons provided above, Applicant respectfully submits that claims 1-5, 7, 9, 11-15, 17 and 19 are presently in condition for allowance.”
Examiner respectfully disagrees.
Under Step 2A: Prong I, as previously discussed, Examiner respectfully notes that the claims, as amended, is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea of identifying a set of optimized financing programs by estimating and determining the rating of cash flow of the financing programs; without significantly more. The series of steps recited in claim 1, as amended, describe the abstract idea of identifying a set of optimized financing and programs by estimating and determining the rating of cash flow of the financing programs, which is mitigating risk by determining an optimized set of financing programs to offer to a merchant to enable the merchant to offer one or more of the financing programs from the optimized set to prospective customers, while also minimizing risk or maximizing revenue to the underwriter; therefore, corresponding to a fundamental economic principle or practice (including mitigating risk). Hence, a fundamental economic principle or practice (mitigating risk) is a Certain Methods of Organizing Human Activity. The abstract idea is also the enabling of the merchant to offer one or more financing programs to prospective customers, which is a commercial interaction. Therefore, a commercial interaction is also a Certain Methods of Organizing Human Activity. Furthermore, the system limitations (Claim 11), e.g., an apparatus, computing device of a merchant; user interface elements, processing circuitry, take-up and terms selection model, loan transition model, in-memory distributed computation tools, models, display interface screen, client device, simulation scaling, multi-arm bandit (MAB) optimization algorithm, offline batch framework, optimal user interface widget, perpetual learning, and different widgets do not necessarily restrict the claim from reciting an abstract idea.
Furthermore, Examiner respectfully notes that the claims are first analyzed in the absence of technology to determine if it recites an abstract idea. The additional limitations of technology are then considered to determine if it restricts the claim from reciting an abstract idea. In this case, and as discussed in the 2019 and 2024 Updated Guidance on Patent Subject Matter Eligibility, it is determined that the additional limitations of technology do not necessarily restrict the claim from reciting an abstract idea. Furthermore, Examiner respectfully notes that the recited features in the limitations, as amended, are making use of a computer and the computer limitations do not necessarily restrict the claim from reciting an abstract idea as discussed above under Step 2A-Prong I of the 35 U.S.C. 101 rejection. Hence, Examiner has also considered each and every arguments under Step 2A-Prong I and concludes that these arguments are not persuasive. For example, under Step 2A-Prong I, Examiner considers each and every limitation to determine if the claim recites an abstract idea. In this case, it is determined that the claim recites an abstract idea and the additional limitations of a computer device does not necessarily restrict the claim from reciting an abstract idea. The recited steps, as amended, are abstract in nature as there are no technical/technology improvements as a result of these steps. Thus, the claim recites an abstract idea. Whether the claim integrates the abstract idea into a practical application by providing technical/technology improvements are considered under Step 2A-Prong II.
Under Step 2A: Prong II, as previously discussed in the Final Office action dated 04/11/2025, Non-Final Office action dated 09/23/2025, and Final Office action dated 03/20/2026, Examiner respectfully notes that there is no improved technology in simply presenting, providing, receiving, replacing, defining, determining, estimating, executing, allocating, generating, displaying, applying, entering, testing, assigning, and outputting data (i.e., historical loan data, simulated loan data, customer data, financing data, cash flow data, valuation score data, batch data, merchandise volume data, merchant business metrics, user context information, cost data, and etc.). The disclosed invention simply cannot be equated to improvement to technological practices or computers. There is no technical improvement at all. Instead, Applicant recites (claim 11) “an apparatus for improving user interface elements to be presented in association with identifying a set of optimized financing programs to provide to a computing device of a merchant, the apparatus comprising processing circuitry configured to: receive historical loan application data defining historical parameters associated with corresponding historical loan applications; replace at least a portion of the historical parameters of the historical loan application data with new parameters associated with a plurality of different loan terms to define a simulated loan data set defining simulated financing programs, wherein the simulated loan data set comprises billions of simulated loan applications generated by applying each of the plurality of different loan terms to the historical loan application data; determine a selection probability score for each of the simulated financing programs by applying each of the simulated financing programs to a take-up and terms selection model, the selection probability score indicating a likelihood of customer selection of each respective one of the simulated financing programs; determine a cash flow rating for each of the simulated financing programs by applying each of the simulated financing programs to a loan transition model that models, on a loan-by- loan basis, a probability of transitioning into any of a plurality of states of a loan from a current state, the cash flow rating estimating cash flow over time for the each respective one of the simulated financing programs, wherein determining the selection probability score, determining the cash flow rating, and determining a valuation score are each performed using simulation scaling comprising in-memory distributed computation tools and monotonicity constraints added to the take-up and terms selection model and the loan transition model to prevent the models from overfitting to noise; generate a display interface screen at a client device, the display interface screen including entry fields for entering merchant business metrics including a first text box receiving entry of industry information by the merchant, a second text box receiving entry of product information associated with the merchant, and a third text box receiving definition of an objective or goal of the merchant; determine the valuation score based on the selection probability score and the cash flow rating of the each respective one of the simulated financing programs; identify an efficient frontier of the simulated financing programs as a set of optimal financing parameters that maximize return on assets for a given gross merchandise volume for the merchant, based on the valuation score and the merchant business metrics; determine the set of optimized financing programs based on the identified efficient frontier; and employ a multi-arm bandit (MAB) optimization algorithm to define testing to determine an optimal user interface widget to employ for customer engagement with respect to the determined set of optimized financing programs, wherein the MAB optimization algorithm is an offline batch framework executed on batch data at a selected cadence for each experiment to dynamically allocate traffic for experimentation for checkout flow and repayment messages using Thompson Sampling, wherein, after each iteration of collecting feedback, arm weights are updated using Thompson Sampling and traffic is assigned to cohorts based on the updated arm weights, to speed convergence of experiments associated with the defined testing and employ perpetual learning adaptive to external environment changes to determine the optimal user interface widget based on user context with respect to obtaining or paying back a loan to minimize cost instead of optimizing loan volume, wherein the MAB optimization algorithm receives user context information and adaptively selects which checkout funnel to direct a given user to, or what message content to send a user based on a particular context or situation of the user, wherein different widgets defining respective different webpages, buttons, and colors are tested corresponding to respective different tasks, and wherein each experiment is assigned a budget to define boundaries for exploration of feature space relative to data collection in terms of cost.” The recited features in the limitations, as amended, do not result in computer functionality or technical improvement. Furthermore, Examiner respectfully notes that Applicant is simply using a computer to input, process, and output data. As previously discussed in the Final Office action dated 04/11/2025, Non-Final Office action dated 09/23/2025, and Final Office action dated 03/20/2026, the recited features in the limitations does not disclose a technical solution to technical problem, but simply a business solution. Specifically, the recited steps in independent claims 1 and 11, as amended, are merely managing/processing data (MPEP 2106.05(d)(II)) and does not result in computer functionality or technical improvement. Thus, Applicant has simply provided a business method practice of generating and transmitting (i.e., managing/processing) data, and no technical solution or improvement has been disclosed. Moreover, there is no technology/technical improvement as a result of implementing the abstract idea. The recited limitations in the pending claims simply amount to the abstract idea of generating and transmitting historical loan data, simulated loan data, customer data, financing data, valuation score data, batch data, and etc. There is no computer functionality improvement or technology improvement. The claim does not provide a technical solution to a technical problem. If there is an improvement, it is to the abstract idea and not to technology. Additionally, Examiner notes that it is important to keep in mind that an improvement in the judicial exception itself (e.g., recited fundamental economic principle or practice and/or commercial interaction) is not an improvement in technology (See, MPEP 2106.05(a)(II)). Moreover, claim 1 and claim 11, as amended, recites the additional elements of an apparatus, computing device of a merchant; user interface elements, processing circuitry, take-up and terms selection model, loan transition model, in-memory distributed computation tools, models, display interface screen, client device, simulation scaling, multi-arm bandit (MAB) optimization algorithm, offline batch framework, optimal user interface widget, perpetual learning, and different widgets. The recited limitations, as amended, are merely steps of gathering and outputting data. In addition, all uses of the recited judicial exceptions require such data gathering and output, and, as such, these limitations do not impose any meaningful limits on the claim. These limitations amount to necessary data gathering and outputting. See MPEP 2106.05.Thus, the claim does not integrate the abstract idea into a practical application; and these arguments are not persuasive.
Additionally, these steps, as amended, are recited as being performed by an apparatus, computing device of a merchant; user interface elements, processing circuitry, take-up and terms selection model, loan transition model, in-memory distributed computation tools, models, display interface screen, client device, simulation scaling, multi-arm bandit (MAB) optimization algorithm, offline batch framework, optimal user interface widget, perpetual learning, and different widgets. The additional elements: an apparatus, computing device of a merchant; user interface elements, processing circuitry, take-up and terms selection model, loan transition model, in-memory distributed computation tools, models, display interface screen, client device, simulation scaling, multi-arm bandit (MAB) optimization algorithm, offline batch framework, optimal user interface widget, perpetual learning, and different widgets are used as a tool to perform the generic computer function of receiving, processing, and outputting data. See MPEP 2106.05(f). As previously discussed, an apparatus, computing device of a merchant; user interface elements, processing circuitry, take-up and terms selection model, loan transition model, in-memory distributed computation tools, models, display interface screen, client device, simulation scaling, multi-arm bandit (MAB) optimization algorithm, offline batch framework, optimal user interface widget, perpetual learning, and different widgets are used to perform an abstract idea, as discussed above in Step 2A, Prong I, such that it amounts to no more than mere instructions to apply the exception using a generic computer. See MPEP 2106.05(f). Additionally, the recitation of an apparatus, computing device of a merchant; user interface elements, processing circuitry, take-up and terms selection model, loan transition model, in-memory distributed computation tools, models, display interface screen, client device, simulation scaling, multi-arm bandit (MAB) optimization algorithm, offline batch framework, optimal user interface widget, perpetual learning, and different widgets in the limitations of claims 1 and 11, as amended, merely indicates a field of use or technological environment in which the judicial exception is performed. The limitations, which are emphasized in the Applicant’s arguments merely confines the use of the abstract idea to a particular technological environment; and thus fails to add an inventive concept to the claims. See MPEP 2106.05(h). Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application, and the claim is directed to the judicial exception. Thus, these arguments are not persuasive.
Hence, Examiner respectfully declines Applicant’s request to withdraw the 35 U.S.C. 101 rejection of claims 1-5, 7, 9, 11-15, 17, and 19.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure is the following:
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Crawford (U.S. Patent Application Publication No. US 2003/0046223 A1) “Method and apparatus for explaining credit scores”
Mukherjee (U.S. Patent Application Publication No. US 2023/0401284 A1) “Hybrid quantum computing system for hyper parameter optimization in machine learning”
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Any inquiry concerning this communication or earlier communications from the examiner should be directed to MOHAMMED H MUSTAFA whose telephone number is (571)270-7978. The examiner can normally be reached M-F 8:00 - 5:00.
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/MOHAMMED H MUSTAFA/Examiner, Art Unit 3693
/ELIZABETH H ROSEN/Primary Examiner, Art Unit 3693
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