DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, 18/397,698, was filed on Dec. 27, 2023, and does not claim foreign priority or domestic benefit to any other application.
The effective filing date is after the AIA date of March 16, 2013, and so the application is being examined under the “first inventor to file” provisions of the AIA .
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
Status of the Application
This Final Office Action is in response to Applicant’s communication of 3/25/2026.
Claims 1, 2, 4-9, 11-16, and 18-21 are pending, of which claims 1, 8, and 15 are independent.
Claims 1, 8, and 15 are currently amended. Claims 3, 10, and 17 were previously cancelled.
All pending claims have been examined on the merits.
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, 2, 4-9, 11-16, and 18-21 are rejected under 35 U.S.C. §101 because the claimed invention is directed to non-statutory subject matter. The claimed invention is directed to an abstract idea, without “significantly more”.
In regards to Step 1 of the Alice/Mayo analysis, independent claim 1 is a method claim, claim 8 is an apparatus claim, and claim 15 is an article of manufacture claim or product by process claim (“non-transitory computer readable medium”).
For the sake of compact prosecution, we continue with the Alice/Mayo “abstract idea” analysis.
The abstract idea elements recited in independent claim 8 are shown in italic font. The “additional elements” and “extra solution steps” are shown in underlined font:
8. (Currently Amended) A system for generating subsidy vectors corresponding to a loan application, the system comprising:
a processor; and
a memory operatively connected to the processor via a communication interface, the memory storing computer readable instructions, when executed, causes the processor to:
implement a platform, language, cloud, and database agnostic optimal subsidies generating module (OSGM), by an optimal subsidies generating device (OSGD) executed by the processor, the OSGD being hosted on a cloud based network environment, wherein OSGM includes a receiving module, an implementing module, a storing module, an updating module, an evaluating module, a running module, and a generating module, wherein each module being called via a corresponding application programming interface, and wherein the OSGM is configured to execute interactions among the modules to identify and generate subsidy vectors with respect to constraints data corresponding to the loan application;
receive, via the receiving module, initial data corresponding to daily subsidy vector for each pricing segment with reference to the loan application;
implement, by calling the implementing module, an assessment process that determines a profit and loss calculation data and constraint scores based on the received initial data and outputs resulting vectors;
store, by calling the storing module, the resulting vectors along with the profit and loss calculation data and the constraint scores onto a database in a distributed cloud environment, wherein the OSGM enables consistent orchestration and exchange of data across heterogeneous platforms, databases, and cloud systems without reconfiguration of underlying data files;
update, by calling the updating module, surrogate function parameters of a surrogate function that captures relationships between the daily subsidy vector and a constraint score with new data points obtained from the database, the updating being performed via a Bayesian optimization engine;
evaluate, by calling the evaluating module, an acquisition function on the surrogate parameters to find a next query subsidy vector and combining the next query subsidy vector with the initial data to output an expanded set of vectors;
run, by calling the running module, the expanded set of vectors through the assessment process and generating new constraint scores;
automatically generate, by calling the generating module, new subsidy vectors corresponding to the new constraint scores;
display the new subsidy vectors onto a display;
receive user input via a user interface for final subsidy selection from the new subsidy vectors as displayed onto the display; and
automatically approve the loan application upon receiving the user input via the user interface in response to the final subsidy selection,
wherein the OSGM is configured to operate as a platform, language, database, and cloud agnostic module that enables consistent orchestration and passing of data among the modules regardless of platform, browser, programming language, database, or cloud environment, and wherein configuration or data files used by the OSGM are structured in a machine-readable format including at least one of JSON, XML, or YAML such that the OSGM is modified without altering underlying data files,
wherein the OSGM is executed within a cloud-based computing environment using one or more virtual machines or virtual servers and is configured for distributed and parallel processing across a plurality of server devices and databases coupled via one or more communication networks, and
wherein the storing module stores the resulting vectors, profit and loss calculation data, and constraint scores in one or more tuple stores, the updating module updates the surrogate function parameters based on data retrieved from the one or more tuple stores using a Bayesian optimization subsidy search, and the evaluating module evaluates the acquisition function to determine a next query subsidy vector that is combined with the received initial data to output the expanded set of vectors.
More specifically, claims 1, 2, 4-9, 11-16, and 18-21 recite an abstract idea: “Certain Methods of Organizing Human Activity", specifically “Commercial or Legal Interactions (Including Agreements in the form of Contracts; Legal Obligations; Advertising, Marketing, or Sales Activities or Behaviors; Business Relations)”, as discussed in MPEP §2106(a)(2) Parts (I) and (II), and in the 2019 Revised Patent Subject Matter Eligibility Guidance.
The “Fundamental Economic Principles or Practices (including Hedging, Insurance, Mitigating Risk)” elements include:
“implement, by calling the implementing module, an assessment process that determines a profit and loss calculation data and constraint scores based on the received initial data and outputs resulting vectors”.
“update, by calling the updating module, surrogate function parameters of a surrogate function that captures relationships between the daily subsidy vector and a constraint score with new data points obtained from the database, the updating being performed via a Bayesian optimization engine”
“evaluate, by calling the evaluating module, an acquisition function on the surrogate parameters to find a next query subsidy vector and combine the next query subsidy vector with the initial data to output an expanded set of vectors”.
“run, by calling the running module, the expanded set of vectors through the assessment process and generate new constraint scores”.
“automatically generate, by calling the generating module, new subsidy vectors corresponding to the new constraint scores”.
“automatically approve the loan application upon receiving the user input via the user interface in response to the final subsidy selection”.
In dependent claims 7 and 14: “wherein the subsidy corresponds to cost attached to every segment of the loan application segments.”
Moreover, claims 1, 2, 4-9, 11-16, and 18-21 recite “Mathematical Concepts", specifically “Mathematical Relationships”, “Mathematical Formulas or Equations”, and “Mathematical Calculations”, as discussed in MPEP §2106.04(a)(2) Part (IV), and in the 2019 Revised Patent Subject Matter Eligibility Guidance.
The mathematic elements include:
“implement a platform, language. cloud, and database agnostic optimal subsidies generating module (OSGM) … wherein the OSGM is configured to execute interactions among the modules to identify and generate subsidy vectors with respect to constraints data corresponding to the loan application”.
“implement, by calling the implementing module, an assessment process that determines a profit and loss calculation data and constraint scores based on the received initial data and outputs resulting vectors”.
“update, by calling the updating module, surrogate function parameters of a surrogate function that captures relationships between the daily subsidy vector and a constraint score with new data points obtained from the database, the updating being performed via a Bayesian optimization engine”,
“evaluate, by calling the evaluating module, an acquisition function on the surrogate parameters to find a next query subsidy vector and combine the next query subsidy vector with the initial data to output an expanded set of vectors”.
“run, by calling the running module, the expanded set of vectors through the assessment process and generate new constraint scores”.
“automatically generate, by calling the generating module, new subsidy vectors corresponding to the new constraint scores”.
“the evaluating module evaluates the acquisition function to determine a next query subsidy vector that is combined with the received initial data to output the expanded set of vectors”.
The “additional elements” include: “a processor” and “a memory operatively connected to the processor via a communication interface, the memory storing computer readable instructions”.
The “additional extra-solution elements” include:
“the memory storing computer readable instructions”,
“receive, by calling the receiving module, initial data corresponding to daily subsidy vector for each pricing segment with reference to a loan application”,
“store, by calling the storing module, the resulting vectors along with the profit and loss calculation data and the constraint scores onto a database in a distributed cloud environment”,
“display the new subsidy vectors onto a display”, and
“receive user input via a user interface for final subsidy selection from the new subsidy vectors as displayed onto the display”.
“wherein the storing module stores the resulting vectors, profit and loss calculation data, and constraint scores in one or more tuple stores, the updating module updates the surrogate function parameters based on data retrieved from the one or more tuple stores using a Bayesian optimization subsidy search”.
This abstract idea is not integrated into a practical application, because:
The claim is directed to an abstract idea with additional generic computer elements. The generically recited computer elements (“a processor” and “a memory operatively connected to the processor via a communication interface, the memory storing computer readable instructions”) do not add a meaningful limitation to the abstract idea, because they amount to simply implementing the abstract idea on a computer. The claim amounts to adding the words "apply it" (or an equivalent) with the abstract idea, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea.
The extra-solution activities (“the memory storing computer readable instructions”, “receive, by calling the receiving module, initial data”, “store, by calling the storing module, the resulting vectors … onto a database in a distributed cloud environment”, “display the new subsidy vectors onto a display”, “receive user input via a user interface for final subsidy selection from the new subsidy vectors as displayed onto the display”, “wherein the storing module stores the resulting vectors, profit and loss calculation data, and constraint scores in one or more tuple stores”, and “the updating module updates the surrogate function parameters based on data retrieved from the one or more tuple stores using a Bayesian optimization subsidy search”) do not add a meaningful limitation to the method, as they are insignificant extra-solution activity;
The combination of the abstract idea with the additional elements (generically recited computer elements), and/or with the extra-solution activities, does not integrate the abstract idea into a practical application.
The claims do not include additional elements that are sufficient to amount to significantly more than the abstract idea, because:
When considering the elements "alone and in combination" (“a processor” and “a memory operatively connected to the processor via a communication interface, the memory storing computer readable instructions”), they do not add significantly more (also known as an "inventive concept") to the exception, because they amount to simply implementing the abstract idea on a computer. Instead, they merely add the words "apply it" (or an equivalent) with the abstract idea, or mere instructions to implement an abstract idea on a computer, or merely use a computer as a tool to perform an abstract idea.
In regards to the extra solution activities (“the memory storing computer readable instructions”, “receive, by calling the receiving module, initial data”, “store, by calling the storing module, the resulting vectors … onto a database in a distributed cloud environment”, “display the new subsidy vectors onto a display”, “receive user input via a user interface for final subsidy selection from the new subsidy vectors as displayed onto the display”, “wherein the storing module stores the resulting vectors, profit and loss calculation data, and constraint scores in one or more tuple stores”, and “the updating module updates the surrogate function parameters based on data retrieved from the one or more tuple stores using a Bayesian optimization subsidy search”), these are recognized as such by the court decisions listed in MPEP § 2106.05(d).
More specifically, in regards to the “storing” and “updating” steps, see the court cases Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015) (storing and retrieving information in memory); and OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015) (storing and retrieving information in memory).
More specifically, in regards to the “receive, by calling the receiving module, initial data” and “receive user input via a user interface” steps, see the court cases OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network) and (presenting offers and gathering statistics), OIP Techs., 788 F.3d at 1362-63, 115 USPQ2d at 1092-93; buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network).
Moreover, in regards to the “displaying” steps, see Apple, Inc. v. Ameranth, Inc., 842 F.3d 1229, 120 U.S.P.Q.2d 1844 (Fed. Cir. 2016) (Holding that the claimed menu graphic user interface is an abstract idea under 35 USC §101, because claimant "[did] not claim a particular way of programming or designing the software to create menus that have these features, but instead merely claims the resulting systems").
The Examiner holds that the independent claims “use a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data)” or “simply add a general purpose computer or computer components after the fact to an abstract idea”.
The Examiner interprets that the following newly-added features are equivalent to reciting “apply the abstract idea on a general purpose computer”:
“wherein the OSGM is configured to operate as a platform, language, database, and cloud agnostic module that enables consistent orchestration and passing of data among the modules regardless of platform, browser, programming language, database, or cloud environment, and wherein configuration or data files used by the OSGM are structured in a machine-readable format including at least one of JSON, XML, or YAML such that the OSGM is modified without altering underlying data files,”.
“wherein the OSGM is executed within a cloud-based computing environment using one or more virtual machines or virtual servers and is configured for distributed and parallel processing across a plurality of server devices and databases coupled via one or more communication networks”.
Independent claims 8 and 15 are rejected on the same grounds as independent claim 1. Independent claim 15 is also rejected on the grounds that it recites a computer-readable medium, which is merely another generic computer component.
All dependent claims are also rejected, because they merely further define the abstract idea.
Response to Amendments
Re: Claim Rejections - 35 USC § 112
The 35 USC § 112(a) written description and scope of enablement rejections have been withdrawn, as necessitated by Applicant’s amendments to the claims.
Re: Claim Rejections - 35 USC § 101
The 35 USC § 101 rejection has been amended, as necessitated by Applicant’s amendments to the claims.
Conclusion
The art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 2025/0384487 A1 to Tsepenekas et al. “System and method for combining multiple pricing data sources for on-line bonds trading”. The effective filing date of June 14, 2026 disqualifies the reference as prior art.
US 12,639,338 B1 to Brugere et al. “System And Method For Fairness Aware Optimization With Features Quantization”. The effective filing date of March 5, 2025 disqualifies the reference as prior art. Also, it shares the same assignee as the present application (but has a different inventive entity). See especially col.1, lines 37-50 and col.2, lines 40-41:
(See Brugere, col.1, lines 37-50: “As illustrated in FIG. 10, a conventional optimization model may apply plus or minus basis points (bps) adjustments to base pricing based on various features of a loan application to maximize profit and losses (P&L) Features of the loan application may include a particular credit score associated with the application, which may have corresponding ranges of bps adjustments possible for maximizing profit. Although the bps adjustments may be applied to maximize P&L in the example of FIG. 10, such optimization may unwittingly result in providing disparate results for certain protected groups of people having certain race, ethnicity, gender or the like, and run afoul of one or more government regulations and/or organizational operating policies.”)
(See Brugere, col.2, lines 40-41: “In some embodiments, the ML model is a Bayesian optimization model.”)
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 should be directed to Examiner Ayal Sharon, whose telephone number is (571) 272-5614, and fax number is (571) 273-1794. The Examiner can normally be reached from Monday to Friday between 9 AM and 6 PM. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, SPE Christine Behncke can be reached at (571) 272-8103 or at christine.behncke@uspto.gov. The fax number for the organization where this application or proceeding is assigned is 571-273-8300.
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Sincerely,
/Ayal I. Sharon/
Examiner, Art Unit 3695
May 27, 2026
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