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 .
Acknowledgements
Applicant’s response filed March 11, 2026 is acknowledged.
Claims 1-16 are pending in the application.
Claim 15 remains withdrawn from consideration.
Claims 1-14 and 16 are examined below.
Examiner Request
Applicant is requested to indicate where in the specification there is support for amendments to claims should applicant amend. The purpose of this is to reduce potential 35 USC 112(a) or 35 USC 112, 1st paragraph issues that can arise when claims are amended without support in the specification. Examiner thanks applicant in advance. See also relevant portions of MPEP 2163.II.A:
With respect to newly added or amended claims, applicant should show support in the original disclosure for the new or amended claims. See, e.g., Hyatt v. Dudas, 492 F.3d 1365, 1370, n.4 (Fed. Cir. 2007) (citing MPEP § 2163.04 which provides that a "simple statement such as ‘applicant has not pointed out where the new (or amended) claim is supported, nor does there appear to be a written description of the claim limitation ‘___’ in the application as filed’ may be sufficient where the claim is a new or amended claim, the support for the limitation is not apparent, and applicant has not pointed out where the limitation is supported."); see also MPEP § 714.02 and § 2163.06 ("Applicant should ... specifically point out the support for any amendments made to the disclosure."); and MPEP § 2163.04 ("If applicant amends the claims and points out where and/or how the originally filed disclosure supports the amendment(s), and the examiner finds that the disclosure does not reasonably convey that the inventor had possession of the subject matter of the amendment at the time of the filing of the application, the examiner has the initial burden of presenting evidence or reasoning to explain why persons skilled in the art would not recognize in the disclosure a description of the invention defined by the claims.").
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 1-14 and 16 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to non-statutory subject matter.
Regarding claims 1-14 and 16, the claimed invention is directed to an abstract idea without significantly more. Representative claim 13 recites obtaining a plurality of models and financial transaction information about a customer to be analyzed, computing multiple analysis results by inputting the financial transaction information of the customer to be analyzed into each of the plurality of models respectively, wherein each of the plurality of models outputs one of the multiple analysis results, and outputting the analysis results, which constitutes a mental process. Accordingly, the claim recites an abstract idea. This judicial exception is not integrated into a practical application because the additional elements beyond the abstract idea simply link the abstract idea to a particular technological environment (machine learning in a secure computing environment). Because the abstract idea is not integrated into a practical application, claim 13 is “directed to” an abstract idea. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements identified above represent only well-understood, routine, and conventional technology (or placeholders for such) when compared with the court decisions listed in MPEP § 2106.05(d). Viewing the additional elements as a combination does not add anything further than the individual elements. Therefore, the additional elements in the claim are not sufficient to amount to an inventive concept. Because claim 13 is directed to an abstract idea and fails to recite an inventive concept, it is patent ineligible.
Independent claims 1 and 14 contain limitations similar to claim 13 and are therefore rejected using the same rationale.
The dependent claims when analyzed as a whole are held to be patent ineligible under 35 U.S.C. 101. The additional limitations added by these claims fail to either integrate the claims into a practical application or add an inventive concept, because they serve to further narrow the abstract idea without integrating it into a practical application (claims 2-6 and 8-12), add additional elements that simply further link to a particular technological environment (claim 7), amount to additional extrasolution activity (claims 3-6), and/or cannot be construed (claim 16). Viewing the additional elements of the dependent claims as a combination does not add anything further than the individual elements. Therefore, the dependent claims neither practically integrate the abstract idea nor constitute an inventive concept, and these claims are also rejected as patent ineligible.
Claim Rejections - 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd Paragraph
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 16 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter that the inventor or a joint inventor, or for pre-AIA the applicant regards as the invention.
Regarding claim 16, applicant’s recitation "output, in a comparable manner, the aggregated multiple analysis results and an analysis result of a model generated for the financial institution from which the financial transaction information of the customer to be analyzed was obtained” would have been unclear to a person having ordinary skill in the art. This recitation does not make sense, grammatically.
Claim Rejections - 35 USC § 103
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 statute.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The following is a quotation of 35 U.S.C. 103(a) (pre-AIA ) which forms the basis for all obviousness rejections set forth in this office action:
(a) A patent may not be obtained though the invention is not identically disclosed or described as set forth in section 102 of this title, if the differences between the subject matter sought to be patented and the prior art are such that the subject matter as a whole would have been obvious at the time the invention was made to a person having ordinary skill in the art to which said subject matter pertains. Patentability shall not be negatived by the manner in which the invention was made.
Claims 1, 2, 7-9, 13, 14, and 16, as understood by the examiner, are rejected under 35 U.S.C. 103 as being unpatentable over Govan (US 10,868,888 B1) in view of Badrinarayanan (US 2024/0250809 A1).
Govan discloses as follows:
Claim
Limitation
Govan
1,14
at least one memory configured to store instructions
"server 100 will include at some level one or more physical servers, at least one of the physical servers having one or more microprocessors and digital memory for, inter alia, storing instructions which, when executed by the processor, cause the servers to perform methods and operations described herein" C3 L47-52
1
at least one processor configured to execute the instructions to:
1,13,14
obtain a plurality of models, each of the plurality of models having been generated for a respective one of a plurality of financial institutions based on financial transaction information about customers held by the respective financial institution;obtain financial transaction information of a customer to be analyzed;compute multiple analysis results by inputting the financial transaction information of the customer to be analyzed into each of the plurality of models respectively ... wherein each of the plurality of models outputs one of the multiple analysis results
"data pipeline 200 feeds multiple analytic models 202 (e.g. models 202A, 202B et seq.) The outputs of analytic models 202 are fed to ranking and optimization component 204. Ranking and optimization component 204 generates output 206, which is conveyed to reporting component 208" C3 L65 - C4 L3"Event repository 324 contains actions associated with a user and/or resource. Information within repository 324 may include: a) user history, consisting of user interactions with resources; and b) user profile information containing observed and derived data about each user. Observed user data may include demographic information and/or technographic information (e.g. browser, OS, email address, etc.). Derived user data may include behavioral segments the user falls into or, in the case of missing observations, imputed demographic data. Thus, data associated with a user data is collectively stored within both people repository 320 and event repository 324.Events within repository 324, such as user interactions with resources, are stored having a schema, such as schema 400 illustrated in FIG. 4. Each Event 400 includes a user 410 with whom the event is associated (e.g. a UUID); an Event Type 420 (such as video play, web page view, item purchase, partial page scroll, rating, add to cart); a time and date 430 at which the event took place; and a resource identifier 440 indicating the resource with which the event is associated." C5 L15-34
1,13,14
output one or more analysis results based on the multiple analysis results
"Reporting component 208 can make output 206 available to other internal or external systems, such as one or more of third party systems 130" C4 L3-5
2
output the one or more analysis results of the plurality of models in a format in which it is not possible to specify which models, among the plurality of models, the one or more analysis results are obtained from
Govan allows the user to choose which model is being employed ("weighting factors may be determined intuitively, based on a user's beliefs as to which models are likely to be more appropriate for a particular analysis. For example, if a particular customer provided data streams having rich text data, but very limited behavioral data, the customer might deem a Text recommender to be more reliable than a behavioral model recommender" C10 L24-30), but Govan is silent regarding display of which model the analysis results are obtained from. Therefore, the examiner is interpreting Govan as not labelling the output by model. However, even if Govan did label the models, modifying Govan to remove the label would constitute a change in nonfunctional descriptive material that would not distinguish the invention from the prior art.
3
aggregate the multiple analysis results; and output the agregated multiple analysis results as the one or more analysis results
"Reporting component 208 can make output 206 available to other internal or external systems, such as one or more of third party systems 130" C4 L3-5
8
wherein each of the plurality of models is a model that analyzes a possibility that the customer purchases a financial product
"the probability that individuals will purchase item X after purchasing item Y"
9
wherein each of the plurality of models is a model that predicts a financial product that the customer is likely to purchase
"in order to predictive what a user is likely to do next based on the behavior of other users that are either similar or are in a related situation (e.g. after watching the movie ‘Conan Barbarian’, what is the next movie that the user will watch: ‘Terminator’ or another movie in the same setting or a movie from the same era?)."
16
output, in a comparable manner, the aggregated multiple analysis results and an analysis result of a model generated for the financial institution from which the financial transaction information of the customer to be analyzed was obtained
As detailed in the 112(b) rejection above, this limitation could not be construed, and, therefore, fails to distinguish from the prior art
Govan fails to explicitly disclose but Badrinarayanan teaches wherein models and financial transaction information are obtained in concealed format and that the computation is performed “while keeping the plurality of models and the financial transaction information in concealed form, through secure computation including at least one of homomorphic encryption, multi-party computation with secret sharing, or processing in a trusted execution environment isolated on hardware” (claim 1) and in particular that this is accomplished via secret sharing (claim 7): "Secure multi-party communication (MPC) can be used for transmitting data for training and/or evaluating machine learning models while retaining privacy of the data. Secure MPC can ensure that, during training, the only information leaked about the data may be the final model (or an encrypted version of the model). Further, during evaluation, the only information leaked can include the output label. One setting considered is where data owners (e.g., clients) secret share their data among multiple independent servers that perform training on the combined data or apply a (secret shared) pre-trained model to evaluate new data samples" ([0029]).
It would have been obvious to one having ordinary skill in the art at the time of the invention to modify Govan to include the secret sharing security of Badrinarayanan in order to achieve the predictable result of maintaining privacy of the customer’s data and the provider’s models.
Claims 3-6, as understood by the examiner, are rejected under 35 U.S.C. 103 as being unpatentable over Govan in view of Badrinarayanan and further in view of Henryson (US 11,790,296 B1).
Govan/Badrinarayanan fails to explicitly disclose but Henryson teaches:
Claim
Limitation
Henryson
3
aggregate the multiple analysis results; and output the agregated multiple analysis results as the one or more analysis results
See Fig. 7 and associated text
4
aggregate the multiple analysis results based on a number of models that obtain analysis results from which the same determination is derived
"If two or more of the models agree on a category score, the machine learning text model may determine that the category score is correct and output the category score accordingly."
5
output the agregated multiple analysis results based on a majority decision by the plurality of models
"If two or more of the models agree on a category score, the machine learning text model may determine that the category score is correct and output the category score accordingly."
6
output a number or a ratio of the plurality of models to a total number of models that analyzed the one or more analysis results ouptut
See Fig. 7 and associated text
It would have been obvious to one having ordinary skill in the art at the time of the invention to modify Govan/Badrinarayanan to include the aggregation and model comparison of Henryson in order to achieve the predictable result of allowing the user to better choose appropriate models to provide them with recommendations.
Claims 10-12, as understood by the examiner, are rejected under 35 U.S.C. 103 as being unpatentable over Govan/Badrinarayanan in view of applicant admitted prior art.
The below officially noticed facts are taken to be admitted prior art. The official notices were asserted by the examiner in the office action mailed December 11, 2025. Applicant did not adequately traverse these official notices in applicant's next response submitted March 11, 2026. Applicant did not state why the noticed facts are not considered to be common knowledge or well-known in the art. Therefore, the officially noticed facts are taken to be admitted prior art. See MPEP 2144.03.C.
Regarding claim 10, Govan/Badrinarayanan discloses as discussed above, but Govan/Badrinarayanan fails to explicitly disclose wherein each of the models is a model that predicts a customer predicted to purchase a financial product
However, the examiner takes official notice that it is old and well known in the art to using machine learning to predict a customer to purchase a product.
It would have been obvious to a person having ordinary skill in the art at the time of the invention to modify Govan/Badrinarayanan to include the customer prediction of examiner’s official notice because all the claimed elements/steps were known in the prior art and one skilled in the art could have combined the elements/steps as claimed by known methods with no change in their respective functions, and the combination would have yielded predictable results, such as increased sales, to one of ordinary skill in the art at the time of the invention.
Regarding claim 11, Govan/Badrinarayanan discloses as discussed above, but Govan/Badrinarayanan fails to explicitly disclose wherein each of the models is a model that analyzes whether a desired partner for M & A can be acquired, or analyzes a desired expected acquisition amount. However, the examiner takes official notice that it is old and well known in the art to predict prices using machine learning in order to optimize profits.
It would have been obvious to a person having ordinary skill in the art at the time of the invention to modify Govan/Badrinarayanan to include the price prediction of examiner’s official notice because all the claimed elements/steps were known in the prior art and one skilled in the art could have combined the elements/steps as claimed by known methods with no change in their respective functions, and the combination would have yielded predictable results, such as increased profits, to one of ordinary skill in the art at the time of the invention.
Regarding claim 12, Govan/Badrinarayanan discloses as discussed above, but Govan/Badrinarayanan fails to explicitly disclose wherein each of the models is a model that outputs credit information of the customer. However, the examiner takes official notice that it is old and well known in the art to make credit predictions regarding customers.
It would have been obvious to a person having ordinary skill in the art at the time of the invention to modify Govan/Badrinarayanan to include the credit prediction of examiner’s official notice because all the claimed elements/steps were known in the prior art and one skilled in the art could have combined the elements/steps as claimed by known methods with no change in their respective functions, and the combination would have yielded predictable results, such as increased sales, to one of ordinary skill in the art at the time of the invention.
Citation of Relevant Prior Art
All references listed on form PTO-892 are cited in their entirety. The following prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Banipal (US 2022/0188852 A1) uses multiple models to predict an optimal price.
Kursun (US 2020/0387602 A1) discloses a machine learning system including multiple models where the user can specify the percentage of models that must agree in order to produce an output ([0056]).
Bannae (US 12,073,937 B2) discloses a machine learning system that includes aggregation of output from different models (see at least Fig. 5).
Response to Amendments and Arguments
The examiner expresses his appreciation for applicant’s specific citations to the specification indicating where applicant believes support for the claim amendments can be found. The examiner's search for support for the claim amendments was not limited to these citations.
The 112(b) rejections are withdrawn in response to applicant’s amendment. Note, however, the new rejection above.
Regarding the 101 rejection, applicant argues that the amendment overcomes the rejection of record. The examiner respectfully disagrees. See the rejection above, modified in response to applicant’s amendment.
Regarding the prior art rejection, applicant argues that “none of the cited references teach or suggest analyzing a customer's financial transaction information using models from multiple financial institutions as is recited in the independent claims.” The examiner respectfully disagrees. Govan discloses this limitation as detailed above. Govan does not disclose that the models are from multiple financial institutions. However, this the provenance of data amounts at most to nonfunctional descriptive material, which fails to distinguish the claimed invention from the prior art.
Conclusion
Applicant's amendment necessitated the new grounds 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 mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JAMIE KUCAB whose telephone number is (571)270-3025. The examiner can normally be reached Monday through Friday, 9 a.m. to 4:30 p.m. ET. The examiner’s email address is Jamie.Kucab@USPTO.gov. See MPEP 502.03 regarding email communications. Following is the sample authorization for electronic communication provided in MPEP 502.03.II: “Recognizing that Internet communications are not secure, I hereby authorize the USPTO to communicate with the undersigned and practitioners in accordance with 37 CFR 1.33 and 37 CFR 1.34 concerning any subject matter of this application by video conferencing, instant messaging, or electronic mail. I understand that a copy of these communications will be made of record in the application file.” Without such an authorization in place, an examiner is unable to respond via email.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Neha Patel, can be reached at telephone number (571) 270-1492. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/JAMIE R KUCAB/Primary Examiner, Art Unit 3699
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