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 09/30/2025.
Claims 1-20 are currently pending and have been examined.
This action is made Non-Final.
Examiner’s 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.
Examiner’s Note
There are no prior art rejections at this time. However, Examiner respectfully notes that based on Applicant’s clarification of the 35 U.S.C. 112(b) rejections of Claims 1-20, prior art rejection(s) may be applied in future examination of the claims.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 09/30/2025 was filed before the mailing date of a first Office Action on the merits. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Drawings
New corrected drawings in compliance with 37 CFR 1.121(d) are required in this application because FIG. 7 of the drawings are illegible and do not comply with line uniformity, density definition requirement and the use of shading standards put forth in 37 CFR 1.84 (l) and (m):
(l) All drawings must be made by a process which will give them satisfactory reproduction characteristics. Every line, number, and letter must be durable, clean, black (except for color drawings), sufficiently dense and dark, and uniformly thick and well-defined. The weight of all lines and letters must be heavy enough to permit adequate reproduction. This requirement applies to all lines however fine, to shading, and to lines representing cut surfaces in sectional views. Lines and strokes of different thicknesses may be used in the same drawing where different thicknesses have a different meaning.
(m) Shading. The use of shading in views is encouraged if it aids in understanding the invention and if it does not reduce legibility. Shading is used to indicate the surface or shape of spherical, cylindrical, and conical elements of an object. Flat parts may also be lightly shaded. Such shading is preferred in the case of parts shown in perspective, but not for cross sections. See paragraph (h)(3) of this section. Spaced lines for shading are preferred. These lines must be thin, as few in number as practicable, and they must contrast with the rest of the drawings. As a substitute for shading, heavy lines on the shade side of objects can be used except where they superimpose on each other or obscure reference characters. Light should come from the upper left corner at an angle of 45°. Surface delineations should preferably be shown by proper shading. Solid black shading areas are not permitted, except when used to represent bar graphs or color.
Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as "amended." If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either "Replacement Sheet" or "New Sheet" pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Applicant is advised to employ the services of a competent patent draftsperson outside the Office, as the U.S. Patent and Trademark Office no longer prepares new drawings.
The Examiner further notes that due to the grayscale conversion process inherent in the Office's electronic application filing system, elements of FIG. 7 are rendered partially illegible which interferes with providing a clear disclosure of the invention to the public. Specifically, the text in FIG. 7 is blurry and illegible.
Applicant may further refer to MPEP § 608.02 et seq. for further information regarding acceptability of drawings presented in a utility patent application.
Claim Objections
Claims 1–3, 5, 6, 7, 9, 13-15 16, 17, 18, 19, and 20 are objected to because of the following informalities:
Claims 1, 19, and 20 recite “one or more prediction task” in both the preamble and the body. This is grammatically incorrect. When the phrase “one or more” is used to modify a noun, the noun should be in the plural form. It appears there is a grammatical mistake. Each instance of “one or more prediction task” should read, “one or more prediction tasks.” Similarly, each instance of “each of the one or more prediction task” should read, “each of the one or more prediction tasks.” For compact examination purposes, Examiner interpreted the instances recited in Claims 1, 19, and 20 as “one or more prediction tasks” and “each of the one or more prediction tasks.” Appropriate corrections are required.
Claims 2, 3, 5, 7, 9, 16, and 17 inherit the same grammatical error from claim 1 by reciting “each of the one or more prediction task” or “the one or more prediction task.” It appears there is a grammatical mistake. Each instance should be corrected to “one or more prediction tasks” and “each of the one or more prediction tasks.” For compact examination purposes, Examiner interpreted the instances recited in Claims 2, 3, 5, 7, 9, 16, and 17 as “one or more prediction tasks” and “each of the one or more prediction tasks.” Appropriate corrections are required.
Claim 6 recites “predicting a risk of an account being fraudulently taken over, predicting a risk of mule fraud for an account, or the risk or likelihood of an account being used for money laundering, predicting that an application for a financial product is fraudulent, or predicting a fraudulent transaction on an account.” The list of alternatives is grammatically inconsistent. Certain list items begin with “predicting” while one item begins with “or the risk or likelihood” without a preceding verb “predicting.” Additionally, the use of “or” within the list makes it unclear which items are intended to be alternatives. The claim should be amended to present the alternatives in a consistent grammatical format with clear delineation between each alternative. For example, the claim could be amended to recite: “predicting fraud associated with a financial product comprises at least one of: (a) predicting a risk of an account being fraudulently taken over; (b) predicting a risk of mule fraud for an account; (c) predicting a risk or likelihood of an account being used for money laundering; (d) predicting that an application for a financial product is fraudulent; or (e) predicting a fraudulent transaction on an account.” For compact examination purposes, Examiner interpreted the instances recited in Claim 6 as “predicting fraud associated with a financial product comprises at least one of: (a) predicting a risk of an account being fraudulently taken over; (b) predicting a risk of mule fraud for an account; (c) predicting a risk or likelihood of an account being used for money laundering; (d) predicting that an application for a financial product is fraudulent; or (e) predicting a fraudulent transaction on an account.” Appropriate correction is required.
Claim 14 recites “the predetermined window being smaller that the historical time period.” The word “that” appears to be a typographical error and should read “than.” For compact examination purposes, Examiner interpreted the instances recited in Claim 14 as “the predetermined window being smaller than the historical time period.” Appropriate correction is required.
Claims 13 and 15 recite the limitation “a plurality of intermediate tokens.” “A plurality of intermediate tokens” is previously recited in independent Claim 1. It appears there is a typographical mistake since the specification only points to a single instance of a plurality of intermediate tokens. For compact examination purposes, Examiner interpreted the instances recited in Claims 13 and 15 as “the plurality of intermediate tokens.” Appropriate correction is required.
Claim 18 recites “a set of one or more intermediate token that represents that tabular dataset.” It appears there is a grammatical mistake. The noun “token” should be in the plural form when modified by “one or more.” This should read: one or more intermediate tokens. For compact examination purposes, Examiner interpreted the instances recited in Claim 18 as “a set of one or more intermediate tokens that represents that tabular dataset.” Appropriate correction is required.
Claim Rejections - 35 USC § 112
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.
Claims 1-20 are rejected under 35 U.S.C. 112(b), as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention.
Independent claims 1, 19, and 20 recite the limitations “process the plurality of tabular datasets using a hierarchical set of encoder machine learning models to generate a token that represents the plurality of tabular datasets, the hierarchical set of encoder machine learning models comprising a plurality of first layer encoder machine learning models configured to generate a plurality of intermediate tokens from the plurality of tabular datasets and a second layer encoder machine learning model configured to generate the token from the plurality of intermediate tokens” and “process the token using a predictor machine learning model to generate a predicted target for each of the one or more prediction task,” which are vague and confusing. Is the generating of the token further explaining and referring to the token that was initially generated, or the generating of another token, which is a different token than the one initially generated? The token recited in the limitations: “Generat[ing] the token from the plurality of intermediate tokens” and “process[ing] the token using a predictor machine learning model to generate a predicted target for each of the one or more prediction task” could be differently understood as the token initially recited in the “process the plurality of tabular datasets using a hierarchical set of encoder machine learning models to generate a token that represents the plurality of tabular datasets,” or a completely different token (a third token) from the initially recited generated token and intermediate token(s), by every person having ordinary skill in the art, and thus making the limitations vague and confusing. For the purposes of examination, the Examiner interpreted the limitations in Independent claims 1, 19, and 20 as “process the plurality of tabular datasets using a hierarchical set of encoder machine learning models to generate a first token that represents the plurality of tabular datasets, the hierarchical set of encoder machine learning models comprising a plurality of first layer encoder machine learning models configured to generate a plurality of intermediate tokens from the plurality of tabular datasets and a second layer encoder machine learning model configured to generate a third token from the plurality of intermediate tokens” and “process the third token using a predictor machine learning model to generate a predicted target for each of the one or more prediction task.” Clarification and appropriate correction are required.
Dependent claims 2-18 are rejected by their virtue of dependency on Independent claim 1. Thus, Claims 1-20 are rejected under 35 U.S.C. 112(b).
Additionally, Claim 2 is rejected under 35 U.S.C. § 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention. Claim 2 recites “each of the one or more prediction task comprises prediction of one of acquisition, fraud, attrition, delinquency, and action.” The term “action” renders the claim indefinite because a person of ordinary skill in the art would not be able to determine the metes and bounds of what constitutes a prediction of “action” as distinguished from the other enumerated prediction types (acquisition, fraud, attrition, delinquency). The term “action” is exceedingly broad. Virtually any prediction could be characterized as predicting an “action.” While the specification at paragraph [0104] describes various predictions that may fall under this category, including “future account actions such as, but not limited to recurring bill payment, e-bills etc.,” as well as predictions of ULOC utilization, HELOC utilization, credit limit decrease, cash flow management, balance transfer, account upgrade, account downgrade, pre-authorized payment, direct deposit, overdraft protection, savings account balance increase, mutual fund purchase, and RRSP contribution increase, the breadth and open-ended nature of these examples does not provide a clear and definite boundary for the term “action.” Specifically, a person of ordinary skill in the art would not be able to ascertain when a particular prediction qualifies as an “action” prediction as opposed to, for example, an “acquisition” prediction or an “attrition” prediction. There is no clear principle of demarcation between “action” and the other enumerated categories. For purposes of examination, the Examiner interpreted “action” to encompass any prediction of a customer behavior or account event that does not fall within the categories of acquisition, fraud, attrition, or delinquency. Clarification and appropriate correction are required.
Furthermore, Claims 14-15 are rejected under 35 U.S.C. § 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention. Claim 14 recites “a tabular dataset comprising a summary of activity for a financial account within each predetermined window in the historical time period, the predetermined window being smaller that the historical time period.” The claim first introduces “each predetermined window” which implies a plurality of predetermined windows, and then refers back to “the predetermined window” in the singular. It is unclear whether “the predetermined window” is intended to refer to each individual window of the plurality, to a single window size parameter that defines all of the windows, or to something else. This creates an ambiguity regarding the antecedent basis for “the predetermined window.” Additionally, as noted in the claim objections above, “that” should read “than.” For purposes of examination, the Examiner interpreted claim 14 to mean that the tabular dataset comprises a summary of activity for a financial account within each of a plurality of predetermined windows in the historical time period, wherein each predetermined window is smaller than the historical time period. Clarification and appropriate correction are required.
Claim 15 depends from claim 14 and is therefore also rejected under 35 U.S.C. § 112(b) by virtue of its dependency.
Hence, Examiner recommends Applicant make necessary amendments.
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea of processing datasets to generate a predicted target for a prediction task; without significantly more.
Examiner has identified claim 1 as the claim that represents the claimed invention presented in independent claims 1, 19, and 20.
Claim 1 is directed to a system which is one of the statutory categories of invention; (Step 1: YES); Claim 19 is directed to a method which is one of the statutory categories of invention (Step 1: YES); and Claim 20 is directed to a non-transitory computer readable medium which is one of the statutory categories of invention (Step 1: YES).
Claim 1 is directed to a system for performing one or more prediction task, the system comprising at least one processor configured to: receive a plurality of tabular datasets, each tabular dataset of the plurality of tabular datasets comprising data related to a same historical time period; process the plurality of tabular datasets using a hierarchical set of encoder machine learning models to generate a token that represents the plurality of tabular datasets, the hierarchical set of encoder machine learning models comprising a plurality of first layer encoder machine learning models configured to generate a plurality of intermediate tokens from the plurality of tabular datasets and a second layer encoder machine learning model configured to generate the token from the plurality of intermediate tokens; and process the token using a predictor machine learning model to generate a predicted target for each of the one or more prediction task. These limitations describe the abstract idea of processing datasets to generate a predicted target for a prediction task (with exception of the italicized and bolded terms above), which is mitigating the risk involved with acquisition, fraud, attrition, or delinquency by processing datasets to generate a predicted target for a prediction task; 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. Additionally, Claim 1 recites a series of steps that describe the abstract idea of processing datasets using a hierarchical set of models to generate a token; therefore, corresponding to a mathematical calculation, relationship, and/or equation. Hence, a mathematical calculation, relationship, and/or equation is a Mathematical Concept. The computer device limitations, e.g., a system, at least one processor, hierarchical set of encoder machine learning models, token, plurality of first layer encoder machine learning models, plurality of intermediate tokens, second layer encoder machine learning model, and predictor machine learning model, 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 system, at least one processor, hierarchical set of encoder machine learning models, token, plurality of first layer encoder machine learning models, plurality of intermediate tokens, second layer encoder machine learning model, and predictor machine learning model, 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. Merely invoking a system, hierarchical set of encoder machine learning models, token, plurality of first layer encoder machine learning models, plurality of intermediate tokens, second layer encoder machine learning model, and predictor machine learning model is similar to invoking software and software components. 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 system, at least one processor, hierarchical set of encoder machine learning models, token, plurality of first layer encoder machine learning models, plurality of intermediate tokens, second layer encoder machine learning model, and predictor machine learning model 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.
Similar arguments can be extended to the other independent claims, claims 19 and 20; and hence, claims 19 and 20 are rejected on similar grounds as claim 1.
Dependent Claims 2-18 are directed to a system, which perform steps that describe the abstract idea of processing datasets to generate a predicted target for a prediction task. Furthermore, dependent claims 13 and 15 is directed to a system, which preform the steps: “wherein the plurality of first layer encoder machine learning models comprises an encoder-only transformer configured to convert the tabular dataset comprising the transactions in the historical time period related to the financial product to a plurality of intermediate tokens;” and “wherein the plurality of first layer encoder machine learning models comprises a multi-layer perceptron neural network configured to convert the tabular dataset comprising the summary of activity for the financial account within each predetermined window in the historical time period to a plurality of intermediate tokens,” which is mitigating the risk involved with acquisition, fraud, attrition, delinquency by processing datasets to generate a predicted target for a prediction task; 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 processing of datasets to predict acquisition, fraud, attrition, delinquency of a financial product involved in banking and/or real estate lending transactions, which is commercial interaction. Therefore, a commercial interaction is also a Certain Methods of Organizing Human Activity. Additionally, Claims 2-18 recites a series of steps that describe the abstract idea of processing datasets using a hierarchical set of models to generate a token; therefore, corresponding to a mathematical calculation, relationship, and/or equation. Hence, a mathematical calculation, relationship, and/or equation is a Mathematical Concept. The system limitations, e.g., a system, at least one processor, hierarchical set of encoder machine learning models, token, plurality of first layer encoder machine learning models, plurality of intermediate tokens, second layer encoder machine learning model, predictor machine learning model, encoder-only transformer, and multi-layer perceptron neural network, do not necessarily restrict the claim from reciting an abstract idea. Thus, claims 2-18 are directed to an abstract idea. The additional limitations of a system, at least one processor, hierarchical set of encoder machine learning models, token, plurality of first layer encoder machine learning models, plurality of intermediate tokens, second layer encoder machine learning model, predictor machine learning model, encoder-only transformer, and multi-layer perceptron neural network 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. Merely invoking a system, hierarchical set of encoder machine learning models, token, plurality of first layer encoder machine learning models, plurality of intermediate tokens, second layer encoder machine learning model, predictor machine learning model, encoder-only transformer, and multi-layer perceptron neural network is similar to invoking software and software components. The presence of a generic computer arrangement is nothing more than to implement the claimed invention (MPEP 2106.05(f)). The computer network limitations are a field of use limitations (MPEP 2106.05(h)). 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 of a system, at least one processor, hierarchical set of encoder machine learning models, token, plurality of first layer encoder machine learning models, plurality of intermediate tokens, second layer encoder machine learning model, predictor machine learning model, encoder-only transformer, and multi-layer perceptron neural network 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 2-18 have further defined the abstract idea that is present in their respective independent claim 1; and thus, correspond to Certain Methods of Organizing Human Activity and/or Mathematical Concept, and hence are abstract in nature for the reason presented above. The dependent claims 2-18 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, dependent claims 2-18 are directed to an abstract idea without significantly more.
Thus, claims 1-20 are not patent-eligible.
Prior Art Rejections
There are no prior art rejections at this time. However, as discussed above in the Examiner’s Note, Examiner respectfully notes that based on Applicant’s clarification of the 35 U.S.C. 112(b) rejections of Claims 1-20, prior art rejection(s) may be applied in future examination of the claims.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure is the following:
Shraga (U.S. Patent Application Pub. No. US 2021/0342684 A1) “Method and system for table retrieval using multimodal deep co-learning with helper query-dependent and query-independent relevance labels”
Rawat (U.S. Patent Application Pub. No. US 2021/0357443 A1) “Methods and systems for generating textual summary from tabular data”
Chen (U.S. Patent Application Pub. No. US 2022/0121921 A1) “State-augmented reinforcement learning”
Karlsson (U.S. Patent Application Pub. No. US 2023/0092819 A1) “Systems and methods for determining cause of performance change using machine learning techniques”
Chandelier (U.S. Patent Application Pub. No. US 2024/0005203 A1) “Method of and system for adapting multiple trained machine learning models on unlabelled dataset”
Reyes (U.S. Patent Application Pub. No. US 2024/0127114 A1) “Method of and system for providing an aggregated machine learning model in a federated learning environment and determining relative contribution of local datasets thereto”
Rohwer (U.S. Patent Application Pub. No. US 2024/0211734 A1) “Hierarchical framing transformer for activity detection”
Jacob (U.S. Patent Application Pub. No. US 2024/0362036 A1) “Dynamic generation of user interface controls”
Sethi (U.S. Patent Application Pub. No. US 2024/0403369 A1) “Methods and systems for training artificial intelligence-based models using limited labeled data”
Rahman (U.S. Patent No. US 12,164,542 B1) “Systems and methods for synchronization of data”
Cheng (U.S. Patent No. US 12,205,292 B2) “Methods and systems for semantic segmentation of a point cloud”
Chowanski (U.S. Patent Application Pub. No. US 2025/0028852 A1) “Systems and methods for tokenization”
Tabatabaei (U.S. Patent Application Pub. No. US 2025/0077939 A1) “Systems and methods for computing fairness metrics in artificial intelligence and machine learning models”
Choudhary (U.S. Patent Application Pub. No. US 2025/0200608 A1) “Segment discovery and channel delivery”
D'Agostino (U.S. Patent Application Pub. No. US 2025/0245511 A1) “Computing systems and methods for data processing using a generic large language model and a secondary large language model configured for structured data”
Sohn (U.S. Patent Application Pub. No. US 2026/0057583 A1) “Visual prompt tuning for generative transfer learning”
Khuc (U.S. Patent Application Pub. No. US 2026/0134585A1) “One-step inference for prior model in text-to-image synthesis”
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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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, MICHAEL W. ANDERSON can be reached on 571-270-0508. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MOHAMMED H MUSTAFA/Examiner, Art Unit 3693
/ELIZABETH H ROSEN/Primary Examiner, Art Unit 3693
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