Detailed Action
Acknowledgements
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This action is in reply to the Amendment filed on October 6, 2025.
Claims 1-20 are pending.
Claims 1-20 are examined.
This Office Action is given Paper No. 20251120 for references purposes only.
Claim Rejections - 35 USC § 112b
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 1-12 are 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 which the inventor or a joint inventor, or for pre-AIA the applicant regards as the invention.
These claims are vague and indefinite because they include purely functional limitations without corresponding structure. Specifically, the specification does not clearly link or associate structure(s) for these limitations:
“a requesting entity transmitting… data” in claims 1 and 9;
“a score generator combining… score” in claims 1 and 9;
“a response module receiving… entity” in claims 1 and 9;
“a combination module further determining… score” in claims 4 and 10;
“the combination module further determining… score” in claim 7;
“the combination module further receiving… result” in claim 8;
“the combination model further determining… result” in claim 12.
Please see Claim Interpretation below.
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 a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Step 2A Prong 1: The claims recite an abstract idea of rejecting or approving transactions based on training model data, which is a certain method of organizing human activity (e.g. fundamental economic principles or practices including hedging, insurance, mitigating risk; commercial or legal interactions including agreements in the form of contracts, legal obligations, advertising, marketing or sales activities or behaviors, business relations; managing personal behavior or relationships or interactions between people including social activities, teaching, and following rules or instructions).
Claim 1, representative of claims 9 and 13, includes the following limitations:
A first model trained on relevant data including a first set of features, which include one or more dominant features, the first model receiving the transaction request data and producing a first initial fraud result;
A second model trained on the relevant data including a second set of features, which exclude the one or more dominant features, the second model receiving the transaction request data and producing a second initial fraud result;
Combining the first and second initial fraud results to generate a final fraud score;
Rejecting or allowing the transaction request based on the final fraud score.
Step 2A Prong 2: The claim limitations recite the following additional elements that are beyond the judicial exception:
Transmitting a transaction request including transaction request data.
These additional elements are not indicative of integration into a practical application because:
They add insignificant extra-solution activity to the judicial exception. Note that “extra-solution activity” can be understood as activities incidental to the primary process or product that are merely a nominal or tangential addition to the claim. Extra-solution activity can include both pre-solution and post-solution activity. An example of pre-solution activity is a step of gathering data for use in a claimed process. An example of post-solution activity is an element that is not integrated into the claim as whole. See MPEP 2106.05(g).
Step 2B: The claim limitations do not recite additional elements, or an ordered combination of additional elements, that are sufficient to amount to significantly more than the judicial exception.
As discussed with respect to step 2A prong 2 above, the additional element is extra solution activity that does not integrate a judicial exception into a practical application at step 2A or provide an inventive concept at step 2B.
According to the 2019 PEG, a conclusion that an additional element is insignificant extra solution activity under step 2A should be re-evaluated at step 2B. The limitation “transmitting a transaction request including transaction request data” is re-evaluated to determine whether it constitutes well-understood, routine, and conventional activity in the field. The “transmitting of data” is well-understood, routine, and conventional in the field. See Intellectual Ventures v. Symantec, 838 F.3d 1307, 1321 and MPEP 2106.05(d). Thus, a conclusion that the limitation “transmitting a transaction request including transaction request data” is well-understood, routine, and conventional is supported under Berkheimer.
Therefore, when considering all the additional claim elements both individually and as an ordered combination, Examiner finds that the claim does not amount to significantly more than the exception.
The dependent claims fail to cure this deficiency and are rejected accordingly.
Claim 2 recites the first and second modeling technologies are the same, which is merely describing data and further defining the abstract idea.
Claim 3 recites the first and second modeling technologies are different, which is merely describing data and further defining the abstract idea.
Claim 4 recites determining a first weight and second weight to apply and then combining the weighted first result and weighted second result, which is insignificant extra-solution activity (e.g. selecting a particular data source or type of data to be manipulated). See Electric Power Group, and MPEP 2106.05(g).
Claim 5 recites combining the first and second fraud results, which is insignificant extra-solution activity (e.g. mere data gathering). See CyberSource v. Retail Decisions, Inc., 654 F.3d 1366, 1375, and MPEP 2106.05(g).
Claim 6 recites the model is based on a boosted tree technology, which is merely describing data and further defining the abstract idea.
Claim 7 recites determining a first weight and second weight to apply and then combining the weighted first result and weighted second result, which is insignificant extra-solution activity (e.g. selecting a particular data source or type of data to be manipulated). See Electric Power Group, and MPEP 2106.05(g).
Claim 8 recites receiving one or more fields from the models and generating a final fraud score, which is insignificant extra-solution activity (e.g. selecting a particular data source or type of data to be manipulated). See Electric Power Group, and MPEP 2106.05(g).
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 status.
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, 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 factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-20 are rejected under 35 U.S.C. 103(a) as being unpatentable over Hu et al. (US 2023/0186164) in view of Ameisen et al. (US 2024/0095741).
Claims 1, 9, 13
Hu discloses:
a first model (first model, see [0013]) trained on relevant data (training data, see [0013]) and including a first set of features (first subset of features, see [0013]) which are relevant to detecting fraud in electronic payment card (card, see [0035, 0043]) transactions (payment transaction, see [0015, 0031]), the first set of features including one more dominant features (e.g. feature A, see figure 3), and the first model receiving the electronic payment card transaction request data (transaction request, see [0013]), evaluating the electronic payment card transaction request data for fraud, and producing a first initial fraud result (collective error for the first layer, see [0018]);
a second model (second model, see [0014]) trained on the relevant data and including a second set of features (second subset of features, see [0014]) which are relevant to detecting fraud in the electronic payment card transactions, the second set of features excluding the one or more dominant features (second subset of features is different from the first subset of features, see [0014]), and the second model receiving the electronic payment card transaction request data (transaction request, see [0014]), evaluating the electronic payment card transaction request data for fraud, and producing a second initial fraud result (collective error for the second layer, see [0020]);
a score generator combining the first and second initial fraud results to generate a final fraud score (collective error, see [0059]); and
a response module receiving the final fraud score and taking an action (response, see [0072]) based on the final fraud score, wherein the action includes rejecting (deny, see [0072]) or allowing (authorize, see [0072]) the electronic payment card transaction request from the requesting entity.
Hu does not explicitly disclose:
A requesting entity… data.
Ameisen teaches:
a requesting entity transmitting an electronic payment card transaction request (transactions, see [0037]) including an electronic payment card transaction request data (e.g. transaction identifiers, amount, time, see [0037]).
Hu discloses a first model, a second model, a score generator, and a response module. Hu does not explicitly disclose transmitting a transaction request including transaction data, but Ameisen does. It would have been obvious to one of ordinary skill in the art at the effective filing date of the invention to combine the enhanced gradient boosting tree for risk and fraud modeling of Hu with the transmitting a transaction request including transaction data of Ameisen because 1) a need exists for reducing the time required to build certain types of machine learning models without sacrificing their accuracy performance (see Hu [0004]); and 2) a need exists for deploying updated fraudulent transaction detection modules that improve fraud detection without disrupting merchant expectations (see Ameisen [0005]). Transmitting a transaction request including transaction data can be used for fraudulent transaction detection modules.
Claims 2, 9, 14
Furthermore, Hu discloses:
the first model is based on a first modeling technology and the second model is based on a second modeling technology which is the same (e.g. decision tree, see [0017]) as the first modeling technology.
Claims 3, 15
Furthermore, Hu discloses:
the first model is based on a first modeling technology and the second model is based on a second modeling technology which is different (e.g. regression model, a neural network, see [0017]) from the first modeling technology.
Claims 4, 10, 16
Furthermore, Ameisen teaches:
the score generator is a combination module further determining a first weight (e.g. w1) to apply to the first initial fraud result (initial fraud score, see [0029]) to produce a weighted first initial fraud result (adjusted weight score, see [0029]), determining a second weight (e.g. w2, see [0078]) to apply to the second initial fraud result (additional score, see [0078]) to produce a weighted second initial fraud result, and then combining the weighted first initial fraud result and the weighted second initial fraud result to generate the final fraud score (final fraud detection score, see [0078]).
Claims 5, 11, 17
Furthermore, Hu discloses:
the score generator is a combination model which is trained, receives the first (collective error for the first layer, see [0018]) and second (collective error for the second layer, see [0020]) initial fraud results, and combines the first and second initial fraud results to generate the final fraud score (collective error, see [0059]).
Claims 6, 11, 18
Furthermore, Hu discloses:
the combination model is based on a boosted tree modeling technology (gradient boosting tree, see [0012]).
Claims 7, 12, 19
Furthermore, Ameisen teaches:
determining a first weight (e.g. w1) to apply to the first initial fraud result (initial fraud score, see [0029]) to produce a weighted first initial fraud result (adjusted weight score, see [0029]), determining a second weight (e.g. w2, see [0078]) to apply to the second initial fraud result (additional score, see [0078]) to produce a weighted second initial fraud result, and then combining the weighted first initial fraud result and the weighted second initial fraud result to generate the final fraud score (final fraud detection score, see [0078]).
Claims 8, 12, 20
Furthermore, Ameisen teaches:
receiving one or more fields (e.g. threshold value, see [0078]) from the first and second models and generating the final fraud score (final fraud detection score, see [0078]) by combining the one or more fields, the weighted first initial fraud result, and the weighted second initial fraud result.
Response to Arguments
112 rejection
Applicant argues the rejection should be withdrawn.
Examiner disagrees. The claims invoke 112f because they recite a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. For example, “a score generator” is a generic placeholder. The language “combining the first and second initial fraud results to generate a final fraud score” performs a recited function. There is no recitation of structure in the claim limitation itself. As shown by the analysis below under Claim Interpretation, these claim limitations invoke 112f in system claims 1 and 9. However, these claim limitations are vague and indefinite (i.e. 112b rejection) because the specification does not clearly link or associate corresponding structure to these limitations. Applicant may either amend the claim limitations so they do not invoke 112f, or identify the corresponding structure for them.
101 arguments
Applicant argues that the claimed invention is directed toward a specific practical solution of improving accuracy of fraud detection for electronic payment card transactions. Specifically, Applicant argues that the claimed invention combines the results of multiple fraud detection models including a first model that considers dominant features and a second model that excludes the dominant features.
Examiner disagrees. The claims recite an abstract idea of rejecting or approving transactions based on training model data, which is a certain method of organizing human activity. The abstract idea includes training two models on relevant data sets, combining the two models, and then rejecting or allowing the request based on a final fraud score. Having the two models use two different data sets (i.e. one with dominant features and one without dominant features) is a business solution, and not a technical solution.
103 arguments
Applicant argues that Hu is directed to multiple independent models whereas the claimed invention uses a single layer of models that are dependent.
Examiner disagrees with this assessment. The claim limitations do not recite a single layer of models that are dependent upon each other. The claims simply recite a first model trained on a first set of features including dominant features, and a second model trained on a second set of features that exclude the dominant features. Hu discloses a first model (first model, see [0013]) trained on relevant data (training data, see [0013]) and including a first set of features (first subset of features, see [0013]). Hu also discloses a second model (second model, see [0014]) trained on the relevant data and including a second set of features (second subset of features, see [0014]) that exclude the dominant features (second subset of features is different from the first subset of features, see [0014]).
Claim Interpretation
The prior art made of record and not relied upon is considered pertinent to Applicant's disclosure (see attached form PTO-892).
Afzal (US 2023/0137734) discloses systems and methods for improved detection of network attacks.
112f analysis
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitations use a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitations are:
“a requesting entity transmitting… data” in claims 1 and 9;
“a score generator combining… score” in claims 1 and 9;
“a response module receiving… entity” in claims 1 and 9;
“a combination module further determining… score” in claims 4 and 10;
“the combination module further determining… score” in claim 7;
“the combination module further receiving… result” in claim 8;
“the combination model further determining… result” in claim 12.
Because these claim limitations are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, they are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have these limitations interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitations to avoid them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitations recite sufficient structure to perform the claimed function so as to avoid them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim limitation “a requesting entity transmitting a transaction request including a transaction request data” has been interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because it uses a generic placeholder “a requesting entity” coupled with functional language “transmitting a transaction request including a transaction request data” without reciting sufficient structure to achieve the function. Furthermore, the generic placeholder is not preceded by a structural modifier. The remaining limitations listed above have a similar analysis.
Since the claim limitation(s) invokes 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, claims 1-12 have been interpreted to cover the corresponding structure described in the specification that achieves the claimed function, and equivalents thereof.
If applicant wishes to provide further explanation or dispute the examiner’s interpretation of the corresponding structure, applicant must identify the corresponding structure with reference to the specification by page and line number, and to the drawing, if any, by reference characters in response to this Office action.
If applicant does not intend to have the claim limitations treated under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may amend the claims so that they will clearly not invoke 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, or present a sufficient showing that the claims recite sufficient structure, material, or acts for performing the claimed function to preclude application of 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
For more information, see MPEP § 2173 et seq. and Supplementary Examination Guidelines for Determining Compliance With 35 U.S.C. 112 and for Treatment of Related Issues in Patent Applications, 76 FR 7162, 7167 (Feb. 9, 2011).
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry of a general nature or relating to the status of this application or concerning this communication or earlier communications from Examiner should be directed to Chrystina Zelaskiewicz whose telephone number is 571-270-3940. Examiner can normally be reached on Monday-Friday, 9:30am-5:00pm. If attempts to reach the examiner by telephone are unsuccessful, the Examiner’s supervisor, Neha Patel can be reached at 571-270-1492.
Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://portal.uspto.gov/external/portal/pair <http://pair-direct.uspto.gov>. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866.217.9197 (toll-free).
/CHRYSTINA E ZELASKIEWICZ/Primary Examiner, Art Unit 3699
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