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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 3/2/2026 has been entered.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 4/8/2026 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Status
The claims filed 3/2/2026 have been entered.
Claims 1-6, 8-16, and 18-22 are pending.
Claims 1, 3, 8, 11, 13, and 18 are currently amended.
Claims 9, 19, 21, and 22 are previously presented.
Claims 2, 4-6, 10, 12, 14-16, and 20 are original.
Claims 1 and 11 are independent.
Response to Arguments
35 U.S.C. 101 Rejections
Step 2A Prong 1
Applicant’s arguments regarding the rejection of claims 1-6, 8-16, and 18-22 as being directed to an abstract idea without significantly more have been considered but are not persuasive. The arguments are addressed to the extent they apply to the current rejection.
Regarding Step 2A Prong 1 of the subject matter eligibility framework, Applicant argues that claim 1 does not recite a fundamental economic practice. More specifically, Applicant argues that the claims do not recite any subject matter that is related to hedging, insurance, or mitigating risk.
The argument is not persuasive. The claims recite the abstract idea of providing financial service options to a user, including determining financial services options and providing a list including at least one ATM. While the enumerated grouping of “Certain Methods of Organizing Human Activity” are not to be expanded beyond the enumerated sub-groupings of “fundamental economic principles or practices”, “commercial or legal interactions”, and “managing personal behavior or relationships or interactions between people”, the subgrouping of “fundamental economic principles or practices” is not limited to merely hedging, insurance, and mitigating risk. Per MPEP 2106.04(a)(2), other examples of “fundamental economic principles or practices" include:
i. mitigating settlement risk, Alice Corp. v. CLS Bank,573 U.S. 208, 218, 110 USPQ2d 1976, 1982 (2014);
ii. rules for conducting a wagering game, In re Smith, 815 F.3d 816, 818-19, 118 USPQ2d 1245, 1247 (Fed. Cir. 2016);
iii. financial instruments that are designed to protect against the risk of investing in financial instruments, In re Chorna, 656 Fed. App'x 1016, 1021 (Fed. Cir. 2016) (non-precedential);
iv. offer-based price optimization, OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1362–63, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015);
v. local processing of payments for remotely purchased goods, Inventor Holdings, LLC v. Bed Bath Beyond, 876 F.3d 1372, 1378-79, 125 USPQ2d 1019, 1023 (Fed. Cir. 2017);
vi. using a marking affixed to the outside of a mail object to communicate information about the mail object, i.e., the sender, recipient, and contents of the mail object, Secured Mail Solutions LLC v. Universal Wilde, Inc., 873 F.3d 905, 911, 124 USPQ2d 1502, 1506 (Fed. Cir. 2017); and
vii. placing an order based on displayed market information, Trading Technologies Int’l, Inc. v. IBG LLC, 921 F.3d 1084, 1092, 2019 USPQ2d 138290 (Fed. Cir. 2019)
Applicant further argues that the claims do not recite commercial or legal interactions because they do not recite contracts, legal obligations, advertising, marketing or sales activities or behaviors, and business relations.
The argument is not persuasive. The claimed invention facilitates location of financial service providers (ATMs), which is a commercial interaction of providing information to aid in conducting a financial transaction. Here, providing a list of ATM services and locations falls under marketing or sales activities.
Applicant further argues that the claims do not recite an abstract idea because it recites limitations drawn to the training and use of a language model.
The argument is not persuasive. The recitation of generic computer components in a claim does not necessarily preclude that claim from reciting an abstract idea under Step 2A Prong 1. The limitations drawn to using the computing processor in conjunction with a language model are not identified as part of the abstract idea and are an additional element given due consideration in Step 2A Prong 2.
Applicant further argues that claims as a whole are not directed to a judicial exception under Step 2A and thus are eligible at Pathway B.
The argument is not persuasive. Step 2A is a two-prong inquiry, in which examiners determine in Prong One whether a claim recites a judicial exception, and if so, then determine in Prong Two if the recited judicial exception is integrated into a practical application of that exception. Together, these prongs represent the first part of the Alice/Mayo test, which determines whether a claim is directed to a judicial exception. For the above reasons, the claims recite a judicial exception under Prong One. As such, the analysis proceeds to Prong 2.
Step 2A Prong 2
Regarding Step 2A Prong 2 of the subject matter eligibility framework, Applicant argues that the claims as a whole integrate the judicial exception into a practical application of the exception. More specifically, Applicant argues that the claims as a whole, including additional elements drawn to the training and use of a language model/classification engine to identify appropriate interbank networks, provide an improvement to the functioning of ATM-related technologies.
The argument is not persuasive. The training and use of a language model is recited at a high level of generality in a manner which does not convey a technological improvement to one of ordinary skill in the art. The specification does not describe the language model or classification engine at a level of technical detail which would convey a technological improvement to language models/classification engines or any other technology. As such, the additional element amounts to mere use of a computer as a tool to perform the abstract idea which includes identifying the appropriate bank network. It is important to note that a general purpose computer that applies a judicial exception, such as an abstract idea, by use of ordinary computer functions does not qualify as a particular machine. Ultramercial, Inc. v. Hulu, LLC, 772 F.3d 709, 716-17, 112 USPQ2d 1750, 1755-56 (Fed. Cir. 2014). See also TLI Communications LLC v. AV Automotive LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (mere recitation of concrete or tangible components is not an inventive concept); Eon Corp. IP Holdings LLC v. AT&T Mobility LLC, 785 F.3d 616, 623, 114 USPQ2d 1711, 1715 (Fed. Cir. 2015) (noting that Alappat’s rationale that an otherwise ineligible algorithm or software could be made patent-eligible by merely adding a generic computer to the claim was superseded by the Supreme Court’s Bilski and Alice Corp. decisions). Merely adding a generic computer, generic computer components, or a programmed computer to perform generic computer functions does not automatically overcome an eligibility rejection. Alice Corp. Pty. Ltd. v. CLS Bank Int’l, 573 U.S. 208, 223-24, 110 USPQ2d 1976, 1983-84 (2014). See In re Alappat, 33 F.3d 1526, 1545, 31 USPQ2d 1545, 1558 (Fed. Cir. 1994); In re Bilski, 545 F.3d 943, 88 USPQ2d 1385 (Fed. Cir. 2008). Furthermore, looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide generic computer implementation.
Step 2B
Regarding Step 2B of the subject matter eligibility framework, Applicant argues that the claims amount to significantly more than the identified abstract idea because the claims amount to more than merely applying a general purpose computer. Applicant argues that the claims are meaningfully limited because they provide a particular, practical application.
The argument is not persuasive for similar reasons as discussed with regards to Step 2A Prong 2, namely that the claims are not found to recite a technological improvement because the trained language model/classification engine/interbank network and other additional elements are recited at a high level of generality in a manner which does not convey a technological improvement to one of ordinary skill in the art.
35 U.S.C. 103 Rejections
Applicant’s arguments with regards to the prior rejections under 35 U.S.C. 103 have been considered but are moot in view of the new grounds of rejection necessitated by the current amendment.
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 1-6, 8-16, and 18-22 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1
Claims 1-6, 8-16, and 18-22 are directed to systems or methods, and thus fall within the statutory categories of invention. (Step 1: YES).
Step 2A - Prong 1
The Examiner has identified independent system claim 1 as the claim that represents the claimed invention for analysis and is similar to independent method claim 11. Claim 1 recites the limitations of:
1. A system for facilitating automated teller machine (ATM) services for a user using machine learning, comprising:
at least one processor; and
at least one non-transitory computer-readable medium containing instructions that, when executed by the at least one processor, cause the at least one processor to perform operations comprising:
training a language model to classify an input as associated with a particular interbank network based on a training dataset comprising data associated with a plurality of banks and interbank networks;
receiving, from a user device, a request comprising at least one constraint for a desired transaction, the at least one constraint comprising language;
analyzing, via the trained language model, the language in the at least one constraint of the request;
based on the analysis, determining at least one ATM that satisfies the at least one constraint of the request, by:
determining, using a classification engine of the trained language model, with which interbank network the request is associated; and
providing, to the user device, a response specific to the interbank network associated with the request, the response comprising financial services options;
providing, to the user device, a list including the at least one ATM that satisfies the at least one constraint of the request;
receiving, from the user device, a selection of an ATM from the list; and
communicating, with at least one interbank network, the selection of the ATM from the list.
These limitations, under their broadest reasonable interpretation, cover performance of the limitation as “Certain Methods of Organizing Human Activity”.
The claim limitations delineated in bold above recite a fundamental economic practice, as they set forth or describe providing financial service options to a user. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation as a fundamental economic practice, then it falls within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas.
The claim limitations delineated in bold above also recite commercial or legal interactions, as they set forth or describe providing financial service options to a user. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation as commercial or legal interactions, then it falls within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas.
Accordingly, the claim recites an abstract idea. The limitations are considered together as a single abstract idea for Step 2A Prong 2 and Step 2B.
The processor and computer-readable medium in claim 1 is just applying generic computer components to the recited abstract limitations. The recitation of generic computer components in a claim does not necessarily preclude that claim from reciting an abstract idea. Independent claim 10 is also abstract for similar reasons. (Step 2A-Prong 1: YES. The claims recite an abstract idea)
Step 2A - Prong 2
This judicial exception is not integrated into a practical application. In particular, the claims recite the additional elements of:
Claim 1: at least one processor; at least one non-transitory computer-readable medium (in conjunction with a language model/classification engine and in communication with a user device)
Claim 10: receiving data from a user device; analyzing language via a language model; communicating with an interbank network
The computer hardware/software is/are recited at a high-level of generality (i.e., as a generic processor performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer component.
With regards to the limitations drawn to machine learning (preamble), the natural language model, and the classification engine, the claim only recites the idea of a solution or outcome and fails to recite how the solution to the problem is accomplished. Furthermore, these elements are described at a high level of generality in Applicant’s specification without any meaningful detail about its structure or configuration (see e.g., para. 0045). These limitations merely invoke the additional element as a tool to perform the abstract idea. As demonstrated by the specification, the claimed invention does not improve machine learning itself, but merely describes the features at a high level of generality as an implementation tool for performing the abstract idea. Here, the disclosure does not provide sufficient detail such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement to the functioning of the computer or to any other technology or technical field. MPEP 2106.04(d)(1). Thus, even considering this limitation, the use of the processor still merely amounts to adding the words “apply it” (or an equivalent) with the judicial exception. MPEP 2106.05(f).
Furthermore, the recitation of “using machine learning” (preamble) and “using a classification engine” merely indicates a field of use or technological environment in which the judicial exception is performed. This type of limitation merely confines the use of the abstract idea to a particular technological environment (machine learning/language models) and thus fails to provide a practical application. MPEP 2106.05(h).
Accordingly, these additional elements, when considered separately and as an ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea and are at a high level of generality. Therefore, claims 1 and 10 are directed to an abstract idea without a practical application. (Step 2A-Prong 2: NO. The additional claimed elements are not integrated into a practical application)
Step 2B
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, when considered separately and as an ordered combination, they do not add significantly more (also known as an “inventive concept”) to the exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a computer hardware amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. See Applicant’s specification para. [0032] about implementation using general purpose or special purpose computing devices and MPEP 2106.05(f) where applying a computer as a tool is not indicative of significantly. Accordingly, these additional elements, do not change the outcome of the analysis, when considered separately and as an ordered combination. Thus, claims 1 and 10 are not patent eligible. (Step 2B: NO. The claims do not provide significantly more)
Dependent Claims
Dependent claims 2-6, 8-9, 11-16, and 18-22 further define the abstract idea that is present in their respective independent claims 1 and 10 and thus correspond to “Certain Methods of Organizing Human Activity” and hence are abstract for the reasons presented above. The dependent claims 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, the dependent claims are directed to an abstract idea without significantly more.
Thus, claims 1-6, 8-16, and 18-22 are not patent-eligible.
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 (i.e., changing from AIA to pre-AIA ) 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.
Claims 1-5, 8-9, 11-15, 18-19, and 21-22 are rejected under 35 U.S.C. 103 as being unpatentable over Benkreira (US 2021/0304166 A1) in view of Kumar (US 2022/0101310 A1), further in view of Rodrigues (US 2018/0341934 A1).
Regarding claims 1 and 11, Benkreira discloses a system and associated method for facilitating automated teller machine (ATM) services for a user using machine learning, comprising:
at least one processor (see para. 0018); and
at least one non-transitory computer-readable medium containing instructions that, when executed by the at least one processor, cause the at least one processor to perform operations (see para. 0018) comprising:
receiving, from a user device, a request comprising at least one constraint for a desired transaction, the at least one constraint comprising language (see para. 0057, Figs. 6A-6B);
analyzing, via a trained language model, the language in the at least one constraint of the request (see para. 0049, 0057, 0084, Figs. 6A-6B);
based on the analysis, determining at least one ATM that satisfies the at least one constraint of the request by (see para. 0049, 0057, 0084, Figs. 6A-6B);
determining, using a classification engine of the trained language model stored in one or more memories of one or more computing devices, with which interbank network the request is associated (see para. 0049, 0057, 0084, Figs. 6A-6B, wherein filtering to show only fee-free ATMs necessarily involves determining the user’s eligible interbank network(s)); and
providing, to the user device, a response specific to the interbank network associated with the request, the response comprising financial services options (see para. 0049, 0057, 0084, Figs. 6A-6B);
providing, to the user device, a list including the at least one ATM that satisfies the at least one constraint of the request (see para. 0049, 0057, 0084, Figs. 6A-6B);
Benkreira does not explicitly disclose, but Kumar teaches training a language model to classify an input as associated with a particular interbank network based on a training dataset comprising data associated with a plurality of banks and interbank networks (see para. 0070-0073).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system and method of Benkreira to include the features taught by Kumar to determine the interbank network with the lowest transaction cost (see para. 0075).
Benkreira does not explicitly disclose, but Rodrigues teaches:
receiving, from the user device, a selection of an ATM from the list (see para. 0064-0065); and
communicating, with at least one interbank network, the selection of the ATM from the list (see para. 0064-0065).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system and method of Benkreira to include the features taught by Rodrigues to allow a customer to perform a withdrawal query to determine whether a desired withdrawal amount can be withdrawn (see Rodrigues, para. 0065).
Regarding claims 2 and 12, Benkreira discloses wherein the at least one constraint of the request comprises at least one of: a bank, the bank associated with a user; a location; a total amount of currency; or a breakdown of the total amount of currency by denomination (see para. 0049, 0057, 0084, Figs. 6A-6B).
Regarding claims 3 and 13, Benkreira discloses wherein the location is determined by at least one of: a postal code; or location data associated with the user device’s location (see para. 0049, 0057, 0084, Figs. 6A-6B; para. 0018-0022).
Regarding claims 4 and 14, Benkreira discloses wherein analyzing the language comprises: sending, to at least one machine-learning model, the language contained in the request; and receiving, from the at least one machine-learning model, an assessment of the language (see para. 0049, 0057, 0084, Figs. 6A-6B).
Regarding claims 5 and 15, Benkreira discloses wherein the language in the at least one constraint of the request comprises free form text (see para. 0049, 0057, 0084, Figs. 6A-6B).
Regarding claims 8 and 18, Benkreira discloses wherein the language model training comprises providing, to a classification engine stored in one or more memories of one or more computing devices, a training dataset, the training dataset tailored to a particular domain or application to optimize the language model (see Benkreira, para. 0049, 0084).
Regarding claims 9 and 19, Benkreira discloses wherein the financial services options comprise at least one of: withdraw funds from an account; PIN services; block/hotlist card; re-issue card; deposit funds into the account; bill payment; or transfer funds between accounts (see para. 0049, 0057, 0084, Figs. 6A-6B, para. 0051, 0066).
Regarding claims 21 and 22, Benkreira discloses wherein determining the at least one ATM that satisfies the at least one constraint of the request include: applying a first filter based on location; and applying a second filter to identify non-operational ATMs (see para. 0049, 0057, 0084, Figs. 6A-6B; para. 0018-0022).
Claims 6 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Benkreira (US 2021/0304166 A1) in view of Kumar (US 2022/0101310 A1), further in view of Rodrigues (US 2018/0341934 A1), further in view of Applicant admission of prior art.
Regarding claims 6 and 16, the combination as set forth with regards to the base claim teaches wherein the language in the at least one constraint of the request comprises text but does not explicitly disclose spoken language.
Applicant admission of prior art teaches it was old and well known before the effective filing date of the claimed invention to dictate text to a mobile device. Applicant did not traverse the Official Notice taken with regards to the feature in the prior Office action. As such, the feature is treated as admitted prior art.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system/method of Benkreira further to include the feature, thus making the constraint spoken language.
The modification would have merely been the application of a known technique to a known device/method ready for improvement to yield predictable results. One of ordinary skill in the art would have recognized that applying the known technique would have yielded predictable results and resulted in an improved system/method.
Claims 10 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Benkreira (US 2021/0304166 A1) in view of Kumar (US 2022/0101310 A1), further in view of Rodrigues (US 2018/0341934 A1), further in view of Phillips ‘421 (US 2019/0147421 A1).
Regarding claims 10 and 20, the combination set forth with regards to the base claim teaches wherein determining the at least one ATM that satisfies at least one constraint of the request comprises: commanding the at least one interbank network associated with the request to query associated ATMs for data; receiving the data; storing the data in a data structure; and creating the list based on the data stored in the data structure, each element of the list comprising: a unique alphanumeric identification associated with each ATM; and an indication associated with the ATM (see Benkreira para. 0049, 0057, 0084, Figs. 6A-6B; Rodrigues, para. 0064-0065).
Benkreira does not explicitly disclose, but Phillips ‘421 teaches calculating a score for each ATM, the score calculated based how closely the ATM matches the at least one constraint of the request; ranking the ATMs by the score (see abstract).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system/method of Benkreira to include the features taught by Phillips ‘421.
One of ordinary skill in the art would have been motivated to make the modification to provide an ATM recommendation platform that intelligently selects an ATM device (see Phillips ‘421, para. 00012).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Brown (US 2015/0186156 A1) discloses techniques and architectures for implementing a team of virtual assistants. The team may include multiple virtual assistants that are configured with different characteristics, such as different functionality, base language models, levels of training, visual appearances, personalities, and so on. The characteristics of the virtual assistants may be configured by trainers, end-users, and/or a virtual assistant service. The virtual assistants may be presented to end-users in conversation user interfaces to perform different tasks for the users in a conversational manner. The different virtual assistants may adapt to different contexts. The virtual assistants may additionally, or alternatively, interact with each other to carry out tasks for the users, which may be illustrated in conversation user interfaces.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ERIC T WONG whose telephone number is (571)270-3405. The examiner can normally be reached 9am-5pm M-F.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Michael W Anderson can be reached at 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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/ERIC T WONG/Primary Examiner, Art Unit 3693
ERIC WONG
Primary Examiner
Art Unit 3693
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