DETAILED ACTION
Acknowledgements
This action is in response to Applicant’s filing on Apr. 15, 2026, and is made Non-Final. This action is being examined by James H. Miller, who is in the eastern time zone (EST), and who can be reached by email at James.Miller1@uspto.gov or by telephone at (469) 295-9082.
Interviews
Interviews are “indispensable to advance the prosecution of a patent application.” MPEP § 713. Accordingly, the following Examiner’s guidance and suggested workflow maximizes this benefit to Applicant by: (1) avoiding back and forth telephone calls for scheduling, (2) permitting Examiner out-of-office notifications to the Applicant when sending the agenda, and (3) permitting real-time document collaboration and screen sharing.
Interviews are available by telephone or, preferably, by video conferencing using the USPTO’s web-based collaboration platform. Applicants are strongly encouraged to schedule via the USPTO Automated Interview Request (AIR) portal at http://www.uspto.gov/interviewpractice. If an interview is needed more quickly than permitted by the AIR scheduling tool, note this in the AIR remarks for consideration. The Examiner routinely considers such urgent requests when practicable.
An agenda submitted when filing the AIR is strongly encouraged, because Examiners use agendas when determining whether to grant an interview. The AIR has character limits, so send the agenda contemporaneously to James.Miller1@uspto.gov and reference the AIR.
After-Final Interviews Requests are granted only at the Examiner’s discretion and only if disposal or clarification for appeal may be accomplished with only nominal further consideration. MPEP § 713.09. An advance agenda explaining how the interview advances prosecution—e.g., through targeted arguments, identified Examiner error, or proposed claim amendments—is strongly suggested.
For GRANTED requests, expect an email within two (2) business days confirming a date/time slot and collaboration tool access instructions. For DENIED requests, the record will include an explanation for the denial.
The examiner is generally available for interviews, Monday through Friday, 10:00 a.m. to 4:00 p.m. ET.
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 .
Claim Status
The status of claims is as follows:
Claims 1–20 remain pending and examined with Claims 1 and 11 in independent form.
Claims 1, and 11 are presently amended.
No Claims are presently cancelled or added.
Response to Amendment
Applicant's Amendment has been reviewed against Applicant’s Specification filed Jan. 13, 2023, [“Applicant’s Specification”] and accepted for examination.
Response to Arguments
35 U.S.C. § 101 Argument
Applicant argues the claim is not directed to a mental process or other abstract idea because transmitting, routing, authorizing, and completing a transaction across multiple computing systems cannot, as a practical matter, be performed by a human. Applicant’s Reply at 1–2. Applicant further argues that the claim integrates an exception into a practical application because “the anomaly determination and account selection control[s] how the transaction is processed across a financial system including routing the transaction to a computing device associated with a selected account, and directing anomalous transactions to a designated financial account while preventing routing to other accounts,” citing “[t]he December 4, 2025 memorandum from Director Squires, discussing In re Desjardins. Applicant’s Reply at 2. Applicant further argues the amended claim recites an inventive concept in the ordered combination of Claim 1 limitations that require “anomaly detection using prior transaction information across multiple accounts, selection of a designated financial account based on that determination, and execution of a transaction-processing pipeline in which the selected account dictates routing, authorization, and completion across multiple computing systems,” which is not generic but “defines a specific operational sequence that governs how financial transactions are processed and authorized.” Applicant’s Reply at 3.
Examiner respectfully disagrees. As described in the specification, the amended claims remain directed to "selecting an optimal financial account for a financial transaction" (Spec. Abstract) using a "transaction-dependent financial account selection system" (Spec. ¶ 14) that "automatically selects a financial account from one of the linked financial accounts in an optimum manner e.g. to maximize reward points and/or minimize interest payments." Spec. ¶ 14. The additional elements in Claim 11, such as the "unsupervised machine learning model implemented within the payment intermediary computer system," the "financial system," and the "computing device associated with the selected financial account," are implemented on generic computer components, including "one or more server computers or other computing devices that execute programmatic instructions" (Spec. ¶¶ 19, 25) and a conventional "computer system 300" with standard processor, memory, storage, and network interface. Spec. ¶¶ 61–64, 69. The specification explains that an "unsupervised machine learning model may be used to detect transaction anomalies" and that "[i]n some cases, detection of a transaction anomaly will result in a selection of a particular financial account that is identified as being designated for anomaly transactions" (Spec. ¶ 44), which reflects automated application of financial decision rules rather than an improvement in computer technology itself.
Regarding Applicant's newly added "transmitting," "routing," "determining a payment authorization result," and "transmitting the payment authorization result" limitations, these recite generic, conventional payment-processing operations described in the specification at a results-oriented level of generality. The specification describes the routing as ordinary message passing among a processing computing device, a financial computing device, and a banking computing device, in which "[t]he financial devices to which the transaction information and financial account information is sent is dictated by the financial account that is selected," and in which the banking computing device "determines the result of payment authorization and sends the results of the authorization to POS System 104 to complete the financial transaction." Spec. ¶ 26. The specification does not disclose any non-conventional routing mechanism, network architecture, or improvement to the way the computers transmit or authorize data. Rather, the specification describes the components performing their ordinary functions. Spec. ¶¶ 19, 25, 26, 55, 60–64. Because the specification teaches the devices to which information is routed are “dictated by the financial account that is selected” (Spec. ¶ 26), the recited routing reflects the result of the abstract account selection decision rather than a technical improvement in how information is processed through the system and "directing" anomalous transactions to one account while "prevent[ing] routing" to others is merely the expected consequence of having selected that account. Accordingly, the post-selection limitations amount to insignificant extra solution activity that applies the judicial exception using generic computer components and do not integrate the exception into a practical application or supply an inventive concept. MPEP §§ 2106.05(a), 2106.05(f).
To the extent Applicant relies on the December 4, 2025, Squires Memorandum and In re Desjardins, those authorities require that the claim reflect a change to system operation or architecture with sufficient specificity. Here, the amended claim recites only the desired result (i.e., anomalies routed to a designated account) without reciting how any technical improvement is achieved, and the specification confirms the underlying operations are conventional. Spec. ¶¶ 26, 55, 60, 61. Accordingly, even though the recited operations may not be practically performed by a human at the same scale or speed, that distinction does not confer eligibility because merely invoking generic computer technology to perform abstract idea faster or to scale is not a technical improvement. The recited operations amount to using generic computer technology to carry out the abstract idea of collecting, analyzing, and classifying financial transaction and account information to select a funding account and then route and authorize a payment in the conventional manner, and they do not integrate the judicial exception into a practical application or provide an inventive concept under Step 2B. Additionally, the specification never frames the invention solving a technical problem but rather as solving a business problem (consumers picking the optimal card). Spec. ¶¶ 4, 5. The computer is used as a tool. MPEP §§ 2106.05(a), (f).
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., an abstract idea) without significantly more.
Analysis
Step 1: Claims 1–20 are directed to a statutory category. Claim 1 recites “a computer-implemented method” and is therefore, directed to the statutory category of “a process.” Claim 11 recites “one or more non-transitory computer-readable media” and is therefore, directed to the statutory category of “an article of manufacture.”
Representative Claim
Claim 11 is representative [“Rep. Claim 11”] of the subject matter under examination and recites, in part, emphasis added by Examiner to identify limitations with normal font indicating the abstract idea exception, bold limitations indicating additional elements. Each limitation is identified by a letter for later use as a shorthand notation in referencing/describing each limitation. Portions of the claim use italics to identify intended use limitations1 and underline, as needed, in further describing the abstract idea exception:
[A] 11. One or more non-transitory computer-readable media storing instructions for selecting a financial account for a financial transaction of a consumer which, when executed by one or more processors, cause:
[B] receiving, by a payment intermediary computer system, transaction information of a financial transaction involving a multi-account payment card associated with a unique multi-account payment card identification (ID);
[C] accessing financial account information of a plurality of financial accounts linked to the multi-account payment card ID, wherein each financial account is associated with distinct transaction-based criteria; wherein each financial account of the plurality of financial accounts is associated with a distinct payment source; wherein the plurality of financial accounts includes a first financial account designated for use with anomaly transactions;
[D] inputting, into an unsupervised machine learning model implemented within the payment intermediary computer system, (i) one or more financial transactions associated with each of the plurality of financial accounts, including for each transaction a transaction amount, merchant identifier, and transaction category; and (ii) transaction information for the financial transaction;
[E] determining, by the unsupervised machine learning model, that the financial transaction is an anomaly transaction by detecting that the financial transaction differs from the one or more financial transactions associated with the plurality of financial accounts based on a comparison between the transaction amount of the financial transaction and a threshold value derived from a mean amount for the one or more financial transactions, or based on a deviation in transaction category patterns; wherein an anomaly transaction is a financial transaction of the consumer that is determined by the unsupervised machine learning model to be unlike the previous financial transactions performed by the consumer using the plurality of financial accounts;
[F] in response to determining that the financial transaction is an anomaly transaction, classifying the anomaly transaction into an anomaly category and selecting the first financial account to fund the anomaly transaction; and
[G] causing, by the payment intermediary computer system, the selected financial account information to be transmitted to a financial system:
[H] routing, by the financial system, the financial transaction to a computing device associated with the selected financial account, the routing being performed to direct anomalous transactions to the first financial account designated for anomaly transactions and to prevent routing of the anomalous transactions to other financial accounts of the plurality of financial accounts:
[I] determining, by the computing device, a payment authorization result for the financial transaction: and
[J] transmitting, by the computing device, the payment authorization result to complete the financial transaction.
Step 2A, Prong One: Rep. Claim 11 recites “selecting a financial account for a financial transaction of a consumer” in the preamble (Limitation A), and “transmitting … the payment authorization result to complete the financial transaction” in Limitation J, which recites a fundamental economic practice and commercial interaction under certain methods of organizing human activity because selecting a funding account for, and completing, a consumer’s financial transaction recites “commercial or legal interactions, including … sales activities or behaviors, and business relations” between two people. MPEP § 2106.04(a)(2)(II)(B). Limitations B–J are the required steps and received data inputs required to “complete the financial transaction” and therefore, recite the same exception. Id.
Alternatively2, Limitations B–F, as drafted, recite the abstract idea exception of mental processes that under the broadest reasonable interpretation, cover performance in the human mind or with pen and paper, but for the recitation of the generic computer components indicated in bold. MPEP § 2106.04(a)(2)(III). Newly added Limitations G, H, I, and J are addressed as additional elements under Step 2A, Prong Two, infra.
Claims recite a mental process when they contain limitations that can practically be performed in the human mind, including for example, observations, evaluations, judgments, and opinions. Examples of claims that recite mental processes include:
• a claim to "collecting information, analyzing it, and displaying certain results of the collection and analysis," where the data analysis steps are recited at a high level of generality such that they could practically be performed in the human mind, Electric Power Group v. Alstom, S.A., 830 F.3d 1350, 1353-54, 119 USPQ2d 1739, 1741-42 (Fed. Cir. 2016);
. . .
• a claim to collecting and comparing known information (claim 1), which are steps that can be practically performed in the human mind, Classen Immunotherapies, Inc. v. Biogen IDEC, 659 F.3d 1057, 1067, 100 USPQ2d 1492, 1500 (Fed. Cir. 2011).
MPEP § 2106.04(a)(2)(III)(A). For example, but for the generic computer components claim language, here, Limitations B–F, recite collecting information (Limitations B, C, D) and analyzing it (Limitations E, F), where the data analysis steps are recited at a high level of generality such that they could practically be performed in the human mind. For example, Limitations E, is a mental processes that is practically performed in the human mind or with pen and paper because it requires mere “observation, evaluation, judgment, and/or opinion” to determine that the financial transaction is an anomaly transaction unlike the previous financial transactions performed by the consumer, by detecting that the financial transaction differs from the one or more financial transactions associated with the plurality of financial accounts [1] based on a comparison between the transaction amount of the financial transaction and a threshold value derived from a mean amount for the one or more financial transactions, or [2] based on a deviation in transaction category patterns. The specification confirms this is a simple arithmetic comparison, teaching that “if a calculated mean (i.e. average) amount for financial transactions of the plurality of financial accounts is $100 and a threshold value is set to $300, any financial transaction with an amount greater than $400 is detected as a transaction anomaly.” Spec. ¶ 46. Collecting and comparing known information (i.e., the transaction amount of the financial transaction and a threshold value derived from a mean amount for the one or more financial transactions) are steps that can be practically performed in the human mind under Classen. Deriving the threshold value from a mean amount for comparison covers any solution with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, which is so broad as to encompass mental processes. Alternatively, the “or” permits either [1] or [2] to detect the difference (or determine an anomaly transaction). The “based on a deviation in transaction category patterns” is also very broad and is also a mental process. A deviation in transaction category patterns covers any solution with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, which is so broad as to encompass mental processes. Limitation F is a mental process that is practically performed in the human mind or with pen and paper because it requires mere “observation, evaluation, judgment, and/or opinion” to, in response to Limitation E, classify anomaly-related metric data associated with the financial transaction based on the determination that the financial transaction is an anomaly transaction and select the first account to fund the anomaly transaction. Classifying the anomaly transaction into an anomaly category and selecting the first financial account covers any solution with no restriction on how the result is accomplished, which is so broad as to encompass mental processes. Regarding the unsupervised machine learning model, Applicant’s Specification teaches it may be a “k-means clustering” algorithm. Spec. ¶ 44. Examiner relies on NPL Leskovec’s clustering examples (pp. 268, 463, 464) as evidence that the recited model performs a mathematical/clustering analysis within the mental processes and mathematical concepts groupings. To the extent the model is characterized as “neural networks,” the Examiner relies on it as a mathematical concept rather that as an assertion that a neural network is itself practically performed in the human mind. See, Leskovec, Jure, Anand Rajaraman, and Jeffrey David Ullman. "Mining of Massive Datasets." (2019) (“NPL Leskovec”), p. 268 (Example 7.8), p. 463 (explaining equivalency of unsupervised learning and clustering), p. 464 (Example 12.1) (cited herein on PTO-892). “The use of a physical aid (e.g., pencil and paper or a slide rule) to help perform a mental step (e.g., a mathematical calculation) does not negate the mental nature of the limitation, but simply accounts for variations in memory capacity from one person to another” or a multi-step mental process. MPEP § 2106.04(a)(2)(III)(B).
If a claim limitation under BRI, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract idea exception. MPEP § 2106.04(a)(2)(III). Accordingly, the pending claims recite the combination of these abstract idea exceptions.
Step 2A, Prong Two: Rep. Claim 11 does not contain additional elements that integrate the abstract idea exception into a practical application because the additional elements are mere instructions to apply the abstract idea exception. MPEP § 2106.05(f). The additional elements are limited to the computer components and indicated in bold, supra. The additional elements are: one or more non-transitory computer-readable media storing instructions, one or more processors, an unsupervised machine learning model, a payment intermediary computer system; a financial system; and a computing device associated with the selected financial account. Limitations, G, H, I, and J
Regarding the one or more non-transitory computer-readable media storing instructions, one or more processors, an unsupervised machine learning model, a payment intermediary computer system; a financial system, Applicant’s Specification does not otherwise describe them or describes them using exemplary language as a general-purpose computer, as a part of a general-purpose computer, or as any known and exemplary (generic) computer component known in the prior art. Thus, Applicant takes the position that such hardware/software is so well known to those of ordinary skill in the art that no explanation is needed under 35 U.S.C. § 112(a). Lindemann Maschinenfabrik GMBH v. Am. Hoist & Derrick Co., 730 F.2d 1452, 1463 (Fed. Cir. 1984) (citing In re Meyers, 410 F.2d 420, 424 (CCPA 1969) (“[T]he specification need not disclose what is well known in the art”). E.g., Spec. ¶¶ 60, 66 (known and generic (exemplary) media), ¶¶ 60, 68 (known and generic (exemplary) instructions), ¶ 60, 61 (“general purpose microprocessor”), ¶¶ 19, 25 (“one or more server computers or other computing devices that could execute programmatic instructions”); ¶ 26 (financial computing device and banking computer device performing conventional relay and authorization); ¶¶ 62, 63, 64 (known and generic (exemplary) payment intermediary computer system); ¶ 60 (“any other device that incorporates hardwired and/or program logic to implement the techniques”); ¶ 66 (“any non-transitory media that store data and/or instructions that cause a machine to operate in a specific fashion”); ¶ 17 (“Financial account information may include any information relating to a financial account.”); ¶ 18 (“The term "transaction information", as used herein, refers to any information about the specific transaction for which the TDFAS system is selectin a financial account.”); ¶¶ 21, 32 (“Transaction information may include any information obtained from the POS 104”); ¶ 24 (“Payment information may include any information obtained from a multi-account payment card that was used to initiate a transaction”); ¶ 66 (“any other magnetic data storage medium … any other optical data storage medium, any physical medium with patterns of holes, … any other memory chip or cartridge.”); ¶ 44 (any known and generic (exemplary) unsupervised machine learning model). The generic processor, here, appears to perform calculations (functions) that are programmed by software. Spec. ¶ 60. This is a computer doing what it is designed to do—performing directions it is given to follow.
Regarding the unsupervised machine learning model, Applicant’s Specification discloses it is a generic, off-the-shelf, algorithm known in the prior art to a PHOSITA at the time of filing. Spec. ¶¶ 43, 44, 45, 46. The claims merely recite using the model to receive input and to produce an output, a function of any model, without disclosing any details for how the model produces the output. The model itself is created outside of the claimed invention and can be created in known way. Id. The improvement as argued by Applicant is in the ability to detect an anomaly with the unsupervised ML model and to route the resulting transaction to a designated account, but again, any model may be used. Id. (identifying nine exemplary and known unsupervised ML models). This describes a solution merely at the level of a “generic black box” for determining an “anomaly transaction” and reads neatly on “use a computer” to do it. MPEP § 2106.05(f). Thus, using any known model in its ordinary way is not a practical application.
Regarding Limitations, G, H, I, and J, the “transmitting,” “routing,” “determining a payment authorization result,” and “transmitting the payment authorization result” steps are additional elements that amount to no more that insignificant extra-solution activity and mere instructions to apply the exception. MPEP §§ 2106.05(f), (g). The specification confirms these are conventional payment processing functions. The selected account “dictate[s]” where the information is sent, the banking computer device “determines the result of payment authorization and sends the results … to … complete the financial transaction,” and the components are generic. Spec. ¶¶ 26, 60, 61. Reciting that routing “direct[s] anomalous transactions to the first financial account designated for anomaly transactions and to prevent routing of the anomalous transactions to other financial accounts of the plurality of financial accounts” recites the result of the abstract selection, not an improvement in the computer or network functionality and does not impose a meaningful limit on the exception. MPEP §§ 2106.05(a), (f).
Limitation A describes the generic computer/computer components performing the steps of the claimed invention, Limitations B–J, which represent the abstract idea exception itself together with the generic additional elements applying it. Performing the steps of the abstract idea itself simply adds a generic computer after the fact to an abstract idea exception, MPEP 2106.05(f)(2), or generically recites an effect of the judicial exception. MPEP 2106.05(f)(3).
Therefore, the claim as a whole, looking at the additional elements individually and in combination, are no more than mere instructions to apply the exception using generic computer components and is not a practical application. MPEP § 2106.05(f). The additional elements do not integrate the abstract idea exception into a practical application because they do not impose any meaningful limits on the abstract idea exception. Accordingly, Rep. Claim 11 is directed to an abstract idea.
Rep. Claim 11 is not substantially different than Independent Claim 1 and includes all the limitations of Rep. Claim 11. Independent Claim 1 contains no additional elements. Therefore, Independent Claim 1 is also directed to the same abstract idea.
The claims do not provide an inventive concept.
Step 2B: Rep. Claim 11 fails Step 2B because the claim as whole, looking at the additional elements individually and in combination, are not sufficient to amount to significantly more than the recited judicial exception. As discussed with respect to Step 2A, Prong Two, the additional elements in the claim amount to no more than mere instructions to apply the exception using a generic computer and/or generic computer components. MPEP § 2106.05(f). The same analysis applies here in Step 2B. Mere instructions to apply an exception using a generic computer and/or generic computer components cannot provide an inventive concept. MPEP § 2106.05(I).
The additional elements, taken individually and in combination, do not result in the claim, as a whole, amounting to significantly more than the identified judicial exception.
The pending claims in their combination of additional elements is not inventive. First, the claims are directed to an abstract idea. Second, each additional element represents a currently available generic computer technology, used in the way in which it is commonly used (individually generic). Third, the newly added routing and authorization limitations recite conventional payment-processing operations performed by generic components in their ordinary manner. Last, Applicant’s Specification discloses that the combination of additional elements is not inventive. Spec., ¶ 28 (steps/functions may be performed in any order); ¶¶ 17, 18, 21, 22, 23, 24, 26, 32, 44, 60, 61, 62, 63, 64, 66, 68 (known and generic (exemplary) computer equipment as explained and cited supra.)
Thus, Examiner finds the additional elements of Rep. Claim 11 are elements that have been recognized as well-understood, routine, and conventional (“WURC”) activity in the particular field of this invention based on Applicant’s own disclosure3. Spec. ¶¶ 17, 18, 21, 22, 23, 24, 26, 28, 32, 44, 60, 61, 62, 63, 64, 66, 68; MPEP § 2106.05(d). Specifically, Applicant’s Specification discloses the recited additional elements are limited to generic computer components. These elements do no more than “apply” the recited abstract idea(s) on a known computer (e.g., processor) and computer-related components (e.g., media). Further, Leskovec, Jure, Anand Rajaraman, and Jeffrey David Ullman. "Mining of Massive Datasets." (2019) (“NPL Leskovec”) (cited on PTO-892) is prior art and additional evidence that unsupervised machine learning algorithms were well-known and merely operate on the generic components. The Examiner also finds the functions of receiving, storing, transmitting, routing, and processing (e.g., performing mathematical operations on) data, described in Limitations B–J are all normal functions of a generic computer and of a conventional payment processing system.
There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Thus, taken alone, the additional elements do not amount to significantly more than the above-identified judicial exception (the abstract idea). Looking at the additional elements in combination adds nothing that is not already present when looking at the elements individually. Their collective functions merely provide conventional computer implementation of the abstract idea at a high level of generality. Thus, Rep. Claim 11 does not provide an inventive concept.
Rep. Claim 11 is not substantially different than Independent Claim 1 and includes all the limitations of Rep. Claim 11. Independent Claim 1 contains no additional limitations that alters this analysis. Therefore, Independent Claim 1 also do not recite an inventive concept.
Dependent Claims Not Significantly More
The dependent claims have been given the full two-part analysis including analyzing the additional limitations both individually and in combination. The dependent claim(s) when analyzed both individually and in combination are also held to be patent ineligible under 35 U.S.C. § 101. Dependent claims are dependent on Independent Claims and include all the limitations of the Independent Claims. Therefore, all dependent claims recite the same Abstract Idea. Dependent claims do not contain additional elements that integrate the abstract idea exception into a practical application or recite an inventive concept because the additional elements: (1) are mere instructions to apply the abstract idea exception; and/or (2) further limit the abstract idea exception of the Independent Claims. The abstract idea itself cannot provide the inventive concept or practical application. MPEP §§ 2106.05(I), 2106.04(d)(III).
Dependent Claims 2, 3, 6, 12, 13, and 16 all recite “wherein” clauses that further limits the abstract idea of the Independent Claims but contains the additional elements of: a first financial computing device/computing device (Claims 2, 3, 12, 13); a second financial computing device (Claims 2 and 12), a banking computing device/computing device (Claims 3 and 13), a database (Claims 6 and 16). For the same reasoning as explained for the “payment intermediary computer system” in Step 2A, Prong Two, supra, these additional elements do not provide a practical application or inventive concept because it is amounts to mere instructions to apply the exception with a computer. MPEP § 2106.05(f). Spec. ¶¶ 17, 18, 21, 24, 28, 32, 44, 60, 61, 62, 63, 64, 66, 68; ¶¶ 24, 30, Fig. 1 (recitation of “database” by name only). An inventive concept or practical application cannot be furnished by an abstract idea exception itself. MPEP §§ 2106.05(I), 2106.04(d)(III).
Dependent Claims 4, 5, 9, 10, 14, 15, 19, and 20 all recite “wherein” clauses or limitations that further limit the abstract idea of the Independent Claims and contain no additional elements. An inventive concept or practical application cannot be furnished by an abstract idea exception itself. MPEP §§ 2106.05(I), 2106.04(d)(III).
Dependent Claims 7, 8, 17, and 18 recite additional limitations that form part of the same abstract idea exception as recited in Independent Claims and contain the additional element of: an interface (Claims 7 and 17) and a digital receipt (Claims 8 and 18). For the same reason as analyzed for the “payment intermediary computer system” in Step 2A, Prong Two, supra, these additional elements do not provide a practical application or inventive concept because it is amounts to mere instructions to apply the exception with a computer. MPEP § 2106.05(f). The interface is part of a generic computer. Spec. ¶ 69. An inventive concept or practical application cannot be furnished by an abstract idea exception itself. MPEP §§ 2106.05(I), 2106.04(d)(III).
Conclusion
Claims1–20 are therefore drawn to ineligible subject matter as they are directed to an abstract idea without significantly more. The analysis above applies to all statutory categories of invention. As such, the presentment of Rep. Claim 11 otherwise styled as another statutory category is subject to the same analysis.
Examiner Statement of Prior Art—No Prior Art Rejections
Based on the prior art search results, the prior art of record fails to anticipate or render obvious the claimed subject matter of the instant application. While some individual features of Claims 1–20 may be shown in the prior art of record—no known reference, alone or in combination, would render obvious the claimed invention of the invention of Claims 1–20.
The prior art most closely resembling the applicant’s claimed invention are:
Novis (U.S. Pat. Pub. No. 2020/0202330) is pertinent because it discloses systems and methods for optimizing financial transactions of a user by using a multi-use account system associated with a plurality of financial accounts belonging to a user and an optimization model 130 configured to detect transaction patterns. Novis does not disclose “determining, by the unsupervised machine learning model, that the financial transaction is an anomaly transaction by detecting that the financial transaction differs from the one or more financial transactions associated with the plurality of financial accounts based on a comparison between the transaction amount of the financial transaction and a threshold value derived from a mean amount for the one or more financial transactions, or based on a deviation in transaction category patterns; wherein an anomaly transaction is a financial transaction of the consumer that is determined by the unsupervised machine learning model to be unlike the previous financial transactions performed by the consumer using the plurality of financial accounts.”
Dietrich et al. (U.S. Pat. No. 10,482,464) is pertinent because it discloses Identification of anomalous transaction attributes in realtime with adaptive threshold tuning is provided by determining a financial transaction is unlike the previous financial transaction; identifying a transaction that diverges from historical spending patterns based on one or more thresholds derived from prior financial transaction data; and identifying the financial transaction as an anomaly and selecting the account based on account selection criteria specific to anomalous activity. Dietrich does not disclose “determining, by the unsupervised machine learning model, that the financial transaction is an anomaly transaction by detecting that the financial transaction differs from the one or more financial transactions associated with the plurality of financial accounts based on a comparison between the transaction amount of the financial transaction and a threshold value derived from a mean amount for the one or more financial transactions, or based on a deviation in transaction category patterns; wherein an anomaly transaction is a financial transaction of the consumer that is determined by the unsupervised machine learning model to be unlike the previous financial transactions performed by the consumer using the plurality of financial accounts.”
FOR: Int. Pat. Pub. No. WO 2013/019995 A1 is pertinent because it discloses a fraud analytic system and method applied to a financial transaction device, such as a card or a mobile communication device (hereafter, simply "mobile device"), that is used as access to one or more funding accounts to execute a financial transaction. Fraud detection can benefit within a specific scenario, i.e. use of a specific funding account, if usage patterns are within normal variances associated with the other funding accounts, and if the selection of the specific funding account is normal for this specific type of transaction. FOR does not disclose “determining, by the unsupervised machine learning model, that the financial transaction is an anomaly transaction by detecting that the financial transaction differs from the one or more financial transactions associated with the plurality of financial accounts based on a comparison between the transaction amount of the financial transaction and a threshold value derived from a mean amount for the one or more financial transactions, or based on a deviation in transaction category patterns; wherein an anomaly transaction is a financial transaction of the consumer that is determined by the unsupervised machine learning model to be unlike the previous financial transactions performed by the consumer using the plurality of financial accounts.”
NPL: Federated Optimization for Financial Transaction Management, 2019 is pertinent because it discloses systems and methods for reviewing all an individual’s expenses, payment options, and all the associated implications, and then presents the individual with the optimal payment method for a single or group of expense(s). Thus, the system automates the dynamic selection of an optimal payment mode without human intervention via a virtual brokerage layer and inspection mechanism. NPL does not disclose “determining, by the unsupervised machine learning model, that the financial transaction is an anomaly transaction by detecting that the financial transaction differs from the one or more financial transactions associated with the plurality of financial accounts based on a comparison between the transaction amount of the financial transaction and a threshold value derived from a mean amount for the one or more financial transactions, or based on a deviation in transaction category patterns; wherein an anomaly transaction is a financial transaction of the consumer that is determined by the unsupervised machine learning model to be unlike the previous financial transactions performed by the consumer using the plurality of financial accounts.”
Conclusion
THIS ACTION IS MADE FINAL. 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 concerning this communication or earlier communications from the examiner should be directed to JAMES H MILLER whose telephone number is (469)295-9082. The examiner can normally be reached M-F: 10- 4 PM (EST).
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/JAMES H MILLER/Primary Examiner, Art Unit 3694
1 Statements of intended use fail to limit the scope of the claim under BRI. MPEP § 2103(I)(C).
2 “It should be noted that these groupings are not mutually exclusive, i.e., some claims recite limitations that fall within more than one grouping or sub-grouping. … Accordingly, examiners should identify at least one abstract idea grouping, but preferably identify all groupings to the extent possible, if a claim limitation(s) is determined to fall within multiple groupings and proceed with the analysis in Step 2A Prong Two.” MPEP § 2106.04(a).
3 See Changes in Examination Procedure Pertaining to Subject Matter Eligibility, Recent Subject Matter Eligibility Decision (Berkheimer v. HP, Inc.), 3-4, https://www.uspto.gov/sites/default/files/documents/memo-berkheimer-20180419.PDF (April, 18, 2018) (That additional elements are well-understood, routine, or conventional may be supported by various forms of evidence, including "[a] citation to an express statement in the specification or to a statement made by an applicant during prosecution that demonstrates the well-understood, routine, conventional nature of the additional element(s).").
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