Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
This Non-Final Office action is in reply to amendments/arguments filed 1/7/26.
Claims 1, 7-9, 12-14 and 18 have been amended.
Claims 1-20 are pending.
Response to Arguments/Amendments
With respect to the 35 U.S.C. § 101 rejection, applicant states, “the claims do not recite any type of commercial or legal interaction, nor do they recite steps for managing personal behavior or relationships or interactions between people. Instead, the claims recite specific processes for detecting instances of anomalous payments in payment systems, through the use of both a "recurrent neural network" and an "unsupervised clustering function," as recited in amended independent claims 1, 14, and 18. Such operations cannot be considered a commercial or legal interaction because the claims do not involve any type of contract, agreement, or legal obligation. Moreover, the claims cannot be considered to recite managing personal behavior or relationships or interactions between people, because the claims do not recite any features relating to the management of behavior or relationships. As noted above, the claims are instead related to specific approaches for detecting anomalous payments using a "recurrent neural network" and an "unsupervised clustering function," as recited in amended independent claims 1, 14, and 18, which does not involve behavior or relationships”. Applicant’s arguments have been considered but are not persuasive. The claimed invention pertains to management of personal behavior or interactions between people according to rules and instruction to facilitate commercial or legal interactions for receiving a set of payments, categorizing each payment, determining that a user payment is anomalous and problematic, transmitting an alert and receiving a request to cancel or reverse the payment; hence directed to certain methods of organizing human activity groupings of abstract ideas. Applicant’s “computing system, recurrent neural network”, “intermediary device”, “alert”, “network interface”, “processor”, “memory” “electronic communication”, “call center device”, “user device” (which are merely standard computer technology and hardware/software components) – see ¶6, ¶14, ¶22, ¶84, ¶85 do no impose any meaningful limits on performing the abstract idea for receiving a set of payments, categorizing each payment, determining that a payment is anomalous and problematic, transmitting an alert and receiving a request to cancel or reverse the payment in any exceptional manner, and there is no evidence in the disclosure to suggest achieving an actual improvement in the computer functionality itself, or improvement in any specific computer technology other than utilizing ordinary computational tools to automate and perform the abstract idea recited above. Further, the additional elements in the dependent claims “call center device”, “user device”, “tracking device”, “mobile application”, “k-means clustering”, “hidden Markov model”, “electronic notification”, similarly provides a generic environment in which the claimed invention is performed an amounts to no more than applying the judicial exception noted above using generic computing components, and linking the use of the judicial exception to a computing environment. Moreover, the steps for “receiving a set of payments made from a first account to a second account, at least one of the first and second accounts being administered by the provider …wherein the set of payments comprises one or more payments by a user; …assigning each payment of the set of payments to one or more clusters previously generated via a plurality of historical payments; determining that at least one payment of the set of payments is anomalous …determining that the at least one payment is problematic according to a set of one or more predetermined criteria; …transmitting an alert … identifying at least one of the user or the at least one payment… responsive to the alert, a request to cancel or reverse the at least one payment; and canceling or reversing the at least one payment in accordance with the request”, are directed to (i) commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations), while the steps for “receiving a set of payments made from a first account to a second account,…generate … a predicted categorization for each payment in the set of payments… identify an actual categorization for each payment of the set of payments … assigning each payment of the set of payments to one or more clusters previously generated via a plurality of historical payments; …determining that at least one payment of the set of payments is anomalous …determining that the at least one payment is problematic according to a set of one or more predetermined criteria; …transmitting an alert … identifying at least one of the user or the at least one payment; receiving, … a request to cancel or reverse the at least one payment; and canceling or reversing the at least one payment in accordance with the request”, are directed to (ii) managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions), hence Examiner maintains that claim limitations are directed to certain methods of organizing human activity groupings of abstract ideas.
As it relates to applicant’s argument that, “the claims integrate any purported abstract idea into a practical application because the claimed technology provides technical improvements to the functioning of computing systems that detect anomalous activity in payment data”, and “therefore integrate any would-be abstract idea into a practical application”. Applicant’s arguments have been reconsidered; however, they are unpersuasive. As noted in the Non-Final action and determined in this Final action, applicant’s computing components (“computing system, recurrent neural network”, “intermediary device”, “alert”, “network interface”, “processor”, “memory” “electronic communication”, “call center device”, “user device”) and additional elements in the dependent claims (“call center device”, “user device”, “tracking device”, “mobile application”, “k-means clustering”, “hidden Markov model”, “electronic notification”) amount to no more than mere instructions to apply the exception using generic computer components (standard hardware and software) which does not integrate a judicial exception into a practical application nor provide an inventive concept (significantly more than the abstract idea). The use of applicant’s computing components is well-known, routine, and perform conventional activity.
Applicant then states, “the claims recite "significantly more" than any alleged abstract idea or generic computer implementation. In particular, the claims recite features that cannot be considered well-understood, routine, or conventional,” "executing, using the set of payments as input, a recurrent neural network to generate, as output, a predicted categorization for each payment in the set of payments," "executing an unsupervised clustering function to identify an actual categorization for each payment of the set of payments," where "the unsupervised clustering function involves assigning each payment of the set of payments to one or more clusters previously generated via a plurality of historical payments," and "determining that at least one payment of the set of payments is anomalous at least in part by determining that the actual categorization for the at least one payment does not match the predicted categorization for the at least one payment." Such features cannot be considered well-understood, routine, or conventional.
As it relates to the nonstatutory double patenting rejection, applicant has not filed a terminal disclaimer and generally states, “Applicant amends claims 1, 7-9, 12-14, and 18, rendering these rejections moot. Applicant’s arguments and amendments have been considered, but are unpersuasive. Examiner maintains that although the claims at issue are not identical, they are not patentably distinct from each other – see table below which identifies how the claims of the instant application are anticipated by US Patent No US 11,803,852. Examiner therefore maintains the nonstatutory double patenting rejection.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to an abstract idea without significantly more. Claims 1-17 are directed to a process (an act, or series of acts or steps), and claims 18-20 are directed to a machine (a concrete thing, consisting of parts, or of certain devices and combination of devices). Thus, each of the claims fall within one of the four statutory categories.
Step 2A-Prong 1: Representative independent claim 1 recites in part, “receiving a set of payments made from a first account to a second account, at least one of the first and second accounts being administered by the provider computing system, wherein the set of payments comprises one or more payments by a user; executing, using the set of payments as input, a recurrent neural network to generate, as output, a predicted categorization for each payment in the set of payments; responsive to generating the predicted categorization by executing the recurrent neural network, executing an unsupervised clustering function to identify an actual categorization for each payment of the set of payments, wherein the unsupervised clustering function involves assigning each payment of the set of payments to one or more clusters previously generated via a plurality of historical payments; determining that at least one payment of the set of payments is anomalous at least in part by determining that the actual categorization for the at least one payment does not match the predicted categorization for the at least one payment; determining that the at least one payment is problematic according to a set of one or more predetermined criteria; in response to determining that the at least one payment is both anomalous and problematic, transmitting an alert to an intermediary device, the alert identifying at least one of the user or the at least one payment; receiving, from the intermediary device, responsive to the alert, a request to cancel or reverse the at least one payment; and canceling or reversing the at least one payment in accordance with the request.”
The underlined limitations above demonstrate independent claim 1 is directed toward the abstract idea for receiving a set of payments, categorizing each payment, determining that a payment is anomalous and problematic, transmitting an alert and receiving a request to cancel or reverse the payment in a computing environment.
Applicant’s specification emphasizes a method/system for generating a set of payments made from a first user account to a second account via a tracking device, evaluating a payment and determining if the payment is anomalous whereby the actual categorization for the payment does not match the predicted categorization (based on categories for payments in the set of payments). The specification further discusses determining if the payment is problematic according to a set of one or more predetermined criteria (experiences of the user and/or on the experiences of other users with similar behavior) and transmitting an alert indicating there is a potential issue with the payment. The disclosure teaches that the alert may identify the user and/or the payment. (¶4)
Representative Claim 1 is considered an abstract idea because the claimed invention is directed to (i) commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations), and (ii) managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions). The steps for “receiving a set of payments made from a first account to a second account, at least one of the first and second accounts being administered by the provider computing system, wherein the set of payments comprises one or more payments by a user; executing, using the set of payments as input, a recurrent neural network to generate, as output, a predicted categorization for each payment in the set of payments; responsive to generating the predicted categorization by executing the recurrent neural network, executing an unsupervised clustering function to identify an actual categorization for each payment of the set of payments, wherein the unsupervised clustering function involves assigning each payment of the set of payments to one or more clusters previously generated via a plurality of historical payments; determining that at least one payment of the set of payments is anomalous at least in part by determining that the actual categorization for the at least one payment does not match the predicted categorization for the at least one payment; determining that the at least one payment is problematic according to a set of one or more predetermined criteria; in response to determining that the at least one payment is both anomalous and problematic, transmitting an alert to an intermediary device, the alert identifying at least one of the user or the at least one payment; receiving, from the intermediary device, responsive to the alert, a request to cancel or reverse the at least one payment; and canceling or reversing the at least one payment in accordance with the request”, pertains to management of personal behavior or interactions between people according to rules and instruction to facilitate commercial or legal interactions for determining that a user payment is anomalous and problematic, transmitting an alert and receiving a request to cancel or reverse the payment; hence directed to certain methods of organizing human activity groupings of abstract ideas. Therefore, the claimed invention recites an abstract idea--see MPEP 2106.04(II). Independent claims 14 and 18 recite substantially similar limitations as independent claim 1, therefore they are also directed to the same abstract idea.
Step 2A-Prong 2: This judicial exception is not integrated into a practical application because the additional elements “computing system, recurrent neural network”, “intermediary device”, “alert”, “network interface”, “processor”, “memory” “electronic communication”, “call center device”, “user device”, merely provide an abstract-idea based solution using data gathering and analysis and merely provide instructions for receiving a set of payments, categorizing each payment, determining that a payment is anomalous and problematic, transmitting an alert and receiving a request to cancel or reverse the payment in a computing environmentabstract idea to a particular technological environment. See MPEP 2106.05 (f-h). Further, the additional elements do not impose any meaningful limits on practicing the abstract idea—see MPEP 2106.05(g). Independent claim 1 fails to operate the recited “computing system, recurrent neural network”, “intermediary device”, “alert”, “network interface”, “processor”, “memory” “electronic communication”, “call center device”, “user device” (which are merely standard computer technology and hardware/software components- see applicant’s disclosure, ¶6: “the intermediary device may be a user device of the user. The alert may be part of an email message and/or a text message transmitted to the use”; ¶14: “determining the predicted categorization may comprise applying a hidden Markov model and/or a recurrent neural network to the second set of categories”; ¶22: “Various embodiments of the disclosure relate to a system which may be a provider computing system. The system may comprise a network interface configured to communicate with devices via a telecommunication network. The system may also comprise a processor and a memory storing instructions which, when executed by the processor, cause the processor to perform specific functions”; ¶84: “Each processor may be provided as one or more general-purpose processors, application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), digital signal processors (DSPs), or other suitable electronic data processing components structured to execute instructions provided by memory”;¶85: “An exemplary system for providing the overall system or portions of the embodiments might include a general purpose computing computers in the form of computers, including a processing unit, a system memory, and a system bus that couples various system components including the system memory to the processing unit”; in any exceptional manner, and there is no evidence in the disclosure to suggest achieving an actual improvement in the computer functionality itself, or improvement in any specific computer technology other than utilizing ordinary computational tools to automate and perform the abstract idea for receiving a set of payments, categorizing each payment, determining that a payment is anomalous and problematic, transmitting an alert and receiving a request to cancel or reverse the payment in a computing environment-see MPEP 2106.05(a). Accordingly, applicant has not shown an improvement or practical application under the guidance of MPEP section 2106.04(d) or 2106.05(a).
Dependent claims 2-13, 15-17, 19 and 20 fail to cure the deficiencies of the above noted independent claim from which they depend and are therefore rejected under the same grounds. The dependent claims further recite the abstract idea without imposing any meaningful limits on practicing the abstract idea. Dependent claims 2-13, 15-17, 19 and 20 recite additional data gathering and processing steps. For example dependent claims 2-5, 16 and 17 recites in part, “wherein the intermediary device is a”; claims 6 and 7 recite in part, “wherein the set of payments are"; claim 8, recites in part, “wherein determining that the at least one payment is anomalous further comprises:”; claim 9 recites in part, “wherein generating the first set of categories comprises”; claim 10 recites in part, “further comprising determining a maximum number”; claim 11 recites in part, “wherein determining the predicted categorization further comprises”; claim12 recites in part, “further comprising at least one of:”; claim 13 recites in part, wherein the set of one or more predetermined criteria comprises”, claim 15 recites in part, “further comprising determining that the most recent payment is”; claim 19 recites in part, “wherein the instructions further cause the processor to:”; claim 20 recite in part, “wherein the instructions further cause the processor to transmit”, which are still directed toward the abstract idea identified previously and are no more than mere instructions to apply the exception using a computer or with computing components. Therefore, the abstract idea fails to integrate into any practical application. Thus, under Step 2A-Prong Two the claims are directed to an abstract idea.
Step 2B: The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because as discussed above, with respect to integration of the abstract idea into a practical application, the additional elements “computing system, recurrent neural network”, “intermediary device”, “alert”, “network interface”, “processor”, “memory” “electronic communication”, “call center device”, “user device”, amount to no more than mere instructions to apply the exception using generic computer components which does not integrate a judicial exception into a practical application nor provide an inventive concept (significantly more than the abstract idea). The use of applicant’s computing components are well-known, routine, and performing conventional activity. The court describes the use of a computer to create electronic records, track information/data and issue simultaneous instructions as purely conventional computer functions and notes that nearly every computer has a data processing system with a communications controller and a data storage unit. Their collective functions merely provide conventional computer implementation.
The additional elements in the dependent claims “call center device”, “user device”, “tracking device”, “mobile application”, “k-means clustering”, “hidden Markov model”, “electronic notification”, amounts to no more than applying the judicial exception using generic computing components, and linking the use of the judicial exception to a computing environment. In this case, the “call center device”, “user device”, “tracking device”, “mobile application”, “electronic notification” is/are generically used to further process data and fails to integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea (see applicant’s disclosure, ¶5: “In one or more implementations, the intermediary device may be a call center device; ¶6: “the intermediary device may be a user device of the user. The alert may be part of an email message and/or a text message transmitted to the use”; ¶7: “The alert may be a pop-up message presented via a mobile application running on the user device”; ¶9: “the tracking device may be a part of the provider computing system”). Moreover, applicant’s additional elements of “k-means clustering”, “hidden Markov model” are broadly used to further process received data utilizing rules logic and fails to integrate the abstract idea into a practical application. The k-means clustering, hidden Markov model is recited at a high level of generality without technical implementation details of the operations to indicate how they improve computers or other technologies- see applicant’s specification at ¶12: “generating the first set of categories comprises applying clustering to payment amounts in the set of payments. The clustering may be unsupervised clustering. The clustering may be k-means clustering”; ¶14: “determining the predicted categorization may comprise applying a hidden Markov model and/or a recurrent neural network to the second set of categories”; ¶34: “An example model for detecting anomalous payment detection may involve using clustering, such as an unsupervised k-means clustering algorithm, to categorize past payment behavior for a particular user”; ¶88: “software and web implementations of the present disclosure may be accomplished with standard programming techniques with rule based logic and other logic to accomplish the various database searching steps, correlation steps, comparison steps and decision steps”) Claims are not saved from abstraction merely because they recite components more specific than a generic computer” Here the recited “call center device”, “user device”, “tracking device”, “mobile application”, “k-means clustering”, “hidden Markov model”, “electronic notification”, similarly provides a generic environment in which the claimed method is performed”. In re TLI Commc’ns LLPC Patent Litig., 823F.3d607,611 (Fed. Cir.2016). Moreover, there is no improvement to the “call center device”, “user device”, “tracking device”, “mobile application”, “k-means clustering”, “hidden Markov model”, “electronic notification”, and the additional element(s) amount to no more than applying the judicial exception using generic computing components, linking the use of the judicial exception to a computing environment. Hence, the additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Therefore, the abstract idea fails to integrate into any practical application. Thus, under Step 2A-Prong Two the claims are directed to an abstract idea.
Accordingly, even when considered as a whole, the claims do not transform the abstract idea into a patent-eligible invention since the claim limitations do not amount to a practical application or significantly more than an abstract idea for receiving a set of payments, categorizing each payment, determining that a payment is anomalous and problematic, transmitting an alert and receiving a request to cancel or reverse the payment in a computing environment. Hence, claims 1-20 are directed to non-statutory subject matter and are rejected as ineligible subject matter under 35 USC 101. See MPEP 2106.04.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-20 of U.S. Patent No.11,803,852. Although the claims at issue are not identical, they are not patentably distinct from each other – see table below which identifies how the claims of the instant application are anticipated by US Patent No US 11,803,852.
Application 18/385149
Anticipated by US Patent No 11,803,852
Claim 1: A method implemented by a provider computing system, the method comprising: receiving a set of payments made from a first account to a second account, at least one of the first and second accounts being administered by the provider computing system, wherein the set of payments comprises one or more payments by a user; executing, using the set of payments as input, a recurrent neural network to generate, as output, a predicted categorization for each payment in the set of payments; responsive to generating the predicted categorization by executing the recurrent neural network, executing an unsupervised clustering function to identify an actual categorization for each payment of the set of payments; wherein the unsupervised clustering function involves assigning each payment of the set of payments to one or more clusters previously generated via a plurality of historical payments; determining that at least one payment of the set of payments is anomalous at least in part by determining that the actual categorization for the at least one payment does not match the predicted categorization for the at least one payment; determining that the at least one payment is problematic according to a set of one or more predetermined criteria; in response to determining that the at least one payment is both anomalous and problematic, transmitting an alert to an intermediary device, the alert identifying at least one of the user or the at least one payment; receiving, from the intermediary device, responsive to the alert, a request to cancel or reverse the at least one payment; and canceling or reversing the at least one payment in accordance with the request.
Claims 6 & 7: wherein the set of payments are generated via a tracking device that tracks payments by the user
Claim 1: A method implemented by a provider computing system, the method comprising: generating, via a tracking device that tracks payments by a user, [claims 6,7 of application ‘149] a set of past payments made from a first account to a second account, at least one of the first and second accounts being administered by the provider computing system; executing, using the set of past payments as input, a recurrent neural network to generate, as output, a predicted categorization for [[a]]each payment in the set of past payments; responsive to generating the predicted categorization by executing the recurrent neural network, executing an unsupervised clustering function to identify an actual categorization for each payment of the set of past payments; determining that at least one payment of the set of past payments is anomalous at least in part by determining that the actual categorization for the at least one payment does not match the predicted categorization for the at least one payment; determining, responsive to determining that the at least one payment is anomalous, that the at least one payment is problematic according to a set of one or more predetermined criteria; in response to determining that the at least one payment is both anomalous and problematic, transmitting an alert to an intermediary device, the alert identifying at least one of the user and the at least one payment; receiving, from the intermediary device, responsive to the alert, a request to cancel or reverse the at least one payment; and canceling or reversing the at least one payment in accordance with the request.
Claims 2-5
Claims 2-5, 20
Claim 6: wherein the set of payments are generated via a tracking device that tracks payments by the user [claim 1 of Patent ‘852], and wherein the tracking device is part of the provider computing system.
Claim 6: wherein the tracking device is part of the provider computing system.
Claim 7: wherein the set of payments are generated via a tracking device that tracks payments by the user [claim 1 of Patent ‘852], and wherein the tracking device is a user device running a mobile application used to initiate each payment in the set of past payments.
Claim 7: wherein the tracking device is a user device running a mobile application used to initiate each payment in the set of past payments.
Claims 8-12
Claims 8-12
Claim 13: wherein the set of one or more predetermined criteria comprises at least one of whether: a number of phone calls with the user exceeds a first threshold; or a depletion metric for the payment exceeds a second threshold.
Claim 13: wherein the set of one or more predetermined criteria comprises at least one of whether: a number of phone calls with the user exceeds a first threshold; and a depletion metric for the payment exceeds a second threshold.
Claim 14
Claim 14
Claims 15-17
Claims 15-17
Claim 18: a network interface configured to communicate with devices via a telecommunication network; a processor and a memory storing instructions which, when executed by the processor, cause the processor to: receive payment data for a user, the payment data identifying payments made by the user to an account, the payments including a most recent payment; determine that the most recent payment is anomalous at least in part by: executing an unsupervised clustering function to generate categories for the payments in the payment data, the categories including a most recent payment category corresponding to the most recent payment; responsive to executing the unsupervised clustering function, executing, using the payment data as input, a recurrent neural network to generate, as output, a predicted category for the most recent payment; and determining that the predicted category for the most recent payment does not match the most recent payment category; determine that the most recent payment is problematic based on data in a user profile of the user satisfying one or more predetermined criteria; transmit, via the network interface, an electronic communication to at least one of a call center device or a user device of the user, the electronic communication indicating an issue has been detected with a recent payment.
Claim 18: a network interface configured to communicate with devices via a telecommunication network; a processor and a memory storing instructions which, when executed by the processor, cause the processor to: receive payment data for a user, the payment data identifying payments made by the user to an account, the payments including a most recent payment; determine that the most recent payment is anomalous at least in part by: executing an unsupervised clustering function to generate categories for the payments in the payment data, the categories including a most recent payment category corresponding to the most recent payment; responsive to executing the unsupervised clustering function, executing, using the payment data as input, a recurrent neural network to generate, as output, a predicted category for the most recent payment; determining that the predicted category for the most recent payment does not match the most recent payment category; determine that the most recent payment is problematic based on data in a user profile of the user satisfying one or more predetermined criteria; transmit, via the network interface, an electronic communication to at least one of a call center device and a user device of the user, the electronic communication indicating an issue has been detected with a recent payment; receive, responsive to the electronic communication, a request to cancel or reverse the recent payment; and cancel or reverse the recent payment in accordance with the request [claim 19 of application ‘149].
Claim 19: wherein the instructions further cause the processor to: receive, responsive to the electronic communication, a request to cancel or reverse the recent payment; and cancel or reverse the recent payment in accordance with the request [claim 18 of Patent ‘852].
Claim 20: wherein the instructions further cause the processor to transmit the electronic communication so as to cause the user device to present at least one selected from a group consisting of an email message, a text message, a push notification, or a pop-up message.
Claim 19: wherein the instructions cause the processor to transmit the electronic communication so as to cause the user device to present at least one selected from a group consisting of an email message, a text message, a push notification, and a pop-up message.
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 KIMBERLY L EVANS whose telephone number is (571)270-3929. The examiner can normally be reached M-F 730a-5p. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Lynda Jasmin can be reached at (571)272-6782. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/KIMBERLY L EVANS/Examiner, Art Unit 3629
/LYNDA JASMIN/Supervisory Patent Examiner, Art Unit 3629
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