CTNF 19/188,566 CTNF 92928 DETAILED ACTION Acknowledgements This action is in response to Applicant’s filing on Apr. 24, 2025 , 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 07-03-aia AIA 15-10-aia The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. Priority 02-26 AIA Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55. Information Disclosure Statement The information disclosure statements (IDSs) submitted on Apr. 24, 2025 , and Jun. 5, 2025 , were filed before the mailing of a first office action on the merits and therefore, are in compliance with the provisions of 37 CFR 1.97(b)(3). Accordingly, the IDSs have been considered. Claim Status The status of claims is as follows: Claims 1–20 are pending and examined with Claims 1, 10, and 19 in independent form. This is a first action on the merits. Claim Rejections - 35 USC § 101 07-04-01 AIA 07-04 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. Claims 1–9 recite a “non-transitory recording medium storing a program” and are therefore, directed to the statutory category of an "article of manufacture.” Claims 10–18 recite a “method” and are therefore, directed to the statutory category of a “process.” Claims 19 and 20 recite a “device” and are therefore, directed to the statutory category of a “machine.” Representative Claim Claim 19 is representative [“Rep. Claim 19”] of the subject matter under examination. Normal font is used for limitations that recite the judicial exception. Bold font is used to indicate additional elements evaluated under Step 2A, Prong Two (practical application) and Step 2B (significantly more). Italics font is used where necessary to identify intended use limitations 1 and underline font is used, as needed, in further describing the judicial exception. Each limitation is identified by a letter designator for use as a shorthand notation when analyzing/referencing each limitation. Rep. Claim 19 recites: [A] 19. A fraud detection device , comprising: a memory ; and a processor coupled to the memory , the processor being configured to execute processing, the processing including: [B] detecting and tracking people who are within a predetermined range based on sensor data acquired through sensing in the predetermined range in a store including a payment area, where a self-service checkout is installed , and [C] recognizing a behavior of each of the tracked people; [D] calculating a determination score indicating an extent to which each of the tracked people is a person who is required to perform payment at the self-service checkout , based on the recognized behavior; [E] assigning payment information, indicating that payment is completed, to a person who paid at the self-service checkout ; and [F] determining fraudulent passage at an exit of the store for each person passing through the exit, based on the determination score and the payment information. Claims are directed to an abstract idea exception. Step 2A, Prong One : Rep. Claim 19 recites “[B] detecting and tracking people who are within a predetermined range based on sensor data acquired through sensing in the predetermined range … and [C] recognizing a behavior of each of the tracked people; [D] calculating a determination score indicating an extent to which each of the tracked people is a person who is required to perform payment … , based on the recognized behavior; [E] assigning payment information, indicating that payment is completed, to a person who paid … ; and [F] determining fraudulent passage … for each person passing through the exit, based on the determination score and the payment information,” which recites managing commercial or legal interactions and enforcing payment obligations under the organizing human activity exception because Limitations B–F describe evaluating people to mitigate stealing from a store or the risk of “fraudulent passage … for each person passing through an exit” of a store. Alternatively 2 , 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 fo r the recitation of the generic computer components indicated in bold . MPEP § 2106.04(a)(2)(III). 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 ( Limitation B ) and analyzing it ( Limitations C, D, 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. Spec. ¶ 3. For example, Limitations C, D, E, and F are mental processes that are practically performed in the human mind or with pen and paper because it requires mere “observation, evaluation, judgment, and/or opinion” to “[C] recogniz[e] a behavior of each of the tracked people; [D] calculate[e] a determination score indicating an extent to which each of the tracked people is a person who is required to perform payment … , based on the recognized behavior; [E] assign[ ] payment information, indicating that payment is completed, to a person who paid … ; and [F] determine[e] fraudulent passage … for each person passing through the exit, based on the determination score and the payment information.” These steps could be performed by, for example, by a human clerk observing customers, judging who must pay, recording who paid, and decision which people passing through an exit are attempting to skip payment. Spec. ¶ 3. Limitations B, C, D, E, and F cover 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. 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 : The additional elements identified in Rep. Claim 19, considered individually and as an ordered combination, do not integrate the abstract idea exception into a practical application. MPEP § 2106.04(d). The additional elements are limited to the computer components and field of use limitations indicated in bold , supra . The additional elements are: A fraud detection device , comprising: a memory ; and a processor coupled to the memory; “in a store including a payment area, where a self-service checkout is installed;” “at the self-service checkout;” and “ at an exit of the store.” The additional elements do not improve the functioning of a computer or other technology. MPEP § 2106.05(a) . A claim improves technology only when it recites a specific improvement to the way a computer itself operates, not merely the application of an existing process using a computer. MPEP § 2106.05(a) (citing Enfish, LLC v. Microsoft Corp. , 822 F.3d 1327, 1336 (Fed. Cir. 2016)). Here, the specification describes that, prior to the disclosed embodiments, check-out bypassing was monitored visually by clerks, placing a heavy burden on the clerks. Spec. ¶¶ 3. Thus, the disclosed fraud detection device automates the pre-existing fraud detection process using a generic computer, but does not describe how the computer, memory, or processor themselves operate differently than their ordinary way. Spec. ¶¶ 49–52. Because the process of observing customers, deciding who must pay, and determining fraudulent passage can be and was performed manually, the computer is not being improved and is merely being used as a tool to perform the pre-existing manual decision-making process. Spec. ¶¶ 3, 99. Applying a pre-existing manual process using generic computer components is not an improvement to computer technology. MPEP § 2106.05(a). The specification describes the advantages of the disclosed system, in term of fraud detection and store operation outcomes (business outcomes) (e.g., preventing excessive detection of checkout bypassing, robustly detecting fraudulent passage, reducing restriction of store layout, and reducing the burden of monitoring by clerks). Spec. ¶¶ 3, 94, 101. The specification does not describe any specific technical improvement to the operation of the computer, memory, or computer architecture beyond executing the fraud detection program 50 on a generic computer 40. Spec. ¶¶ 49–52. Thus, any improvements described are improvements in fraud detection and store operations, not technical improvements to the computers themselves. The additional elements do not apply the abstract idea with a particular machine. Although the claims recite hardware components (i.e., a fraud detection device with a memory coupled to a processor), these components are recited at a high functional level and perform only their generic functions of receiving, storing, and processing data. Spec. ¶¶ 49–52. A machine is “particular” only when it imposes a meaningful limit on the claims scope. MPEP § 2106.05(b). Here, the specification describes the fraud detection device 10 as implemented by a generic computer 40, memory and processor. Spec. ¶¶ 49–52. Additionally, the specification contemplates the same functions may be implemented by an ASIC or FPGA. Spec. ¶ 52. These facts confirm that the hardware components are generic rather than “particular.” MPEP § 2106.05(b). The additional elements are mere instructions to apply the abstract idea exception, MPEP § 2106.05(f) and generally link the judicial exception to a particular technological environment, a retail self-service checkout environment. MPEP § 2106.05(h). Regarding additional elements of in a store including a payment area, where a self-service checkout is installed; at the self-service checkout; and at an exit of the store, these additional elements merely indicate a field of use or technological environment (i.e., a retail store with self-service checkout 74 and an exit) in which the abstract idea is applied. Spec. ¶¶ 31–34. Generally linking the use of a judicial exception to a particular technological environment or field of use does not integrate the exception into a practical application. MPEP § 2106.05(h). Regarding the additional elements of a fraud detection device , comprising: a memory ; and a processor coupled to the memory , Applicant’s Specification does not describe them with specificity beyond exemplary language and describes them 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. The specification’s own broad, exemplary characterization confirms that these components are not described in a manner that would impose any specific technical limitation that would integrate the abstract idea into a practical application. 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. ¶¶ 49–52. Limitation A describes the memory device “operatively coupled” in some way with the processor. Limitation A further describes the processor executing processing to perform the steps of the claimed invention. This takes generic hardware and describes the functions of receiving, storing, and sending data (instructions) between the processor and memory device, which merely invokes computers or other machinery in its ordinary capacity to receive, store, or transmit data. MPEP § 2106.05(f)(2). Limitations B–F describe the fraud detection device, comprising: a memory; and a processor coupled to the memory, performing the steps of the claimed invention, which represents the abstract idea exception itself on a general-purpose computer. Performing the steps of the abstract idea exception using a computer, merely adds a general-purpose computer after the fact to an abstract idea exception without imposing any meaningful technical limitations. MPEP § 2106.05(f)(2). Alternatively , the claim generically recites an effect of the abstract idea without specifying how the computer achieves that effect in any technically meaningful way. MPEP § 2106.05(f)(3). Therefore, the claim as a whole, considering the additional elements individually and as an ordered combination, amounts to no more than mere instructions to apply the abstract idea 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 19 is directed to an abstract idea. Independent Claims 1 and 10 are not substantially different from Rep. Claim 19, recite the same abstract idea as Rep. Claim 19, and contain no additional elements not otherwise analyzed for Rep. Claim 19. Therefore, Independent Claims 1 and 10 are also directed to the same abstract idea. The claims do not provide an inventive concept. Step 2B : Rep. Claim 19 fails Step 2B because the claim as a whole, even when considering the additional elements individually and in combination, does not amount to significantly more than the abstract idea. MPEP § 2106.05. The additional elements of “ in a store including a payment area, where a self-service checkout is installed;” “at the self-service checkout;” and “ at an exit of the store”) merely limit the abstract idea to a particular technological environment and are insufficient to amount to significantly more than the judicial exception and cannot provide an inventive concept. MPEP § 2106.05(h); Spec. ¶¶ 31–34. The additional elements of a fraud detection device , comprising: a memory ; and a processor coupled to the memory are each well-understood, routine, and conventional (“WRC”) computer components and functions in the relevant field, as evidenced by Applicant’s own disclosure 3 . Spec. ¶¶ 2, 31, 35, 49–52. Applicant’s Specification describes the device 10 comprising a computer 40 as a generic information processing device executing a fraud detection program 50 without any indication that these components are anything but conventional. (1) A fraud detection device , comprising: a memory ; and a processor coupled to the memory are WRC in the field of information processing and fraud detection in retail stores. Spec. ¶¶ 2, 31, 35, 49–52. The Specification further confirms that the functions of reading the fraud detection program from storage, loading it into memory, and executing instructions to process sensor data and determine scores are normal, well-understood operations of generic computers. Spec. ¶¶ 49–52. The combination of the additional elements is likewise WRC . A combination of individually well-understood, routine, and conventional elements does not provide an inventive concept unless the combination itself produces an unconventional result or is applied in an unconventional manner. MPEP § 2106.05(d)(2). Here, the combination performs each step in exactly the manner described as conventional throughout Applicant’s own Specification. There is no indication that the combination of these elements operates in an unconventional manner or produces a result that is other than what would be expected from the generic application of these individual components. Spec. ¶¶ 49–52., 53–80. Unlike BASCOM , where the claims recited a specific non-conventional arrangement of installing a filtering tool at a specific network location (an ISP server) rather than on individual end-user devices, Rep. Claim 19 does not recite how the elements are combined in a non-conventional way. The claims recite each element at a high level of generality without specifying the particular arrangement or order that constitutes the alleged improvement. At the high level of generality recited (detecting and tracking people, recognizing behavior, calculating a determination score, assigning payment information, and determining fraudulent passage), the combination is WRC. Spec. ¶¶ 8, 35–46, 77–80. Any BASCOM argument fails because any potentially non-conventional arrangement described in the specification (i.e., using weighted behavior scores, transferring determination scores when a basket is transferred between two people, deleting scores when a person leaves a pre-checkout area first, and normalizing determination scores by time before comparing to a threshold) are not recited in Claim 19. Spec. ¶¶ 43, 44, 66–72, 77, 78. A potentially non-conventional arrangement that is described but not claimed cannot supply the inventive concept at Step 2B. Because the claims here recite only generic components performing generic functions at a high level of generality, the abstract idea recited in claims cannot be improved by a computer. MPEP § 2106.05(f). No inventive concept is present under Step 2B. MPEP § 2106.05(d). Accordingly, the additional elements of Rep. Claim 19 have been recognized, based on Applicant’s own disclosure, as WRC activity in the field. MPEP § 2106.05(d). These elements do no more than “apply” the recited abstract idea(s) using known computer and computer-related components. See also Step 2A, Prong Two, supra . Independent Claim 1 is a computer-readable medium claim whose instructions cause a system to perform the same abstract processing and generic computer operations recited in Rep. Claim 19. Independent Claim 10 is a method claim reciting steps that perform the same abstract processing and generic computer operations recited in Rep. Claim 19. Independent Claims 1 and 10 add no additional elements beyond those of Rep. Claim 19 that would amount to significantly more than the abstract idea. Therefore, Independent Claims 1 and 10 also do not recite an inventive concept under Step 2B. 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 with the elements of the independent claims. Each dependent claim incorporates all the limitations of its parent Independent Claim and therefore recites the same abstract idea. The additional limitations recited in the dependent claims do not integrate the abstract idea exception into a practical application under Step 2A, Prong Two, and do not amount to significantly more than the abstract idea under Step 2B, for the following reasons: Dependent Claims 2, 3, 4, 11, 12, 13, and 20 add limitations specifying that the determination score becomes higher when recognized behaviors correspond to payment-required behaviors and lower when recognized behaviors correspond to payment-not-required behaviors, including adding or subtracting weighted behavior scores, transferring scores between people, deleting scores, or stopping calculation based on certain behaviors such as gripping a basket, staying in a pre-checkout area, transferring a basket, or leaving the pre-checkout area. These limitations further limit the abstract idea of evaluating customer behavior to decide who must pay and who is attempting fraudulent passage by specifying business rules and scoring logic, without reciting any specific technological implementation or improvement to the computer itself. Thus, they amount to additional mental steps or mathematical relationships that merely further describe or narrow the same abstract idea and do not integrate the exception into a practical application. Under Step 2B, these behavior and scoring refinements do not add any unconventional hardware or non-routine computer operations. They are implemented by the same generic computer 40 executing a fraud detection program 50 as recited in Rep. Claim 19. Accordingly, these dependent claims do not provide an inventive concept. Dependent Claims 5, 6, 7, 14, 15, and 16 add generating and outputting a control signal for reporting occurrence of fraudulent passage, such as controlling a report device or gate when fraudulent passage is detected. These limitations merely recite generic post-solution activity in the form of outputting a notification or control signal after the abstract fraud-detection decision has been made. They do not improve the functioning of the computer, and simply link the abstract idea to conventional reporting or gate-control operations in a retail environment. MPEP § 2106.05(f), (h). Under Step 2B, outputting a control signal or notification using known I/O devices is a WRC function of generic computer systems, as evidenced by the specification’s description of a standard input/output device 45 and communication interface 47 used to output control signals and notifications. Spec. ¶¶ 49–52. Accordingly, these dependent claims do not amount to significantly more than the abstract idea. Dependent Claims 8, 9, 17, and 18 add limitations specifying particular sensing modalities (e.g., using cameras or other sensors to acquire sensor data and detect/tracking people) or particular tracking/recognition processes (e.g., tracking people in a predetermined range or recognizing behaviors based on sensor data). The specification describes these sensors and tracking/recognition techniques in broad, exemplary terms, including that the recognition unit 12 and calculation unit 14 process sensor data from cameras or other sensors using known object detection and tracking techniques such as YOLO and DeepSORT, without any claimed improvement to those algorithms or to the underlying sensor hardware. Spec. ¶¶ 12, 31–37. These dependent limitations therefore merely select particular types of data using known methods of observing and tracking customers in the store, which are themselves part of the abstract idea of monitoring customers for checkout-bypassing and do not integrate the judicial exception into a practical application. Under Step 2B, the use of conventional sensors and known detection/tracking techniques, executed by generic computer 40, is WRC in the field, as shown by the specification’s description of standard sensor inputs and conventional image recognition/tracking techniques. Spec. ¶¶ 31–37, 49–52. Accordingly, these dependent claims also fail to provide an inventive concept. Conclusion Claims 1–20 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 19 otherwise styled as another statutory category is subject to the same analysis. Claim Rejections - 35 USC § 103 07-06 AIA 15-10-15 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. 07-20-aia AIA 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. 07-21-aia AIA Claim s 1, 7, 8, 9, 10, 16, 17, 18, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Suzuki et al. (U.S. Pat. Pub. No. 2023/0005267) [“Suzuki”] in view of Naito et al. (U.S. Pat. Pub. No. 2022/0270099) [“Naito”] . Regarding Claim 1, Suzuki discloses : A non-transitory recording medium storing a program that causes a computer to execute fraud detection processing comprising: (See at least ¶ 7, “a non-transitory computer-readable recording medium stores therein a fraud detection program that causes a computer to execute a process”) detecting and tracking [motion of the person] people who are within a predetermined range based on sensor data acquired through sensing in the predetermined range in a store including a payment area, where a self-service checkout is installed, and recognizing a behavior of each of the tracked people; (See at least ¶ 39, “The fraud detection apparatus 10 receives, from the camera device 200, a plurality of images obtained by capturing, by the camera device 200, a predetermined image capturing range, such as the inside of the store or the site of the retail store.” See also, Fig. 10 step S101 and associated text ¶¶ 90, 92 (“detect[ing] … a person”); ¶ 93 (“detects the motion of the person”); ¶ 94 (same). The store has a “self-service checkout terminal 400” and a payment area. ¶ 49. “specifies, from the captured image captured by the camera device 200, a person visiting a store and an object that is being used by the subject person. Moreover, a process of specifying the person may include a process of tracking, from the captured images that are captured at different time, the same person at different time on the basis of the appearance and an amount of movement of the person.” ¶ 68. “[T]he fraud detection apparatus 10 counts the number of motions of putting a commodity product into a basket and the number of motions of registering a commodity product to the user terminal 100, and then, evaluates a behavior of the person exhibiting with respect to a purchase of the commodity product.”) ¶ 41. calculating a determination score indicating an extent to which each of the tracked people is a person who is required to perform payment at the self-service checkout , based on the recognized behavior; (The italicized limitation is intended use because it describes what the determination score represents (i.e., the intended meaning or purpose of the score). Accordingly, statements of intended use fail to limit the scope of the claim under BRI. MPEP § 2111.04. (See at least ¶ 72, “The evaluating unit 43 counts a first count that is the number of the first motions of the person putting the commodity product sold at the store into the basket. Furthermore, the evaluating unit 43 counts a second count that is the number of the second motions of the person registering the commodity product targeted for the purchase to the user terminal 100. Furthermore, the evaluating unit 43 evaluates, on the basis of the first count and the second count, a behavior of the person exhibiting with respect to the purchase of a commodity product.” See also, ¶ 102. “[T]he state in which the difference between the first count and the second count is greater than or equal to the first threshold indicates that there is a comparatively large discrepancy between the number of motions of putting the commodity product into the basket and the number of motions of registering the commodity product. Accordingly, the evaluating unit 43 is able to determine that a scan omission of the commodity product occurs.”) ¶ 73.) assigning payment information, indicating that payment is completed , to a person who paid at the self-service checkout; and (The italicized limitation is intended use because it describes what the payment information represents. Accordingly, statements of intended use fail to limit the scope of the claim under BRI. MPEP § 2111.04. See at least ¶ 49, “Then, the customer scans a payment code displayed on a display unit of, for example, the self-service checkout terminal 400. Then, by making payment of an amount displayed on a payment screen of the self-service checkout terminal 400, the purchase of the commodity products has been completed.” The self-service checkout terminal 400 is “connected to the fraud detection apparatus 10 via the network 50 so as to be able to communicate with each other,” ¶ 49, and the fraud detection apparatus 10 tracks each person by “personal ID . ” ¶ 65.) determining fraudulent passage at an exit of the store for each person passing through the exit, based on the determination score and the payment information. (See at least ¶ 49, “the customer is able to exit the store by causing a gate reader 500 or the like installed at the exit of the store or the like to read a payment completion code displayed on the user terminal 100.” Under BRI, the gate reader’s verification function is a determination of fraudulent passage at the exit (i.e., a person that is unable to present payment completion code is fraudulent passage). Regarding the “based on a determination score and the payment information” element, the fraud detection apparatus 10 stores (in motion history 33) for each tracked person, both the determination score based on recognized behavior and payment completion status received from the self-checkout terminal 400. ¶¶ 49, 65. “[T]he self-service checkout terminal 400 and the gate reader 500 are connected to the fraud detection apparatus 10 via the network 50 so as to be able to communicate with each other.” ¶ 49. The “indicating” clauses in the “calculating” and “assigning” steps are intended use characterizing what the score and payment information represent and do not distinguish the prior art. MPEP § 2111.04. Under this claim construction, the “put-into basket motion count Nk and the commodity product registration motion count Ns” difference is the determination score, ¶ 102, and the payment code read by the gate reader 500 is the payment information, ¶ 49, and both values are stored by the fraud detection apparatus 10 for each person tracked at the time a person approaches the exit. To the extent Suzuki does not explicitly disclose the gate reader 500 consulting both the determination score and the payment information when exiting the store, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to do so. The fraud detection apparatus 10 already computes the behavioral determination score for every tracked person, ¶¶ 72, 102, and already receives the payment completion information from the self-service checkout terminal 400 with all the components connected via the same network 50. ¶ 49. Applying both already computed values at the exit gate is an easy and predictable result of a more accurate fraud determination at the exit, which is consistent with the stated purpose of Suzuki to “detect a scan omission of a commodity product caused by a fraudulent act, such as shoplifting, or an erroneous operation. ¶ 3. A person f ordinary skill would have been motivated to apply both the behavior determination score and payment information at the exit of a store to avoid fraudulent passage where a person with a high behavior determination score presents a partial payment (because items bypassed checkout scanning), which is the scenario Suzuki system is designed to mitigate. Alternatively , should a reviewing court determine Suzuki alone does not render Claim 1 obvious, Naito discloses combining a behavior fraud score with payment status information render to make a fraud determination and render Claim 1 obvious. determining fraudulent passage … based on the determination score and the payment information. (See at least ¶ 82, “The detection unit 1004 detects fraud behavior by a customer based on a captured image and/or information related to operation of the self-checkout POS terminal 10.” See at least ¶ 85, “[T]he detection unit 1004 analyzes the captured image and, if an action in which a customer puts a commodity into a shopping bag without executing the checkout process [bypassing payment] is recognized, detects the action as fraud,” ¶ 85, and “correlates the calculated fraud points to the customer code input … along with the associated fraud code and self-checkout POS terminal code and controls the communication control unit 1001 to transmit the correlated information to the management server 20 as fraud detection information.” ¶ 91. The checkout process is “a settlement or accounting process by which the amount due for purchase of previously registered items is tendered by the customer and accepted as payment in the sales transaction.” ¶ 22. Detection of checkout bypass is payment information under BRI. [F]raud points are accumulated and recorded on a per customer code basis” in “DB208.” ¶ 57. “If the total cumulative point in the updated point information exceeds a predetermined threshold, the display control unit 3004 controls the display unit 304 to highlight the customer who has the threshold-exceeding total cumulative point … by surrounding them with a red frame or the like.” ¶ 124. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to have combined determining fraudulent passage … based on the determination score and the payment information, as taught by Naito, to the exit gate of Suzuki, in the same field of invention of preventing self-service checkout terminal fraud in retail stores suing camera-based behavioral analysis, Suzuki, ¶ 3; Naito, ¶¶ 3, 4, with the motivation to improve fraud detection and the combination would have yielded predictable results of a consolidated fraud evaluation at a store exit. Regarding Claim 7, Suzuki and Naito disclose : The non-transitory recording medium of claim 1 and determining the fraudulent passage at the exit of the store for each person passing through the exit based on a determination score and the payment information (Claim 1 last limitation) Suzuki further discloses : wherein: determining the fraudulent passage includes determining that a person for which the determination score is equal to or higher than a threshold value and (See at least Fig. 11 and associated text ¶ 99, “the fraud detection apparatus 10 determines whether or not the put-into-basket motion count Nk of the person targeted for the determination is greater than a first threshold (Step S201).” t o which the payment information is not assigned is a person who has fraudulently passed through the exit . (This limitation is rejected for the same reason as in Claim 1 by both Suzuki alone and in combination with Naito as explained in Claim 1. For example, if payment information is not assigned, the customer cannot scan a payment code. Suzuki, ¶ 49.) Regarding Claim 8, Suzuki and Naito disclose : The non-transitory recording medium of claim 1 Suzuki further discloses : the processing further comprising: notifying a clerk of the fraudulent passage in a case in which the fraudulent passage of the exit is detected. (See at least ¶ 77, “If it is determined that a person has behaved fraudulently or performed an erroneous operation on the basis of the evaluation of a behavior obtained by the evaluating unit 43, the notifying unit 44 notifies the store clerk terminal 300 of an alert.” See also Fig. 10 and associated text ¶ 97, “If it is determined, on the basis of the target person determination process performed at Step S109, that the person for which no commodity product registration motion has been detected at Step S107 is a target person for a scan omission (Yes at Step Sll0), the fraud detection apparatus 10 notifies the store clerk terminal 300 of an alert (Step S111). If it is determined that the person for which no commodity product registration motion has been detected after having performed the process at Step S111 or at the process at Step S107 is not a target person for a scan omission (No at Step S110), the scan omission detection process illustrated in FIG. 10 is ended.”) Regarding Claim 9, Suzuki and Naito disclose : The non-transitory recording medium of claim 8 and notifying the clerk of the fraudulent passage Suzuki further discloses : wherein: notifying the clerk of the fraudulent passage is at least one of [1] immediately transmitting a message to an information processing terminal carried by the clerk, [2] recording a log of the fraudulent passage and transmitting the message to the information processing terminal at a predetermined timing, [3] outputting a sound or a warning sound of the message near the payment area, or [4] turning on a lamp installed near the payment area. The use of “At least one” and “or” is interpreted as requiring only one of limitations [1], [2], [3], or [4]. See at least ¶ 46 for [1], “The store clerk terminal 300 may be a mobile terminal, such as a smartphone or a tablet PC, carried by a store clerk of the retail store, or may be an information processing apparatus, such as a desktop PC or a notebook PC, installed at a predetermined position disposed inside the store. The store clerk terminal 300 receives an alert from the fraud detection apparatus 10 in the case where a fraudulent act or an erroneous operation, such as a scan omission of a commodity product, performed by a person is detected.” See also, ¶¶ 77, 97, 156, Fig. 10. Regarding Claim 10, Suzuki discloses : A fraud detection method, comprising: (See at least Title, “method”) by a processor [Fig. 22, “processor 100d”] , The remaining limitations of Claim 10 are not substantively different than those presented in Claim 1 and are therefore, rejected, mutatis mutandis , based on Suzuki and Naito for the same rationale presented in Claim 1 supra . The resolution of the remaining Graham factual inquiries to support a conclusion of obviousness that a particular known technique was recognized as part of the ordinary skill in the pertinent art is substantively the same as that presented in Claim 1 supra, and is incorporated in its entirety herein, mutatis mutandis , to support the rejection of Claim 10. Regarding Claims 16 and 17, Suzuki and Naito disclose : The fraud detection method of claim 10. The remaining limitations of Claims 16 and 17 are not substantively different than those presented in Claims 7 and 8, respectively, and are therefore, rejected, mutatis mutandis , based on Suzuki and Naito for the same rationale presented in Claims 7 and 8, respectively, supra . Regarding Claim 18, Suzuki and Naito disclose : The fraud detection method of claim 17. The remaining limitations of Claims 18 are not substantively different than those presented in Claim 9, and is therefore, rejected, mutatis mutandis , based on Suzuki and Naito for the same rationale presented in Claim 9, supra . Regarding Claim 19, Suzuki discloses : A fraud detection device, comprising: a memory [Fig. 22, “memory 100c”] ; and a processor coupled to the memory [Fig. 22, processor 100d”] , the processor being configured to execute processing, the processing including: (See at least Fig. 23) The remaining limitations of Claim 19 are not substantively different than those presented in Claim 1 and are therefore, rejected, mutatis mutandis , based on Suzuki and Naito for the same rationale presented in Claim 1 supra . The resolution of the remaining Graham factual inquiries to support a conclusion of obviousness that a particular known technique was recognized as part of the ordinary skill in the pertinent art is substantively the same as that presented in Claim 1 supra, and is incorporated in its entirety herein, mutatis mutandis , to support the rejection of Claim 19 . 07-21-aia AIA Claim s 2, 3, 4, 11, 12, 13, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Suzuki and Naito and further in view of Sommer et al. (U.S. Pat. Pub. No. 2023/0386306) [“Sommer”] Regarding Claim 2, Suzuki and Naito disclose : The non-transitory recording medium of claim 1 and calculating of the determination score Suzuki discloses : wherein: the calculating of the determination score includes calculating the determination score that becomes higher the more the recognized behavior corresponds to a payment-required behavior determined in advance as a behavior of a person who is required to perform payment, and (See at least ¶ 72, “The evaluating unit 43 counts a first count that is the number of the first motions of the person putting the commodity product sold at the store into the basket [i.e., Nk]. Furthermore, the evaluating unit 43 counts a second count that is the number of the second motions of the person registering the commodity product targeted for the purchase to the user terminal 100. Furthermore, the evaluating unit 43 evaluates, on the basis of the first count and the second count, a behavior of the person exhibiting with respect to the purchase of a commodity product . Here, a process of evaluating the behavior may include a process of determining that the person has behaved fraudulently or performed an erroneous operation in the case where a difference between the first count and the second count is greater than or equal to the first threshold and in the case where the first count is greater than or equal to the second threshold.” A higher Nk is a score that increases (“becomes higher”) the more the person exhibits “payment required behavior (putting the product into a basket).) See also, Naito where fraud points are added per recognized behavior to the total, ¶ 110; fraud points “correlate to the seriousness of the type of fraud,” ¶ 89 and are predefined because they are stored in the “fraud point master 116”. ¶¶ 89, 90. Suzuki discloses a “motion history 33” that stores a “commodity product return” motion. ¶ 123; see also Figs. 19 & 20, Step S302. A return reduces the count of items a person is responsible for. Fig. 21, Step S408. Thus, a return behavior/motion lowers what a person must pay because item count is reduced. Suzuki further discloses “If the person targeted for the determination does not carry the user terminal 100 (No at [Fig. 11,] Step S204), the fraud detection apparatus 10 determines that the person targeted for the determination is a non-target person for a scan omission.” ¶ 106. Thus, the fraud determination is not made when the user does not carry the user terminal 100, ¶ 106, or “does not wear a uniform of a store clerk.” ¶ 81. Suzuki does not explicitly disclose explicitly that a behavior determination score “becomes lower.” Thus, Suzuki does not explicitly disclose calculating of the determination score … becomes lower the more the recognized behavior corresponds to a payment-not-required behavior determined in advance as a behavior of a person who is not required to perform payment. Thus, Suzuki does not disclose but Sommer discloses : becomes lower the more the recognized behavior corresponds to a payment-not-required behavior determined in advance as a behavior of a person who is not required to perform payment. (See at least ¶ 7, “If a bag, for example, contains all the items on the shopper's receipt, their trust score can increase since the shopper is more likely paying for all the items they are purchasing. On the other hand, if the bag contains items that are not on the shopper's receipt, their trust score can decrease more quickly that it may increase. The trust score can decrease because the shopper may not be paying for all the items that they are leaving the retail environment with .” “decrease of the shopper trust score based on (i) a quantity of the contents of the shopper's bag that do not match the transaction data on the receipt and (ii) the bag checkout history data” ¶ 16. “Adjusting, by the computer system, the shop per trust score can include determining an amount of increase of the shopper trust score based on (i) the contents of the shopper's bag matching the transaction data on the receipt and (ii) the bag checkout history data.” ¶ 15; see also Claim 5.) 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 fraud detection system of Suzuki, which acknowledges the false-positive problem of flagging customers who pay at an ordinary cash register but fails to reduce or adjust its determination for such persons, Suzuki, ¶ 54, by combining the teachings of Sommer that the determination score … becomes lower the more the recognized behavior corresponds to a payment-not-required behavior determined in advance as a behavior of a person who is not required to perform payment, in the same field of invention, with the motivation to reduce false-positive fraud alerts for customers that pay at an ordinary cash register (instead of a self-service checkout) and improve the accuracy of exit-based fraud determination. Regarding Claim 3, Suzuki, Naito, and Sommer disclose : The non-transitory recording medium of claim 2 and calculating of the determination score … in a case in which each of the behaviors recognized for the tracked people is the payment-required behavior and in a case in which each of the recognized behaviors is the payment-not-required behavior Suzuki discloses wherein: the calculating of the determination score includes adding a behavior score … to the determination score in a case in which each of the behaviors recognized for the tracked people is the payment-required behavior, and, (See at least ¶ 95, “If the put-into-basket motion has been detected at the motion detection at Step S104 (Yes at Step S105), the fraud detection apparatus 10 registers the put-into-basket motion to the motion history 33 (Step S106). This indicates that, for example, a put-into-basket motion count Nk stored in the motion history 33 is incremented by one.” A “put-into-backet motion” is a behavior of a person who is required to perform payment because they are in the process of selecting items to purchase. Suzuki discloses “the calculating of the determination score includes adding a behavior score … to the determination score in a case in which each of the behaviors recognized for the tracked people is the payment-required behavior.” ¶ 95. Suzuki further discloses “calculating of the determination score … in a case in which each of the recognized behaviors is the payment-not-required behavior.” Suzuki does not disclose “adding a behavior score weighted for each type of payment-required behavior” or “subtracting the behavior score weighted for each type of payment-not-required behavior from the determination score.” Thus, Suzuki does not disclose but Naito discloses : calculating of the determination score includes adding a behavior score weighted for each type of payment-required behavior to the determination score (See at least Fig. 3, where “Fraud Code” of “001” results in a “fraud point” value of “5” and “Fraud Code” of “002” results in a “fraud point” value of “3”. “The calculation unit 1005 refers to the fraud point master 116 and calculates the fraud points corresponding to the fraud detected by the detection unit 1004. In the example of FIG. 3, if the action/operation "YYY1" is recognized by image analysis or otherwise, the detection unit 1004 detects fraud name "XXX1" corresponding to the fraud code "001". The calculation unit 1005 uses the fraud point value "5" corresponding to the fraud code "001" as the fraud points assigned to the detected fraud event.” ¶ 90. “The calculation unit 1005 calculates the fraud points based on values in the fraud point master 116. In general, the values set for the fraud points correlate to the seriousness of the type of fraud.” ¶ 89. 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 +1 counter of Suzuki with a behavior score weighted for each type of payment-required behavior to the determination score of Naito, in the same field of retail fraud detection using behavioral analysis and scoring with the motivation to provide amore accurate fraud assessment by correlating the score to “the seriousness of the type of fraud.” Naito, ¶ 89. calculating the determination score by [1] subtracting the behavior score weighted for each type of payment-not-required behavior from the determination score, [2] transferring the behavior score to the determination score of another corresponding person, or [3] stopping calculating the determination score . (The use of “or” is interpreted as requiring only one of limitations [1], [2], or [3]. See at least ¶ 203 for [3], “if a predetermined period of time is elapsed from the previous or most recent fraud detection for a specific customer, the fraud points may be reset, and the point accumulation tally may be restarted/reset.” t would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify calculation of the determination score of Suzuki by stopping the calculation of the determining score as taught by Naito, in the same field of retail fraud detection using behavioral analysis and scoring with the motivation to that a customer is innocent and close monitoring is not required. Naito, ¶ 204. Regarding Claim 4, Suzuki, Naito, and Sommer disclose : The non-transitory recording medium of claim 2, the payment-required behavior , and the payment-not-required behavior. Suzuki further discloses wherein: the payment-required behavior includes at least one of a behavior related to gripping of [1] at least one of a basket, a cart, or a product, or [2] receiving at least one of a basket, a cart, or a product from another person, or [3] a behavior related to an operation of the self-service checkout , and (The use of “at least one” and “or” is interpreted as requiring only one of limitations [1], [2], or [3]. See at least ¶ 70 for [3], “a process of specifying the second motion of registering the commodity product targeted for the purchase may include a process of specifying, on the basis of the specified object and the skeleton information, the second motion in the case where both elbows of the person have not moved for a predetermined period of time while being bent forward within a predetermined range of the region of the specified basket”) the payment-not-required behavior includes at least one of [1] transfer of at least one of a basket, a cart, or a product to another person, [2] a behavior indicating non-involvement in the operation of the self-service checkout , or [3] passage through the payment area in a state in which a product is not held. (The use of “at least one” and “or” is interpreted as requiring only one of limitations [1], [2], or [3]. See at least ¶ 106 for [2], “If the person targeted for the determination does not carry the user terminal 100 (No at Step S204), the fraud detection apparatus 10 determines that the person targeted for the determination is a non-target person for a scan omission.”) Regarding Claim 11, Suzuki and Naito disclose : The fraud detection method of claim 10. The remaining limitations of Claims 11 are not substantively different than those presented in Claim 2, and is therefore, rejected, mutatis mutandis , based on Suzuki, Naito, and Sommer for the same rationale presented in Claim 2, supra . Regarding Claims 12 and 13, Suzuki, Naito, and Sommer disclose : The fraud detection method of claim 11. The remaining limitations of Claims 12 and 13 are not substantively different than those presented in Claims 3 and 4, respectively, and are therefore, rejected, mutatis mutandis , based on Suzuki, Naito, and Sommer for the same rationale presented in Claims 3 and 4, respectively, supra . Regarding Claim 20, Suzuki and Naito disclose : The fraud detection device of claim 19. The remaining limitations of Claims 20 are not substantively different than those presented in Claim 2, and is therefore, rejected, mutatis mutandis , based on Suzuki, Naito, and Sommer for the same rationale presented in Claim 2, supra . 07-21-aia AIA Claim s 5, 6, 14, 15 are rejected under 35 U.S.C. 103 as being unpatentable over Suzuki, Naito, and Sommer, and further in view of Yokoyama (U.S. Pat. Pub. No. 2018/0240090) [“Yokoyama”] Regarding Claim 5, Suzuki, Naito, and Sommer disclose : The non-transitory recording medium of claim 4, the behavior related to the operation of the self-service checkout, and the behavior indicating non-involvement in the operation of the self-service checkout Suzuki further discloses wherein: the behavior related to the operation of the self-service checkout includes at least one of [1] staying of a person in a predetermined pre-payment checkout area including in front of the self-service checkout, [2] reading of product information by a scanner provided at the self-service checkout , or [3] touching on an operation surface of the self-service checkout, and (The use of “at least one” and “or” is interpreted as requiring only one of limitations [1], [2], or [3]. See at least ¶ 49 for [2], “the customer scans a payment code displayed on a display unit of, for example, the self-service checkout terminal 400. Then, by making payment of an amount displayed on a payment screen of the self-service checkout terminal 400, the purchase of the commodity products has been completed.” “[T]he fraud detection apparatus 10 specifies a motion of a person registering a commodity product targeted for a purchase to the user terminal 100 in the case where, for example, the both elbows of the person have not moved for a predetermined time period while being bent forward within a predetermined range of a the region of the specified basket. Furthermore, the fraud detection apparatus 10 is able to detect, for example, a surface of a barcode of each of the commodity products and specify a more detailed motion, such as a motion indicating which commodity product has been registered.” ¶ 85.) Suzuki does not disclose but Yokoyama discloses : the behavior indicating non-involvement in the operation of the self-service checkout includes at least one of [1] staying at a position farther from the self-service checkout than other people or [2] leaving of the pre-payment checkout area earlier than other people, (The use of “at least one” and “or” is interpreted as requiring only one of limitations [1] and [2]. See at least ¶ 15 for [2], “The monitoring server 40, which is an example of a theft detection machine, monitors the operation of the customer within the POS area A1 based on the first image I1 captured by the first camera 31 and the second image 12 captured by the second camera 32, for example. Based on the first image I1 and the second image 12, the monitoring server 40 executes detection and notification of a customer who exits from the POS area Al without completing the checkout . Even if a transaction relating to a plurality of customers belonging to one group who enter the retail store S together is not settled, the monitoring server 40 permits the customers of that group to exit from the checkout area Al without any notification so long as the customer is not the final person of the group to exit (hereinafter referred to as "final exit person") .” See also ¶¶ 94, 96, Fig. 10. in a case in which a plurality of people stay in the pre-payment checkout area corresponding to the same self-service checkout . (The use of “at least one” and “or” is interpreted as requiring only one of limitations [1] and [2]. See at least ¶ 15 for [2], “determine whether at least two persons are captured in the first image”. “while the registration processing is executed, the other customers who are companions are also at a position adjacent to the registration apparatus 10.” ¶ 27; Fig. 9 disclosing multiple customers with shared checkout information ID 90.) 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 retail exit fraud detection system of Suzuki, which detects “scan omissions” by tracking customer behavior with cameras at self-service checkouts (Suzuki, ¶¶ 41, 72), with the behavior indicating non-involvement in the operation of the self-service checkout includes … leaving of the pre-payment checkout area earlier than other people in a case in which a plurality of people stay in the pre-payment checkout area corresponding to the same self-service checkout, as taught by Yokoyama, in the same field of retail exit-based fraud detection, with the motivation to reduce false fraud alerts against non-paying customers in group shopping scenarios, which is a problem Suzuki itself acknowledges. Suzuki, ¶ 82. Regarding Claim 6, Suzuki, Naito, Sommer, and Yokoyama disclose : The non-transitory recording medium of claim 5 and tracking people Suzuki further discloses : wherein: tracking the people includes detecting entry into and exit from the payment area [cash register area] and the pre-payment checkout area. (See at least Fig. 18 and associated text ¶ 140, “FIG. 18 indicates a state in which the fraud detection apparatus 10 specifies, from the captured image of the cash register area , the person P who performs a procedure of calculation of a payment amount at a self-service checkout terminal 400-y, and determines, on the basis of the captured image of the sales floor A , that the specified person Pis the same as the person P who has been specified and who made a motion of acquiring the alcoholic beverages three times. Furthermore, in the example illustrated in FIG. 18, it is determined that a person Q is a person who is different from the person P; however, it is, of course, conceivable to be determined that the person Q is the same person who has been specified from another captured image.” See also, ¶ 150 (detecting entry to payment area). Regarding the claimed “pre-payment checkout area,” cameras track customers in sales floor zones where customers acquire and self-scan products before payment, the pre-payment zone. ¶¶ 114, 115. When a customer enters the sale floor camera image, entry into the pre-payment checkout area is detected. When the same person is re-identified in the cash register area via the Re-ID process, exit from the pre-payment area is detected. ¶¶ 151–154, Figs. 18 & 21. Suzuki alone teaches Claim 6. However should a reviewing court disagree, Yokoyama discloses said limitation. A POS area with three explicitly bounded zones: registration area A11 (pre-payment area), checkout area A12, and exit are A13 with a first camera 31 detecting customers entering and present in the registration are and a second camera 31 detecting customers exiting through exit B11. Yokoyama, ¶¶ 19, 19, 26–31, Fig. 1. 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 retail exit fraud detection system of Suzuki with Yokoyama’s detecting entry into and exit from the payment area and the pre-payment checkout area, in the same field of invention, because both inventions solve the same problem (i.e., detecting fraudulent behavior at retail self-service checkout areas using camera-based person tracking) and combining these known techniques yields predictable results of a more precise entry/exit event detection system for detecting fraud. Regarding Claim 14, Suzuki, Naito, and Sommer disclose : The fraud detection method of claim 13. The remaining limitations of Claims 14 are not substantively different than those presented in Claim 5, and is therefore, rejected, mutatis mutandis , based on Suzuki, Naito, Sommer, and Yokoyama for the same rationale presented in Claim 5, supra . Regarding Claim 15, Suzuki, Naito, Sommer, and Yokoyama disclose : The fraud detection method of claim 14. The remaining limitations of Claims 15 are not substantively different than those presented in Claim 6, and is therefore, rejected, mutatis mutandis , based on Suzuki, Naito, Sommer, and Yokoyama for the same rationale presented in Claim 6, supra . Conclusion 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). 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, Bennett M Sigmond can be reached at (303) 297-4411. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. 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If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /JAMES H MILLER/Primary Examiner, Art Unit 3694 Application/Control Number: 19/188,566 Page 2 Art Unit: 3694 Application/Control Number: 19/188,566 Page 3 Art Unit: 3694 Application/Control Number: 19/188,566 Page 4 Art Unit: 3694 Application/Control Number: 19/188,566 Page 5 Art Unit: 3694 Application/Control Number: 19/188,566 Page 6 Art Unit: 3694 Application/Control Number: 19/188,566 Page 7 Art Unit: 3694 Application/Control Number: 19/188,566 Page 8 Art Unit: 3694 Application/Control Number: 19/188,566 Page 9 Art Unit: 3694 Application/Control Number: 19/188,566 Page 10 Art Unit: 3694 Application/Control Number: 19/188,566 Page 11 Art Unit: 3694 Application/Control Number: 19/188,566 Page 12 Art Unit: 3694 Application/Control Number: 19/188,566 Page 13 Art Unit: 3694 Application/Control Number: 19/188,566 Page 14 Art Unit: 3694 Application/Control Number: 19/188,566 Page 15 Art Unit: 3694 Application/Control Number: 19/188,566 Page 16 Art Unit: 3694 Application/Control Number: 19/188,566 Page 17 Art Unit: 3694 Application/Control Number: 19/188,566 Page 18 Art Unit: 3694 Application/Control Number: 19/188,566 Page 19 Art Unit: 3694 Application/Control Number: 19/188,566 Page 20 Art Unit: 3694 Application/Control Number: 19/188,566 Page 21 Art Unit: 3694 Application/Control Number: 19/188,566 Page 22 Art Unit: 3694 Application/Control Number: 19/188,566 Page 23 Art Unit: 3694 Application/Control Number: 19/188,566 Page 24 Art Unit: 3694 Application/Control Number: 19/188,566 Page 25 Art Unit: 3694 Application/Control Number: 19/188,566 Page 26 Art Unit: 3694 Application/Control Number: 19/188,566 Page 27 Art Unit: 3694 Application/Control Number: 19/188,566 Page 28 Art Unit: 3694 Application/Control Number: 19/188,566 Page 29 Art Unit: 3694 Application/Control Number: 19/188,566 Page 30 Art Unit: 3694 Application/Control Number: 19/188,566 Page 31 Art Unit: 3694 Application/Control Number: 19/188,566 Page 32 Art Unit: 3694 Application/Control Number: 19/188,566 Page 33 Art Unit: 3694 Application/Control Number: 19/188,566 Page 34 Art Unit: 3694 Application/Control Number: 19/188,566 Page 35 Art Unit: 3694 Application/Control Number: 19/188,566 Page 36 Art Unit: 3694 Application/Control Number: 19/188,566 Page 37 Art Unit: 3694 Application/Control Number: 19/188,566 Page 38 Art Unit: 3694 Application/Control Number: 19/188,566 Page 39 Art Unit: 3694 Application/Control Number: 19/188,566 Page 40 Art Unit: 3694 Application/Control Number: 19/188,566 Page 41 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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