DETAILED ACTION
Acknowledgements
This action is in response to Applicant’s filing on Nov. 19, 2025, and is made 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 emailing the agenda, and (3) permitting real-time document collaboration and screen sharing.
Interviews are available by telephone or, preferably, by video conferencing using the USPTO’s web-based collaboration platform. Applicants are strongly encouraged to schedule via the USPTO Automated Interview Request (AIR) portal at http://www.uspto.gov/interviewpractice. If an interview is needed more quickly than permitted by the AIR scheduling tool, note this in the AIR remarks for consideration. The Examiner routinely considers such urgent requests when practicable.
An agenda submitted when filing the AIR is strongly encouraged, because Examiners use agendas when determining whether to grant an interview. The AIR has character limits, so send the agenda contemporaneously to James.Miller1@uspto.gov and reference the AIR.
After-Final Interviews Requests are granted only at the Examiner’s discretion and only if disposal or clarification for appeal may be accomplished with only nominal further consideration. MPEP § 713.09. An advance agenda explaining how the interview advances prosecution—e.g., through targeted arguments, identified Examiner error, or proposed claim amendments—is strongly suggested.
For GRANTED requests, expect an email within two (2) business days confirming a date/time slot and collaboration tool access instructions. For DENIED requests, the record will include an explanation for the denial.
The examiner is generally available for interviews, Monday through Friday, 10:00 a.m. to 4:00 p.m. ET.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Status
The status of claims is as follows:
Claims 1–11 and 20 remain pending and examined with Claims 1 and 20 in independent form.
Claims 1–8, 10 and 20 are presently amended.
No Claims are presently cancelled or added.
Response to Amendment
Applicant's Amendment has been reviewed against Applicant’s Specification filed Jun. 27, 2025, [“Applicant’s Specification”] and accepted for examination.
Response to Arguments
35 U.S.C. § 101 Argument
Applicant argues the amended claims do not recite a mental process exception because the following limitations of amended Claim 1 are not practically performed in the human mind: "represent the generated relationship scores as icons associated with the plurality of records; adjust a size of each icon based on a value of a relationship score associated with the icon; display the icons on a graphical user interface (GUI), wherein spacings between the icons are adjusted based on the size of each icon; and automatically move the icons on the GUI, relative to each other, based on the size of each icon," relying on Data Engine Tech. LLC v. Google LLC and USPTO Example 37, Claim 2. Applicant’s Reply at 8.
Examiner respectfully disagrees. Independent Claims recite the mental process exception in all but the “display the icons on a graphical user interface (GUI), and automatically move the icons on the GUI, relative to each other, based on the size of each icon,” elements, which are evaluated at Step 2A, Prong Two as additional elements. The remaining limitations of Rep. Claim 1 encompass observations, evaluations, and judgments that can practically be performed in the human mind or by a human using pen and paper. For example, a person can compare record information, infer relationships, assign scores, draw differently sized icons corresponding to the scores, position the symbols father apart based on their size, and display the resulting diagram. The recitation of generic computer components does not remove the claims from the mental process exception.
Applicant’s reliance on Data Engine is not persuasive. In Data Engine, the claims recited “a specific method for navigating through three-dimensional electronic spreadsheets,” 906 F.3d at 1008, using “a specific structure (i.e., notebook tabs) within a particular spreadsheet display that performs a specific function (i.e., navigating within a three-dimensional spreadsheet), Id. at 1011, which “solved this known technological problem in computers in a particular way.” Id. at 1008. Here, the present claims do not recite a particular GUI architecture or layout technique. Rather, the claims recite result-orientated functions of a GUI displaying icons and automatically moving them based on icon size, without specifying a technical mechanism that improves GUI functionality.
Applicant reliance on USPTO Example 37, Claim 2, is also not persuasive. Unlike Example 37, the present Specification does not identify a particular problem in conventional GUI functionality or describe a particular technical solution that addresses that problem. Example 37 explains that conventional interfaces require users to manually arrange icons, and the claims recite that improvement (“automatically moving the most used icons to a position on the GUI closest to the start icon of the computer system based on the determined amount of use”) to improve access to frequently used icons. Here, neither the claim nor Specification describes how icon locations are determined or identifies a GUI problem solved by the claimed movement. Rather, the Specification teaches in functional terms that “the size of the icons, spacing between the icons, etc., are varied based on the level of the relationship, the score, etc.” and broadly “any graphical representation of the relationship or other data can be presented to the user.” Spec. ¶ 56; MPEP § 2106.05(a).
As explained in IBM v. Zillow, “improving a user's experience while using a computer application is not, without more, sufficient to render the claims” patent-eligible at step one.” Int'l Bus. Machines Corp. v. Zillow Group, Inc., 50 F.4th 1371, 1377 (Fed. Cir. 2022). Here, like IBM v. Zillow, the present claims are directed to identifying, analyzing, and presenting relationship score information to a user to improve the user’s ability to review that information, without specifying a technical mechanism for doing so or describing in the Specification a technical problem the movement addresses. Thus, the pending claims here, unlike the authority cited by Applicant there, does not recite a specific technical improvement to the functioning or capability of a GUI or a computer itself. Id. at 1378.
Applicant argues at Step 2A, Prong Two that even if the amended claims recite an exception, it is integrated into a practical application because the claims improve user interaction, reduce processor load, memory space requirements, and hardware requirements, and automatically display and rearrange icons like USPTO Example 37, Claim 2. Applicant’s Reply at 8–9 (citing Spec. ¶¶ 19, 21).
Examiner respectfully disagrees. The claims recite generic computer components and result-orientated functions: “generate a relationship score”; “adjust a size of each icon” and “spacings between the icons” “based on a value of a relationship score” and “based on the size of each icon”, respectively; “display the icons”; and “automatically move the icons on the GUI, relative to each other, based on the size of each icon.” The claims do not recite a particular technical mechanism for improving the capability or functioning of a GUI or the computer itself. The Specification’s asserted improvements enable a user to quickly assess relationships and improve user efficiency and experience, not an identified improvement in computer functionality or GUIs themselves. The Specification’s statements that the claimed invention provides “reduced processor load,” “less memory space required,” “reduced hardware requirements,” and improved functioning of the underlying computing device are conclusory. Spec. ¶¶ 19, 21. The Specification does not explain how the claimed comparison of record fields, generating relationship scores, or score-based icon display, sizing, spacing, and movement changes the operation of the processor, memory, hardware, GUI, or computer to achieve the alleged benefit of resource reductions. Therefore, the asserted improvement is not apparent to a PHOSITA as required by MPEP § 2106.05(a).
Further, the assertion that a user may issue fewer commands while using a computer does not demonstrate an improvement in computer functionality. Reducing the frequency of user interaction may improve a user’s experience but does not, without a claimed technical mechanism, improve how the computer processes, stores, or displays information.
Applicant argues that the amended claims recite significantly more than any alleged judicial exception because the “represent the generated relationship scores ascomputer functionality while reducing system resource usage, relying on Berkheimer and DDR Holdings. Applicant’s Reply at 10–11.
Examiner respectfully disagrees. The additional elements amount to generic computer implementation and result-orientated information presentation without specifying a technical mechanism. The Specification’s statements that the claimed invention provides “reduced processor load,” “less memory space required,” “reduced hardware requirements,” and improved functioning of the underlying computing device are conclusory, Spec. ¶¶ 19, 21, because neither the claim nor the Specification identifies a technical mechanism producing those results. Reduced user commands reflect an improvement to the user not the computer or GUI.
Berkheimer and DDR Holdings do not compel a different result. Whether claimed subject matter is novel or nonobvious under §§ 102, 103 is a distinct inquiry from whether additional elements amount to significantly more under Step 2B. MPEP § 2106.04(I) (citing Ass'n for Molecular Pathology v. Myriad Genetics, Inc., 133 S.Ct. 2107, 2117 (2013) (“Groundbreaking, innovative, or even brilliant discovery does not by itself satisfy the § 101 inquiry.”)); MPEP § 2106.05 (“As made clear by the courts, the novelty of any element or steps in a process, or even of the process itself, is of no relevance in determining whether the subject matter of a claim falls within the § 101 categories of possibly patentable subject matter.”). DDR Holdings is likewise inapposite. The present claims do not recite a solution necessarily rooted in computer technology to overcome a problem specifically arising in computer networks.
35 U.S.C. § 103 Argument
Applicant’s arguments with respect to Claims 1–4, 6–11, and 20 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1–20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., an abstract idea) without significantly more.
Analysis
Step 1: Claims 1–11 and 20 are directed to a statutory category. Claims 1–11 recite a “system” and are therefore, directed to the statutory category of a “machine.”. Claim 20 recites “[o]ne or more computer storage devices having computer-executable instructions stored thereon” and is therefore, directed to the statutory category of an "article of manufacture.”
Representative Claim
Claim 1 is representative [“Rep. Claim 1”] 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 limitations1 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 1 recites:
[A] 1. A system operable to identify relationships between records, the system comprising: a data storage device storing data corresponding to a plurality of records, the data related to different consumer cards; and a computer-readable medium storing instructions that are operative upon execution by a processor to:
[B] access the data stored in the data storage device;
[C] compare data fields of the data to identify one or more matches between the plurality of records, wherein the one or more matches comprises a locality match, a shipping address match, an email match, a device match, or a combination thereof;
[D] determine a plurality of relationships between the plurality of records based at least on the identified one or more matches;
[E] for each of the determined plurality of relationships, generate a relationship score;
[F] represent the generated relationship scores as icons associated with the plurality of records;
[G] adjust a size of each icon based on a value of a relationship score associated with the icon;
[H] display the icons on a graphical user interface (GUI), wherein spacings between the icons are adjusted based on the size of each icon; and
[I] automatically move the icons on the GUI, relative to each other based on the size of each icon.
Claims are directed to an abstract idea exception.
Step 2A, Prong One: Limitations B–H, as drafted, recite the abstract idea exception of mental processes that under the broadest reasonable interpretation, cover performance in the human mind or with pen and paper, but for the recitation of the generic computer components indicated in bold. MPEP § 2106.04(a)(2)(III).
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–H, recite collecting information (Limitation B), analyzing it (Limitations C, D, E, F, G) and displaying certain results of the collection and analysis (Limitation H), where the data analysis steps are recited at a high level of generality such that they could practically be performed in the human mind. For example,
Limitations C is a mental process that is practically performed in the human mind or with pen and paper because collecting and comparing known information are steps that can be practically performed in the human mind under Classen. Limitations D and E 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 “[D] determine a plurality of relationships … based at least on the identified one or more matches” and “[E] … generate a relationship score” in any possible way. Limitations D and E 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 under BRI. Limitations F and G 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 “[F] represent the generated relationship scores as icons” and “[G] adjust a size of each icon based on a value of a relationship score” in any possible way. The “icon” and “size” are mere judgments and 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 under BRI. “The use of a physical aid (e.g., pencil and paper or a slide rule) to help perform a mental step does not negate the mental nature of the limitation but simply accounts for variations in memory capacity from one person to another” or a multi-step mental process. MPEP § 2106.04(a)(2)(III)(B).
If a claim limitation under BRI, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract idea exception. MPEP § 2106.04(a)(2)(III). Accordingly, the pending claims recite an abstract idea exception.
Step 2A, Prong Two: The additional elements identified in Rep. Claim 1, 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 indicated in bold, supra. The additional elements are: A system comprising: a data storage device storing data; a computer-readable medium storing instructions; a processor; a graphical user interface (GUI); and Limitation I.
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 asserts that the claimed invention improves “user interaction (such as improved usability, improved user efficiency, and increased user interaction performance)” (Spec. ¶ 19); allowing “a user to quickly assess the relationships between the different payment cards and/or payment accounts, in a user interface (UI) … improv[ing] user efficiency via the UI interaction and improv[ing] user performance via the UI.” Spec. ¶ 20. “[U]ser interaction performance is also improved via the UIs as described herein. This overall improves the human machine interaction.” Spec. ¶ 22. “In some examples, the user is likely to issue a lesser number of commands to the computing device for monitoring the relationship between payment cards and/or payment accounts.” Spec. ¶ 21. These asserted benefits describe a user’s review and understanding of data, not an improvement in computer of GUI technology.
Although the Specification asserts, “The lesser number of commands to the computing device results in reduced system resource usage” (Spec. ¶ 21), and “one or more of reduced processor load, less memory space required, reduced hardware requirements, [and] enhanced reliability” (Spec. ¶ 19), the specification does not explain how the claimed comparison of record fields, generation of relationship scores, or score-based icon sizing, display, spacing, and movement changes processor or memory operation, display rendering, or GUI operation to produce those asserted results. Thus, the specification may set forth an asserted improvement, but the asserted technological improvement is conclusory because the specification does not provide sufficient technical detail for a PHOSITA to recognize how the claimed functionality produces the asserted improvements. Rep. Claim 1 also does not recite a resource reduction technique that results in the asserted benefits. MPEP § 2106.05(a).
The claims GUI limitations are result orientated. Rep. Claim 1 requires icons to be displayed on a GUI, with icon sizes based on relationship score values, spacing based on icon size, and icons automatically moved relative to one another based on icon size. Rep. Claim 1 does not recite how the icon size is calculated and therefore how spacing is calculated, how icon destinations are selected, how icons are moved relative to each other based on size, how overlap is resolved, what layout objective is applied, or any particular rendering, layout, or GUI control technical mechanism or technique. The Specification states only that “the size of the icons, spacing between the icons, etc., are varied based on the level of the relationship, the score, etc.” and “that any graphical representation of the relationship or other data can be presented to the user” (Spec. ¶ 56) without describing a specific GUI technical mechanism or technique.
Accordingly, the claims are distinguishable from eligible claims in USPTO Example 37, which recited “automatically moving the most used icons to a position on the GUI closest to the start icon of the computer system based on the determined amount of use” and identified a particular improvement to a conventional GUI arrangement. The present claims recite only moving icons only “relative to each other” and unlike Example 37, the present Specification does not identify a particular problem in conventional GUI functionality or describe a particular technical solution that addresses that problem. See, Response to Argument point heading supra.
The additional elements do not apply the abstract idea with a particular machine.
Although the claims recite specific hardware components (i.e., a data storage device, computer-readable medium, processor, and GUI), these components are recited at a high functional level and perform only their generic functions of storing, processing, and displaying data. Spec. ¶¶ 23, 67–76. A machine is “particular” only when it imposes a meaningful limit on the claims scope. MPEP § 2106.05(b). Here, any general-purpose computer having storage, a processor, and a display capable of presenting a GUI would satisfy the claim’s hardware requirements, which confirms 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, MPEP § 2106.05(h).
Regarding the additional elements, Applicant’s Specification does not otherwise describe them with specificity beyond exemplary language and instead 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. The specification failure to describe these components in any detail beyond exemplary language is itself an admission that the components are so well known to those of ordinary skill in the art that no explanation is needed under 35 U.S.C. § 112(a). See, Lindemann Maschinenfabrik GMBH v. Am. Hoist & Derrick Co., 730 F.2d 1452, 1463 (Fed. Cir. 1984) (citing In re Myers, 410 F.2d 420, 424 (CCPA 1969) (“[T]he specification need not disclose what is well known in the art”). E.g., Spec. ¶ 23 (describing the computer device 102 as any conceivable computing device), ¶¶ 67–75, Fig. 8 (describing “well known” storge, processor, and computer hardware); ¶¶ 49, 91, Fig. 1 (generic GUI)
The generic processor, here, executes instructions that are programmed by software directed to the abstract idea. Spec. ¶ 67. This is a computer doing what it is designed to do—performing directions it is given to follow, and whose directions are directed to the abstract idea.
The displaying and user interface steps do not provide a practical application because they merely describe the field of use and technical environment in which the abstract idea is implemented, without resulting in an improvement to the computer or GUI itself. MPEP 2106.05(h) (citing Electric Power Group). The specification confirms that the “determined relationships or scores are presented to the user as a graphical representation 152, such as an icon, graph, table, chart, or other graphical representation … textual form and/or graphical form … [and] as audio describing data, relationships, scores, etc.” Spec. ¶ 49. Thus, the Specification teaches the GUI display as a generic GUI for presenting results in no particular way, rather than as particular improvement in GUIs. Further, requiring the use of software to tailor information and provide it to the user on a generic computer also does not provide a practical application. MPEP § 2106.05(f) (citing Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1370-71, 115 USPQ2d 1636, 1642 (Fed. Cir. 2015)).
Limitation A describes the storage device storing data, the medium storing instructions and the processor executing those instructions 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 medium, which merely invokes computers or other machinery in its ordinary capacity to receive, store, or transmit data. MPEP § 2106.05(f)(2). Limitations B–I describe the processor, storage device, medium, and instructions, 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 1 is directed to an abstract idea.
Independent Claim 20 is not substantially different than Rep. Claim 1, recites the same abstract idea as Rep. Claim 1, and contains no additional elements not otherwise analyzed for Rep. Claim 1. Therefore, Independent Claim 20 is also directed to the same abstract idea.
The claims do not provide an inventive concept.
Step 2B: Rep. Claim 1 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 (i.e., A system comprising: a data storage device storing data; a computer-readable medium storing instructions; a processor; a graphical user interface (GUI); and Limitation I), are each recited as generic computer components or generic functions and are each well-understood, routine, and conventional (“WRC”) computer components and functions in the relevant field, as evidenced by Applicant’s own disclosure. The specification describes the computing environment broadly and generically. Further, Applicant’s Specification discloses that “The order of execution or performance of the operations in examples of the disclosure illustrated and described herein is not essential … the operations may be performed in any order … and examples of the disclosure may include additional or fewer operations than those disclosed herein. For example, it is contemplated that executing or performing a particular operation before, contemporaneously with, or after another operation is within the scope of aspects of the disclosure.” Spec. ¶ 97.
A system comprising: a data storage device storing data; a computer-readable medium storing instructions; a processor; a graphical user interface (GUI) is individually WRC. Spec. ¶¶ 23, 67–75.
a graphical user interface (GUI) is individually WRC. The specification describes that the “determined relationships or scores are presented to the user as a graphical representation 152, such as an icon, graph, table, chart, or other graphical representation … textual form and/or graphical form … [and] as audio describing data, relationships, scores, etc.” Spec. ¶ 49. Thus, the Specification teaches the GUI display as a generic GUI for presenting results in no particular way, rather than as particular improvement in GUIs. Accordingly, “on a GUI” as claimed merely invokes a conventional GUI to present the results of the abstract idea.
Limitation I is a result-orientated application of generic processor and display functionality. Limitation I describes only an intended result and does not recite a particular positioning technique, rendering method, or technical mechanism, by which the processor performs the movement. Spec. ¶¶ 56, 91. Thus, Limitation I merely instructs a generic processor and GUI to rearrange displayed information according to a result. Additionally, prior art He et al. (Us. Pat. Pub. No. 2013/0132874) [“He”] is additional evidence that automatically arranging icons on a user interface based on an importance score was WRC at the time of filing the present invention. See Non-Final Office Action mailed Sept. 5, 2025, p.11. Thus, to the extent Limitation I is an additional element, it combines known automated icon arrangement with generic GUI functionality.
The Specification further confirms that the functions of receiving, storing, transmitting, and processing data are normal, well-understood operations of generic computer systems, and the steps may be performed in any order or concurrently. See, e.g., Spec. ¶¶ 67–75, 97.
The combination is also WRC at the high level of generality recited:
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. Rep. Claim 1 combines generic data storage, processor executed information analysis, a generic GUI display environment, and automatic icon rearrangement to present results of the mental process. Rep. Claim 1 does not recite a particular computer architecture, data structure, score formula, spacing rule, layout algorithm, or other nonconventional arrangement of the components. The specification teaches “The order of execution or performance of the operations in examples of the disclosure illustrated and described herein is not essential … the operations may be performed in any order … [and] examples of the disclosure may include additional or fewer operations than those disclosed herein. For example, it is contemplated that executing or performing a particular operation before, contemporaneously with, or after another operation is within the scope of aspects of the disclosure.” Spec. ¶ 97. Thus, the specification does not identify a articular ordered arrangement of the claimed computer components. Accordingly, 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.
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 1 does not recite a nonconventional arrangement of computer components or a specific technical implementation that produces an unconventional result. Rather, the claim invokes conventional storage, processing, display, and automated arrangement functions to implement the menta process. To the extent Applicant asserts that the claim improves computer functioning or reduces system resources, as explained above, these asserted claims are conclusory. The specification does not explain how the claimed comparison of record fields, generation of relationship scores, or score-based icon sizing, display, spacing, and movement changes processor or memory operation, display rendering, or GUI operation to produce those asserted results. Claim 1 also does not recite a resource reduction technique that a PHOSITA would understand results in those asserted benefits. The asserted benefits instead concern “improvements in user interaction (such as improved usability, improved user efficiency, and increased user interaction performance)” (Spec. ¶ 19); allowing “a user to quickly assess the relationships between the different payment cards and/or payment accounts, in a user interface (UI) … improv[ing] user efficiency via the UI interaction and improv[ing] user performance via the UI.” Spec. ¶ 20. “[U]ser interaction performance is also improved via the UIs as described herein. This overall improves the human machine interaction.” Spec. ¶ 22. Those asserted benefits concern a user’s review and understanding of information, rather than a specific improvement to the functioning of a computer. MPEP § 2106.05(a); IBM v Zillow (citation supra)
Independent Claim 20 is a storage device having computer executable instructions stored thereon whose instructions cause a system to perform the same abstract processing and generic computer operations recited in Rep. Claim 1. Independent Claim 20 adds no additional elements beyond those of Rep. Claim 1 that would amount to significantly more than the abstract idea. Therefore, Independent Claim 20 also does 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 and 6–10 all recite “wherein” clauses or limitations that further limit the mental process abstract idea exception of Independent Claim 1 and contain no additional elements. Claims 2 and 6–10 further define the relationship levels (Claim 2) and relationship scores (Claim 6). Claim 8 compares a threshold score with a threshold value and Claim 9 further limits the threshold value of Claim 8 by setting the threshold value after fraud detection. Claims 7 and 102 transmit a relationship score, which merely invokes computers or other machinery in its ordinary capacity to receive, store, or transmit data. MPEP § 2106.05(f)(2). The Specification describes these operations at a high functional level. Spec. ¶¶ 32–41, 49, 55, 60–64. Claims 2 and 6–10 do not recite a particular data structure, scoring formula, threshold adjustment algorithm, or other technical mechanism, that improves computer functionality. An inventive concept or practical application cannot be furnished by an abstract idea exception itself. MPEP §§ 2106.05(I), 2106.04(d)(III).
Dependent Claim 3 recites a “wherein” clause or limitation that further limit the mental process abstract idea exception of Independent Claim 1 and contain no additional elements. Claim 3 generates an audio report in any way. The Specification describes the reports may include results in textual, graphical, or audio form without specifying a technical mechanism. Spec. ¶ 49. At this high level of functionality, generating an audio report is a generic presentation of the results of abstract information analysis using ordinary computer functionality and not an inventive concept. MPEP § 2106.05(a), (f).
Dependent Claim 4 recites a “wherein” clause or limitation that further limit the mental process abstract idea exception of Independent Claim 1 and contains no additional elements. Claim 4 recites comparing the relationship score to a threshold value and determining the score exceeds a threshold value and performing a mitigation action that includes instituting two facto authentication. The comparing and determining steps recite mental evaluations reasonably performed in the human mind or with pen and paper and therefore, recite a mental process exception for the same reason as Rep. Claim 1 supra. The Specification identifies mitigation actions at a high level that include but are not limited to: “blocking a future transaction, sending an alert to a cardholder, freezing a card or account, automatically applying a higher level of authentication to a card or account (e.g., instituting two-factor authentication), flagging a card or account for manual review, training or updating a machine learning model used for fraud analysis, or a combination thereof.” Spec. ¶ 50. The claims do not recite a particular technical mechanism for implementing two factor authentication or an improvement to authentication technology. Universal Secure Registry LLC v. Apple Inc., 10 F.4th 1342, 1358 (Fed. Cir. 2021) (“Thus, nothing in the claims is directed to a new authentication technique; rather, the claims are directed to combining longstanding, known authentication techniques to yield expected additory amounts of security. There is nothing in the specification suggesting, or any other factual basis for a plausible inference (as needed to avoid dismissal), that the combination of these conventional authentication techniques results in an unexpected improvement beyond the expected sum of the security benefits of each individual authentication technique.”).
Dependent Claim 5 recites a “wherein” clause or limitation that further limit the mental process abstract idea exception of Independent Claim 1 and contains no additional elements. Claim 5 recites training a support-vector machine component using historical relationship score samples, inputting the currently generated relationship scores, predicting fraud probabilities, and categorizing those probabilities into severity levels. Claim 5 does not recite any particular support vector machine architecture, algorithm, training technique, or other technical mechanism that improves machine learning technology. Rather Claim 5 invokes a support vector machine at a high functional level as a generic tool to perform the abstract analysis of relationship scores and to produce a fraud related classification (severity level). The Specification teaches in an exemplary fashion a “downstream … machine learning component (e.g., a support vector machine) [ ] trained using labeled samples of historical data of relationship scores.” Spec. ¶ 64. The incoming data of current relationship score values is input to the trained machine learning component to predict a probability that the incoming relationship scores represent fraudulent transactions. The output of the incoming data is classified into different severity levels using the operations described herein.” Spec. ¶ 64. Thus, the SVM, like any model, receives input and provides an output. At this high level of claiming, the claim does not recite a particular improvement to the SVM or machine learning technology, a particular training technique, model architecture, loss function, or other technical mechanism that improves machine learning. Instead, it invokes generic machine learning as a tool to analyze relationship scores. MPEP § 2106.05(f); Recentive Analytics, Inc. v. Fox Corp., 134 F.4th 1205, 1216 (Fed. Cir. 2025) (holding “that patents that do no more than claim the application of generic machine learning to new data environments, without disclosing improvements to the machine learning models to be applied, are patent ineligible under § 101”).
Dependent Claim 11 recites a “wherein” clause or limitation that further limit the mental process abstract idea exception of Independent Claim 1 and contains the additional element of: interface user device 150 and generate a graphical repreparation of a network of cards. The specification’s does not describe the user interface device except by function and is itself an admission that the component is so well known to those of ordinary skill in the art that no explanation is needed under 35 U.S.C. § 112(a). See, Lindemann Maschinenfabrik GMBH v. Am. Hoist & Derrick Co., 730 F.2d 1452, 1463 (Fed. Cir. 1984) (citing In re Myers, 410 F.2d 420, 424 (CCPA 1969) (“[T]he specification need not disclose what is well known in the art”). Spec. ¶ 49, Fig. 1. The specification further describes the generate function at a high level for the same reasons as the GUI functions of Rep. Claim 1, supra. Spec. ¶¶ 49, 56, 91. At this high level of functionality, generating a graphical representation is a generic presentation of the results of abstract information analysis on a generic user interface using ordinary computer functionality and not an inventive concept. MPEP § 2106.05(a), (h).Conclusion
Claims 1–11 and 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 1 otherwise styled as another statutory category is subject to the same analysis.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1, 2, 6, 7, 8, 11 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Jastrebski et al. (U.S. Pat. Pub. No. 2010/0169137) [“Jastrebski”] in view of White et al. (U.S. Pat. Pub. No. 2017/0285911) [“White”]
Regarding Claim 1, Jastrebski discloses:
A system operable to identify relationships between records, the system comprising:
(See at least ¶ 36, “systems and methods are illustrated that allows users to analyze data using a graph. In some instances that data may be descriptive of accounts and relationships between those accounts in real time.” See also, Fig. 1.
a data storage device storing data corresponding to a plurality of records, the data related to different consumer cards; and
(See at least ¶ 37, “transaction information that is stored in respective transaction databases. The transaction information may include account information that describes accounts. Further, the transaction information may include account associations that may be used to describe the associations between accounts. For example, an association between two accounts may include a transaction that includes a flow of money from one account to another account. The aggregating server may retrieve the transaction information from the various transaction databases and store the transaction information as aggregated transaction information in an aggregated transaction database. Accordingly, the aggregated transaction information may include the account information and the account associations.” ¶ 57, “aggregated transaction information 650 may include information for an account including the name of a person (e.g., legal or natural) that is responsible for the account, a social security number, a credit card number” See also, Fig. 1, Fig. 18, ¶ 116.)
a computer-readable medium storing instructions that are operative upon execution by a processor to:
(See at least Claim 23, “Using one or more processors to execute instructions retained in machine readable media to perform at least some of the portion of the following actions:” See also, Fig. 18, ¶ 117.)
access the data stored in the data storage device;
(See at least ¶ 37, “The aggregating server may retrieve the transaction information from the various transaction databases and store the transaction information as aggregated transaction information in an aggregated transaction database.”)
compare data fields of the data to identify one or more matches between the plurality of records, wherein the one or more matches comprises a locality match, a shipping address match, an email match, a device match, or a combination thereof;
(See at least ¶ 37, “For example, an association between two accounts may include a transaction that includes a flow of money from one account to another account … The account association may include a transaction between a pair of accounts or links between accounts. For example, a link may include an email address, credit card number, or telephone number that is common to a pair of accounts (e.g., linked accounts).” ¶ 57, “aggregated transaction information 650 may include information for an account including the name of a person (e.g., legal or natural) that is responsible for the account, a social security number, a credit card number, an email address, a telephone number, an account balance, an address. Further, the aggregated transaction information 650 may include a history of transactions associated with an account.” See also ¶ 60, Fig 1. identify other accounts that are associated with the seed account, a link may include an email address)
determine a plurality of relationships between the plurality of records based at least on the identified one or more matches;
(See at least ¶ 37, “Next, the graph engine may identify other accounts that are associated with the seed account based on the account associations in the aggregated transaction information.” Accounts may be related through transactions or links including common email addresses, credit card numbers or telephone numbers. First level accounts and second level accounts.)
Jastrebski does not disclose but White discloses:
for each of the determined plurality of relationships, generate a relationship [relevance] score;
(See at least ¶ 47, “Scoring engine 132 (see FIG. 1) may process the data elements to determine the relevance between the data elements. In such an example, scoring engine 132 may identify an association between the data elements, and assign a relevance score to the association between the data elements.” ¶ 48, “When a relevance score is assigned to an association between data elements in this manner, the association between the data elements may be referred to as a weighted association.”)
represent the generated relationship scores as icons associated with the plurality of records;
(See at least ¶ 5, “The system further includes a Graphical User Interface (GUI) that displays a first window to the user, and displays data element icons for the data elements in the initial set within the first window. The visual properties of the data element icons within the first window indicate the magnitude of the initial score of the data elements in the initial set.” ¶ 49, “Front end module 112 will identify data elements that are relevant to the anchor, and graphically display the data elements that are relevant to the anchor so that their relevance to the anchor is visually apparent to user 118. For example, front end module 112 may display the data elements having the most relevance in a bigger size than the data elements having the least relevance. That way, user 118 can "see" the relevance of the data elements to the anchor. An exemplary method of operating front end module 112 is further illustrated in FIG. 3.” ¶ 55, “GUI 122 may display data element icons in different sizes based on the relevance scores. In an example, for data elements that have the largest relevance score, GUI 122 may display their data element icons in the largest size. As the relevance scores become weaker for data elements, GUI 122 may display their data element icons in a smaller size.”)
adjust a size of each icon based on a value of a relationship score associated with the icon;
(See at least ¶ 55, “GUI 122 may display data element icons in different sizes based on the relevance scores. In an example, for data elements that have the largest relevance score, GUI 122 may display their data element icons in the largest size. As the relevance scores become weaker for data elements, GUI 122 may display their data element icons in a smaller size.” ¶ 57, “Because data element icons 502-507 are the largest, data elements (DE) 10-15 have the strongest association with data element 1. Because data element icons 508-511 are smaller, data elements (DE) 16-19 have a weaker association with data element 1.”
display the icons on a graphical user interface (GUI), wherein spacings between the icons are adjusted based on the size of each icon; and
(See at least ¶ 5, “The system further includes a Graphical User Interface (GUI) that displays a first window to the user, and displays data element icons for the data elements in the initial set within the first window. ¶ 55, “GUI 122 may display data element icons in different sizes based on the relevance scores.” ¶ 58, “There may not be room in results window 500 to show all of the data element icons the same distance from anchor icon 501, even though their corresponding data elements have the same relevance scores. Thus, a combination of size and position may be used to indicate relevance.” ¶ 63, “GUI 122 may maintain the size of data element icons 509-511 within results window 600 to indicate the relevance of the data elements in the adjusted relevant set to the initial anchor set (i.e., data element 1). GUI 122 may vary a position of the data element icons 509-511 in relation to anchor icon 601 to indicate the relevance of the data elements in the adjusted relevant set to the modified anchor set. In FIG. 5, for instance, GUI 122 displays the data element icons 509-511 for data elements 17-19 at a certain size in results window 500 to indicate the relevance of data elements 17-19 to the initial anchor set. In FIG. 6, GUI 122 maintains the size of data element icons 509-511, but adjusts the position of data element icons 509-511 within results window 600 to indicate the relevance of data elements 17-19 to the modified anchor set.”)
automatically move the icons on the GUI, relative to each other, based on the size of each icon.
(See at least ¶ 55, “GUI 122 may display data element icons in different sizes based on the relevance scores. In an example, for data elements that have the largest relevance score, GUI 122 may display their data element icons in the largest size. As the relevance scores become weaker for data elements, GUI 122 may display their data element icons in a smaller size.” ¶ 63, “GUI 122 may maintain the size of data element icons 509-511 within results window 600 to indicate the relevance of the data elements in the adjusted relevant set to the initial anchor set (i.e., data element 1). GUI 122 may vary a position of the data element icons 509-511 in relation to anchor icon 601 to indicate the relevance of the data elements in the adjusted relevant set to the modified anchor set. In FIG. 5, for instance, GUI 122 displays the data element icons 509-511 for data elements 17-19 at a certain size in results window 500 to indicate the relevance of data elements 17-19 to the initial anchor set. In FIG. 6, GUI 122 maintains the size of data element icons 509-511, but adjusts the position of data element icons 509-511 within results window 600 to indicate the relevance of data elements 17-19 to the modified anchor set.”)
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 for each of the determined plurality of relationships, generate a relationship score; represent the generated relationship scores as icons associated with the plurality of records; adjust a size of each icon based on a value of a relationship score associated with the icon; display the icons on a graphical user interface (GUI), wherein spacings between the icons are adjusted based on the size of each icon; and automatically move the icons on the GUI, relative to each other, based on the size of each icon, as taught by White, to the known invention of Jastrebski, in the same field of invention, with the motivation to “assist[ ] a user in navigating through large collections of data” (White ¶ 1) by improving the graphical presentation of account relationships by visually conveying the strength of each relationship to assist the user in identifying the most relevant account relationships in Jastrebski’s graph. Jastrebski, ¶ 37; White ¶¶ 47, 55.
Regarding Claim 2, Jastrebski and White disclose:
The system of claim 1,
Jastrebski further discloses:
wherein a plurality of relationship levels associated with the plurality of relationships
(See at least ¶ 37, “The transaction information may include account information that describes accounts. Further, the transaction information may include account associations that may be used to describe the associations between accounts. … a graph may be generated a configured number of levels deep. For example, a seed account may be connected by edges to a first level of accounts and the first level of accounts may be connected to a second level of accounts.”)
Jastrebski does not disclose but White discloses:
the plurality of relationships is a function of a number of matches between the plurality of records, and a value of relationship level increases as the number of matches between the plurality of records increases.
(See at least ¶ 46, “The relationship may be determined based on common attributes between the data elements.” The data elements may be, ¶ 46 “a record for an employee, then this data element may have a relationship with other data records for employees within the same department.” Different quantities of shared attributes correspond to different degrees of association strength. ¶ 47, “If the employee indicated in data element 10 and the employ ees indicated in data elements 17-18 work on the same team, in the same department, and in the same division of the company, then a high relevance score may be assigned to the associations between data element 10 and data elements 17-18. If the employee indicated in data element 10 and the employees indicated in data elements 19-20 work in the same department and in the same division of the company (but not on the same team), then a lower relevance score may be assigned to the associations between data element 10 and data elements 19-20. If the employee indicated in data element 10 and the employee indicated in data element 21 work in the same division of the company (but not on the same team or same department), then an even lower relevance score may be assigned to the association between data element 1 and data element 21.” ¶ 76, “By comparing window 1300 to window 1400, it is clear that data element 10 (in FIG. 13) has more "links" or associations with data element 1 (the anchor set) than does data element 18 (in FIG. 14). Because of this, data element 10 will have a higher relevance score than data element 18. As can be seen in FIG. 12, the higher relevance score of data element 10 is visually represented by data element icon 502 being large in size and close in proximity to anchor icon 501. The lower relevance score of data element 18 is visually represented by data element icon 510 being smaller in size and further from anchor icon 501 as compared to data element icon 502.” The relevance score is a numerical value of association strength. ¶ 47.
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 2.
Regarding Claim 6, Jastrebski and White disclose:
The system of claim 1, the relationship score
Jastrebski further discloses:
wherein the relationship score relates to a task corresponding to at least one of a fraud risk, a return risk, an affluence score, a credit bust- out risk, leaked card reporting, or a loyalty program.
(See at least ¶ 59, “ A high score may indicate a high likelihood of fraudulent activity and a low score may indicate a low likelihood of fraudulent activity.”)
Regarding Claim 7, Jastrebski and White disclose:
The system of claim 1, the instructions are operative to [perform functions], the relationship score
Jastrebski further discloses:
transmit the relationship score to a downstream application.
(See at least ¶ 60, “The graph information 680 includes account information 652, account associations 682, account metrics 684, graph metrics 686, graph metadata 688, and a score 690.” ¶ 37, “The graph engine may store the graph in a graph queue according to the score. Finally, the graph engine may retrieve the graph from the graph queue according to the score, select an agent from a group of agents, and communicate an interface that includes the graph to the agent.” ¶ 68, “At operation 780, the graph display module 626 renders the graph information 680 as a graph on an interface 782 and communicates the interface 782 to the agent.” See also Fig. 8A, [0059], review queue 676.)
Regarding Claim 8, Jastrebski and White disclose:
The system of claim 1, the instructions are operative to [perform functions], the relationship score
Jastrebski further discloses:
(See at least ¶ 59, “A high score may indicate a high likelihood of fraudulent activity and a low score may indicate a low likelihood of fraudulent activity” ¶ 109, “the graph engine 620 may automatically restrict an account based on a predetermined threshold.”
Regarding Claim 11, Jastrebski and White disclose:
The system of claim 8, the instructions are operative to [perform functions], determined plurality of relationships, wherein the graphical representation includes the icons
Jastrebski further discloses:
a user interface device [user interface 782]
(See at least ¶ 68)
wherein the instructions are further operative to: generate a graphical representation of a network of cards based on the determined plurality of relationships, wherein the graphical representation includes the icons.
(See at least Fig. 11, ¶¶ 37, 68, 116, graph information 680 rendered as a graph on an interface 782.)
Regarding Claim 20, Jastrebski discloses:
One or more computer storage devices having computer-executable instructions stored thereon, which, upon execution by a computer, cause the computer to perform operations comprising:
(See at least Claim 23, “Using one or more processors to execute instructions retained in machine readable media to perform at least some of the portion of the following actions:” See also, Fig. 18, ¶ 117.)
Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Jastrebski and White and further in view of Subramanian et al. (U.S. pat. Pub. No. 2015/0112756) [“Subramanian”]
Regarding Claim 3, Jastrebski and White disclose:
The system of claim 1, the instructions are operative to [perform functions], determined relationships and generated relationship scores … for use by a user
Jastrebski does not disclose but Subramanian discloses:
generate an audio report … in audio form for use by a user.
(See at least ¶ 43, “User interface layer 110 receives the results and presents the results visually, audibly, or both.”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Jastrebski as modified by White that determines relationships between records and generating relationship scores to audibly present the determined account relationships and their relationship scores, as taught by Subramanian, in the same field of invention, so that the determined account relationships and their relationship scores could be communicated to a user without relying exclusively on visual examination of the graphical interface, for a user who, for example, may be visually impaired.
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Jastrebski and White and further in view of Zager et al. (U.S. pat. Pub. No. 2018/0295137) [“Zager”]
Regarding Claim 4, Jastrebski and White disclose:
The system of claim 1, the instructions are further operative to [perform operations], and the generated relationship score
Jastrebski further discloses:
compare the generated relationship score to a threshold value [predetermined threshold]; determine that the generated relationship score exceeds the threshold value; and perform a mitigation action [restrict an account],
(See at least ¶ 60, “The score 690, in one embodiment, may indicate a likelihood of fraudulent activity. For example, a high score may indicate a high likelihood of fraudulent activity and a low score may indicate a low likelihood of fraudulent activity.” ¶ 109, the graph engine 620 may automatically restrict an account based on a predetermined threshold.”
Jastrebski discloses a mitigation action for a transaction but does not disclose the mitigating action is 2FA. Thus, Jastrebski does not disclose but Zager discloses:
wherein the mitigation action includes instituting a two- factor-authentication for a transaction.
(See at least ¶ 27, “these added authentication functions can be of a type that require user presence at the client login device (e.g., using any of the traditional factors of knowledge, possession and inherence) at points related to system processing or session processing (e.g., invoked dynamically when a user seeks to take an action within an application, such as accessing memory, or within a session, such as transferring bank funds); these examples are non-limiting. Thus, for example, although a user might have instantiated a data processing session, at a predetermined step or steps in a data processing activity, the user can be dynamically required to perform an authentication task (e.g., a 2FA task) to demonstrate that the user is in geographic proximity to a specific computer system and/or a client login device at that moment.” )
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Jastrebski’s threshold based fraud mitigation, as modified by Whites’s relationship specific association’s score, to apply Zager’s known 2FA when the relationship score satisfies the predetermined fraud threshold. Zager teaches dynamically requiring 2FA for a required action within a session, including transferring bank funds and allowing or terminating the requested activity based on the authentication outcome. Zager, ¶ 27. Applying Zager’s increased authentication technique to Jastrebski’s high fraudulent activity would have predictably improved transaction security by requiring additional verification before allowing a suspicious transaction.
Claims 9 and 10 are rejected under 35 U.S.C. 103 as being unpatentable over Jastrebski and White and further in view of Hanis et al. (U.S. Pat. Pub. No. 2020/0250743 [“Hanis”]
Regarding Claim 9, Jastrebski and White disclose:
The system of claim 8, the instructions are further operative to [perform operations], and the threshold value
Jastrebski further discloses:
wherein the instructions are further operative to: [ ] set the threshold value based on a fraud detection occurring after a prediction.
(See at least Fig. 7A, ¶ 52, machine learning engine 634; ¶ 109, threshold, fraud.)
Jastrebski does not specifically disclose dynamically set the threshold value based on a fraud detection occurring after a prediction.
dynamically set the threshold value
(See at least ¶ 33, “By using the machine learning model instead of predefined rules or thresholds, the factors and thresholds in making the determination of whether there is an increase or decrease risk of fraud can be dynamically altered by the machine learning model, without user intervention, as additional data is analyzed/applied to the machine learning model.”
It would have been obvious to a person of ordinary skill in the art before the time of effective filing to modify the threshold and ML of Jastrebski as modified by White to include the dynamic threshold of Hanis so that a fraudulent account may be identified as disclosed in Hanis, ¶ 33, and Jastrebski, ¶ 37. Further, it would have been obvious to one of ordinary skill in the art before the time of effective filing to include the features as taught in Hanis in Jastrebski as modified by White since the claimed invention is merely a combination of old elements, and in combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Additionally, all three are in the field of identifying data relationships and one of ordinary skill in the art would recognize the combination to be predictable.
Regarding Claim 10, Jastrebski and White disclose:
The system of claim 8, the instructions are further operative to [perform operations], and the relationship score
Jastrebski further discloses:
transmit the relationship score to a learnable model to determine the threshold value.
(See at least Fig. 7A, ¶ 52, machine learning engine 634 generates score; ¶ 109, threshold, fraud.
Jastrebski and White do not specifically disclose but Hanis discloses:
transmit the relationship score to a learnable model to determine the threshold value
(See at least ¶ 24, “Machine learning model 250 is a mathematical model created using a machine learning algorithm and training dataset. For example, in some embodiments, the machine learning algorithm can be configured to analyze features generated from real financial data related to customer accounts and/or communities that have been proven to be associated with financial fraud. … the machine learning model 250 can then be used to compare and analyze new financial data associated with customer accounts and/or communities to determine the likelihood of financial fraud for the customer accounts and/or communities.” This is a learnable model. ¶ 33, “By using the machine learning model instead of predefined rules or thresholds, the factors and thresholds in making the determination of whether there is an increase or decrease risk of fraud can be dynamically altered by the machine learning model, without user intervention, as additional data is analyzed/applied to the machine learning model.” Thus, a learnable model that alters fraud evolution thresholds dynamically as it uses additional data. ¶ 20, “the financial information can include a fraud score generated by a financial institution indicating a potential level fraud associated with a customer account.” See also ¶¶ 33, 34 disclosing dynamically adjusting thresholds using additional data input related to fraud into a machine learning model and data includes a fraud score.
It would have been obvious to a person of ordinary skill in the art before the time of effective filing to modify the score and ML of Jastrebski as modified by White to include the dynamic threshold of Hanis so that a fraudulent account may be identified as disclosed in Hanis, ¶ 33, and Jastrebski, ¶ 37)
Examiner Statement of Prior Art—No Prior Art Rejection Claim 5
Claim 5 is not rejected under 35 U.S.C. § 103. Based on the prior art search results conducted to date, the references reviewed, including Zoldi et al (U.S. Pat Pub. No. 2022/0155782) and NPL: Leskovec, Jure, Anand Rajaraman, and Jeffrey David Ullman. "Mining of Massive Datasets." (2019), do not anticipate or render obvious the claimed subject matter of Claim 5. Specifically, the references reviewed do not disclose or suggest: “each labeled sample having a relationship score and a corresponding probability value representing a probability that a transaction associated with that labeled sample was a fraudulent transaction” and “categorize the probabilities of the fraudulent transactions into different severity levels based on values of the probabilities.” Zoldi discloses labeled fraud events, score/ probability concepts, and threshold-based score processing but does not teach or suggest the score/value pair and the categorization of fraud probabilities into different severity levels. NPL Leskovec discloses SVM classification based on labeled feature ventures but does not cure these deficiencies.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JAMES H MILLER whose telephone number is (469)295-9082. The examiner can normally be reached M-F: 10- 4 PM (EST).
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/JAMES H MILLER/ Primary Examiner, Art Unit 3694
1 Statements of intended use fail to limit the scope of the claim under BRI. MPEP § 2103(I)(C).
2 Claim 10 element “to determine the threshold value” is intended use because it describes the purpose of the function being claimed (i.e., transmit the relationship score). Accordingly, statements of intended use fail to limit the scope of the claim under BRI. MPEP § 2111.04.
Prosecution Insights