International Business Machines Corporation et al.Download PDFPatent Trials and Appeals BoardJan 21, 20212020005370 (P.T.A.B. Jan. 21, 2021) Copy Citation UNITED STATES PATENT AND TRADEMARK OFFICE UNITED STATES DEPARTMENT OF COMMERCE United States Patent and Trademark Office Address: COMMISSIONER FOR PATENTS P.O. Box 1450 Alexandria, Virginia 22313-1450 www.uspto.gov APPLICATION NO. FILING DATE FIRST NAMED INVENTOR ATTORNEY DOCKET NO. CONFIRMATION NO. 14/862,656 09/23/2015 Suresh N. Chari YOR920150355US2 1368 35526 7590 01/21/2021 DUKE W. YEE YEE & ASSOCIATES, P.C. P.O. BOX 6669 MCKINNEY, TX 75071 EXAMINER SHAIKH, MOHAMMAD Z ART UNIT PAPER NUMBER 3694 NOTIFICATION DATE DELIVERY MODE 01/21/2021 ELECTRONIC Please find below and/or attached an Office communication concerning this application or proceeding. The time period for reply, if any, is set in the attached communication. Notice of the Office communication was sent electronically on above-indicated "Notification Date" to the following e-mail address(es): ptonotifs@yeeiplaw.com PTOL-90A (Rev. 04/07) UNITED STATES PATENT AND TRADEMARK OFFICE ____________ BEFORE THE PATENT TRIAL AND APPEAL BOARD ____________ Ex parte SURESH N. CHARI, TED A. HABECK, COENRAAD JAN JONKER, FRANK JÖRDENS, IAN M. MOLLOY, YOUNGJA PARK, CORNELIS VAN SCHAIK, and MARK EDWIN WIGGERMAN Appeal 2020-005370 Application 14/862,656 Technology Center 3600 ____________ Before RICHARD M. LEBOVITZ, TAWEN CHANG, and RACHEL H. TOWNSEND, Administrative Patent Judges. LEBOVITZ, Administrative Patent Judge. DECISION ON APPEAL The Examiner rejected the claims under 35 U.S.C. § 103 as obvious and under 35 U.S.C. § 101 as lacking patent eligibility. Pursuant to 35 U.S.C. § 134(a), Appellant1 appeals from the Examiner’s decision to reject the claims. We have jurisdiction under 35 U.S.C. § 6(b). We AFFIRM and set forth a new ground of rejection pursuant to 37 C.F.R. § 41.50(b). 1 We use the word “Appellant” to refer to “applicant” as defined in 37 C.F.R. § 1.42. Appellant identifies the real party in interest as International Business Machines Corporation. Appeal Br. 2. Appeal 2020-005370 Application 14/862,656 2 STATEMENT OF THE CASE The Examiner rejected claims 1, 2, 4–8, 10–12, and 18–20 in the Final Office Action as follows: Claims 1, 2, 4–8, 10–12, and 18–20 under 35 U.S.C § 103(a) as obvious in view of Jastrebski et al. (US 2010/0169137 A1, published July 1, 2010) (“Jastrebski”) and Choudhuri et al. (US 2013/0024361 A1, published Jan. 24, 2013) (“Choudhuri”). Final Act. 59. Claims 10–12 under 35 U.S.C § 103(a) as obvious in view of Jastrebski, Choudhuri, and Shi et al. (US Patent 9,563,921, B2, published Feb. 7, 2017) (“Shi”). Final Act. 69. Claims 1, 2, and 4–20 under 35 U.S.C. § 101 “because the claimed invention is directed to an abstract idea without significantly more.” Final Act. 53. Claim 1 is representative and reproduced below, with annotations added to number the steps in the claim: 1. A computer-implemented method for identifying fraudulent transactions, the computer-implemented method comprising: [1] obtaining, by a data processing system, transactions data corresponding to a plurality of transactions between accounts from one or more different transaction channels; [2] generating, by the data processing system, at least one graph of transaction payment relationships between the accounts from the transaction data; [3] extracting, by the data processing system, features from the at least one graph of transaction payment relationships between the accounts; [4] generating, by the data processing system, a fraud score for a current transaction based on the extracted features from the at least one graph of transaction payment relationships between the accounts; Appeal 2020-005370 Application 14/862,656 3 [5] comparing, by the data processing system, the generated fraud score for the current transaction to a fraudulent transaction threshold value to determine a level of suspicion regarding the current transaction; and [6] responsive to the data processing system determining that the current transaction is fraudulent, blocking, by the data processing system, the current transaction from being completed. The claimed computer-implemented method obtains data about payment transactions (step [1]), generates a graph of the transactions (step [2]; see Spec., Fig. 3 for an exemplary graph), and extracts features from the graph of the payment transactions (step [3]). The features can be the number of accounts involved in a payment transaction, the monetary value of a payment transaction, and the amount of money flowing from one account to another, etc. Spec. ¶ 77. In step [4] of the claim, a “fraud score” is generated for a “current transaction” based on the extracted features. The score is compared “to a fraudulent transaction threshold value to determine a level of suspicion regarding the current transaction” (step [5]), and the transaction is blocked when the transaction is determined to be fraudulent (step [6]). REJECTION BASED ON SECTION 103 The Examiner found that Jastrebski describes a computer- implemented method for identifying fraudulent activity in an account using a “graph of transaction payment relationships between the accounts” as recited in step 2 of claim 1, extracting features from the graph to identify a fraud score, and comparing to a threshold to determine “good” and “bad” transactions. Final Act. 59–61. The Examiner found that Jastrebski does not disclose step 6 of the claim which recites “determining that the current Appeal 2020-005370 Application 14/862,656 4 transaction is fraudulent, [and then] blocking, by the data processing system, the current transaction from being completed.” However, the Examiner found that Choudhuri describes this step of the claim. Final Act. 61. The Examiner found it would have been obvious to one of ordinary skill in the art to modify Jastrebski to include responsive to the data processing system determining that the current transaction is fraudulent, blocking, by the data processing system, the current transaction from being completed in order to ensure that the multi stage filtering process allows the server capacity to be dynamically adjusted for supporting fraud detection services [as described in Choudhuri]. Final Act. 61. Appellant argues that the Examiner erred in finding that Jastrebski describes generating a fraud score for a “current transaction” as required by steps 4–6 of claim 1. Appeal Br. 35. Instead, citing specific disclosure in Jastrebski, Appellant explains that the fraud score is for a graph of transactions in accounts and that the analysis described in Jastrebski to obtain that score is performed on transactions that have already taken place. Id. at 38. The Examiner responds by citing paragraphs 36, 38, 44, 60, and 86 from Jastrebski, asserting that these disclosures generate a score for a current transaction. Ans. 53–54. We have reviewed these passages, and as explained by Appellant, all the disclosures cited by the Examiner are for the construction of a graph of past transactions in accounts, i.e., transactions that have already occurred, and then generating a score for the graph of these past transactions. For example, Jastrebski discloses: Appeal 2020-005370 Application 14/862,656 5 The node 880 is connected to the other nodes with edges 892, 894, 896, 898, and 900. The edges 892, 894, and 896 are directed edges and represent transactions. For example, the edge 892 represents a flow of money from the node 880 to node 882. The width of the edge visually highlights a greater amount of money in comparison with the edges 894 and 896. For example, the edge 892 may represent a transfer of $100.00 USD. Further for example, the edge 894 represents a flow of money from the node 884 to the node 880. The width of the edge visually highlights a lesser amount of money in comparison with the edge 892. For example, the edge 894 may represent a transfer of $50.00 USD. The edge 896 represents a flow of money from the node 880 to the node 886. The width of the edge visually highlights a lesser amount of money in comparison with the edge 892 and the edge 894. For example, the edge 896 may represent a transfer of $25.00 USD. The edge 898 and 900 represent links that respectively connect the node 880 the nodes 890 and 888. Jastrebski ¶ 86. Jastrebski describes generating a score for the graph: “Further, the machine learning engine 634 may generate a score 690 shown in FIG. 8B for the graph being analyzed based on the presence of a matching graph in the un-ranked graph criteria 702.” Jastrebski ¶ 62. It is clear from this disclosure Jastrebski is graphing transactions that have already taken place. Thus, we agree with Appellant that the Examiner erred in finding that Jastrebski describes generating a fraud score for a current transaction as recited in step 4 of claim 1. However, as discussed by the Examiner, Choudhuri describes analyzing current transactions for fraud. Final Act. 61. Choudhuri specifically discloses: In accordance with embodiments of the invention, the term “filtration” or “filter” refers to the means or the process of analyzing aspects of a financial transaction to evaluate the Appeal 2020-005370 Application 14/862,656 6 possibility of fraud associated with the transaction. A “filtration stage” is a stage in a multi-stage process wherein the possibility of fraud associated with a transaction is evaluated. After each filtration stage, the transaction is either deemed to be acceptable to process, the transaction is evaluated by a subsequent filtration stage, the transaction is declined, or other fraud related actions are taken to mitigate additional fraud in the future. Choudhuri ¶ 42 (emphasis added). In accordance with embodiments of the invention, a “fraud alert” is a notification that the multi-stage fraud detection process has deemed a transaction to be potentially fraudulent. The alert may be a notification of any type to any party including the financial institution customer, an employee of the financial institution, the potential payee of the transaction, etc. The term “fraud-detection action” is an action that may be taken when a transaction is identified as fraudulent and/or potentially fraudulent. The action may include sending a fraud alert, flagging a transaction as fraudulent, preventing a transaction from occurring, accessing additional information to further filter the transaction for potential fraud, etc. Choudhuri ¶ 43 (emphasis added). The difference between Jastrebski and Choudhuri is that Jastrebski uses a graph of relationships (see Jastrebski, Figs. 13A–C, Fig. 15) to extract features to determine whether there was past fraud in the account (Jastrebski ¶ 38: “In one embodiment, the graph engine may utilize account metrics to identify the status of the account. If the graph engine identifies the account is ‘GOOD,’ then the graph engine may effectively prune off a part of a graph from further analysis.”). Choudhuri does not use a graph, but Choudhuri does use past transactions to determine whether a current transaction is fraudulent, but does not map the transactions to a graph as does Jastrebski. Choudhuri teaches: Appeal 2020-005370 Application 14/862,656 7 The fraud investigator filtering process 230 may be the same as or similar to the pre-filtering stage or stages. However, instead of pre-filtering the fraud investigator may set up specialized rules to examine the potentially fraudulent transaction on a customer level instead of a transaction level. For example, the fraud investigator may set up rules to look at all of the events related to the customer, such as transaction information (i.e. amount, the payee, the location, the channel, the date and/or time, etc.), customer behavior information (i.e. customer history, velocity data, etc.), account events (i.e. non-monetary account data, etc.), customer information (i.e. customer profile information, customer fraud preferences, type of customer, preferred customer, etc.). In this way the fraud investigator may determine if potential fraud exists, the likelihood that fraud exists, etc. based on the experience of the fraud investigator and an omniscient view of the customer as a whole as opposed to a narrow view of just the transaction. Choudhuri ¶ 68 (emphasis added). Choudhuri blocks a transaction identified as fraudulent: Once the fraud investigator filtering process 230 analyzes the transaction in view of the overall customer, the process 200 moves to decision block 225. If the transaction is deemed to not likely be fraudulent, the transaction related to the customer is processed, as illustrated at block 250. . . . However, if the transaction is determined to be fraudulent, the transaction may be declined, as represented at block 260 and a fraud alert may be generated as noted at block 270. Choudhuri ¶ 69. It would have been obvious to one of ordinary skill in the art to apply Jastrebski’s relationship graphing analysis to detect whether a current transaction is fraudulent, in place of the filtering process described in Choudhuri, for its expected benefit in identifying a current fraudulent transaction. Choudhuri explicitly describes looking at “all of the events related to the customer” (Choudhuri ¶ 68; as reproduced above) in Appeal 2020-005370 Application 14/862,656 8 identifying whether a current transaction is fraudulent, making it obvious to apply Jastrebski’s graphing analysis of looking at customer accounts to the detection of fraudulent activity of a current transaction. Jastrebski specifically looks for “risky” transactions in the graph (at ¶ 81) and uses “the account metric” to “indicate an unusual purchase, unusual amount of purchase, or an unusual location of purchase” (at ¶ 106) and thus looks at individual transactions in the graph, providing further reason to look at a current transaction, as described in Choudhuri, using Jastrebski graphing technique. Summary Because we find that the Examiner erred in finding that Jastrebski describes generating a fraud score for a current transaction as recited in claim 1 (e.g., step 4), we reverse the obviousness rejections as expressed by the Examiner of all the claims. However, as explained above, we find, for different reasons than the Examiner, that the combination of Jastrebski and Choudhuri makes claim 1 obvious. A new ground of rejection under 37 C.F.R. § 41.50(b) is therefore set forth for claim 1. We leave it to the Examiner to determine whether the rejection is applicable to the other independent and dependent claims. REJECTION BASED ON 101 Principles of Law Under 35 U.S.C. § 101, an invention is patent-eligible if it claims a “new and useful process, machine, manufacture, or composition of matter.” However, not every discovery is eligible for patent protection. Diamond v. Appeal 2020-005370 Application 14/862,656 9 Diehr, 450 U.S. 175, 185 (1981). “Excluded from such patent protection are laws of nature, natural phenomena, and abstract ideas.” Id. The Supreme Court articulated a two-step analysis to determine whether a claim falls within an excluded category of invention. Alice Corp. v. CLS Bank Int’l, 573 U.S. 208 (2014); Mayo Collaborative Servs. v. Prometheus Labs., Inc., 566 U.S. 66, 75–77 (2012). In the first step, it is determined “whether the claims at issue are directed to one of those patent-ineligible concepts.” Alice, 573 U.S. at 217. If it is determined that the claims are directed to an ineligible concept, then the second step of the two-part analysis is applied in which it is asked “[w]hat else is there in the claims before us?” Id. (alteration in original). The Court explained that this step involves a search for an “‘inventive concept’”—i.e., an element or combination of elements that is “sufficient to ensure that the patent in practice amounts to significantly more than a patent upon the [ineligible concept] itself.” Alice, 573 U.S. at 217–18 (alteration in original) (citing from Mayo, 566 U.S. at 75–77). Alice, relying on the analysis in Mayo of a claim directed to a law of nature, stated that in the second part of the analysis, “the elements of each claim both individually and ‘as an ordered combination’” must be considered “to determine whether the additional elements ‘transform the nature of the claim’ into a patent-eligible application.” Alice, 573 U.S. at 217. The PTO published revised guidance on the application of 35 U.S.C. § 101, USPTO’s January 7, 2019 Memorandum, 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50 (Jan. 7, 2019) (“2019 Appeal 2020-005370 Application 14/862,656 10 Eligibility Guidance”) (we cite to Federal Register where the 2019 Eligibility Guidance was published). This guidance provides additional direction on how to implement the two-part analysis of Mayo and Alice. Step 2A, Prong One, of the 2019 Eligibility Guidance looks at the specific limitations in the claim to determine whether the claim recites a judicial exception to patent eligibility. In Step 2A, Prong Two, the claims are examined to identify whether there are additional elements in the claims that integrate the exception in a practical application, namely, whether there is a “meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the judicial exception.” 84 Fed. Reg. 54 (Prong Two). If the claim recites a judicial exception that is not integrated into a practical application, then as in the Mayo/Alice framework, Step 2B of the 2019 Eligibility Guidance instructs us to determine whether there is a claimed “inventive concept” to ensure that the claims define an invention that is significantly more than the ineligible concept itself. 84 Fed. Reg. 56. With these guiding principles in mind, we proceed to determine whether the claimed subject matter in this appeal is eligible for patent protection under 35 U.S.C. § 101. Discussion Claim 1 is directed to a computer-implemented method for identifying fraudulent transactions. A method is also a “process,” one of the statutory categories of patent-eligible subject matter under 35 U.S.C. § 101. Because the claim falls into one of the statutory categories of patent-eligible subject matter, we proceed to Step 2A, Prong One, of the Eligibility Guidance. Appeal 2020-005370 Application 14/862,656 11 Step 2A, Prong One In Step 2A, Prong One, of the 2019 Eligibility Guidance, the specific limitations in the claim are examined to determine whether the claim recites a judicial exception to patent eligibility, namely whether the claim recites an abstract idea, law of nature, or natural phenomenon. The Examiner found that the claims cover the performance of “certain methods of organizing human activity,” which is one of the groupings of abstract ideas listed in the 2019 Eligibility Guidance. Final Act. 54. The Examiner specifically characterized the steps in the claim as a fundamental economic practice of “mitigating transaction risk” by generating a fraud score “to determine a level of suspicion regarding . . . [a] current transaction” (step [5]). Final Act. 54–55. The 2019 Eligibility Guidance, citing Alice, 573 U.S. at 219–20, identifies risk mitigation as a fundamental economic practice and an abstract idea. 84 Fed. Reg. 52. Appellant contends that the Examiner erred in characterizing the claim as a method of organizing human activity. Appeal Br. 9. Appellant argues that “methods of organizing human activity must somehow entail actual activities of humans, and the ‘organizing’ of such human activities.” Id. Appellant states that this is “clearly seen when reviewing the various fundamental economic practice examples given in the 2019 Guidance — which all involve human activities.” Id. This argument is not persuasive. The “transactions” which occur between accounts (step [1]), the “current transaction” for which a “fraud score” is generated (step [4]), and the “blocking” of the “current transaction” when it is determined to be fraudulent (step [6]) are each an activity that is initiated by or otherwise involves a human. As explained in the Appeal 2020-005370 Application 14/862,656 12 Specification, the transactions are those of a “payer” and can be a transaction between a customer and merchant for the payment of a good. Spec. ¶¶ 2, 137, 138. The purpose of the claim is to identify a payment fraud by a “payer” in a transaction. Spec. ¶ 2. The claim therefore is monitoring a human’s payment transactions to determine whether they are fraudulent, which is clearly involving a human activity. Appellant’s statement that the claim does not recite any “human activity” may be strictly correct in the sense that the steps recite performance by a “data processing system,” but the claim organizes the “human activity” of a payment transaction, e.g., between a customer and merchant, to mitigate the risk that the customer’s current transaction with the merchant is fraudulent by generating a fraud score (step [4]) and comparing it to a “threshold value to determine a level of suspicion regarding the current transaction” (step [5]), and then blocking the customer’s transaction if it is determined to be fraudulent (step [6]). The human activity is the “plurality of transactions between accounts from one or more different transaction channels” that is recited in the first step [1] of the claim. While a human is not “obtaining” the transaction data (step [1]), “generating . . . transaction payment relationships between the accounts from the transaction data” (step [2]), etc., the claim is managing a human’s payment transactions. Appellant takes the position that a human must actually be an actor in a claim for the claim to be a method of organizing human activity. Appellant states that the “fundamental economic practice examples” cited in the Eligibility Guidance “all involve human activities.” Appeal Br. 9–10. In contrast, Appellant argues that the steps of the claim are accomplished “without any human involvement.” Id. at 10. Appeal 2020-005370 Application 14/862,656 13 We do not agree with Appellant. For example, in Inventor Holdings, LLC v. Bed Bath & Beyond, Inc., 876 F.3d 1372, 1374 (Fed. Cir. 2017) cited in footnote 13 of the 2019 Eligibility Guidance, the claims of the ’582 patent involved a method of processing a payment for purchase of goods from a seller. The steps comprised transmitting orders to a “remote seller,” using “codes” associated with the orders, and making payments to the seller. Id. None of the steps actually recited a human actor, but the claim was still considered to be a patent-ineligible fundamental business practice. As explained by the court: the claims of the ’582 patent are manifestly directed to an abstract idea, which the district court accurately described as “local processing of payments for remotely purchased goods.” Inventor Holdings, 123 F.Supp.3d at 561 (citing ‘582 patent col. 1 ll. 6–10). The idea that a customer may pay for items ordered from a remote seller at a third-party’s local establishment is the type of fundamental business practice that, when implemented using generic computer technology, is not patent-eligible under Alice, 134 S.Ct. at 2355. Inventor Holdings, 876 F.3d at 1378. Claim 1 in this appeal is no different because it involves making a determination that a payment transaction is fraudulent using generic computer technology. The 2019 Eligibility Guidance expressly lists “commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors)” as falling in the grouping of “Certain methods of organizing human activity” (84 Fed. Reg. 52); there is no indication in this list that an actual human actor must participate in the claim for it be classified as such. Rather, a claim Appeal 2020-005370 Application 14/862,656 14 involves organizing human activity when a step in it includes a purchase, sale, etc. that a human ordinarily makes. Appellant also quotes from the 2019 PEG Update,2 as supporting their argument about the requirement for human activity. Appeal Br. 11–12. The disclosure cited by Appellant is as follows: Finally, the sub-groupings encompass both activity of a single person (for example, a person following a set of instructions or a person signing a contract online) and activity that involves multiple people (such as a commercial interaction), and thus, certain activity between a person and a computer (for example a method of anonymous loan shopping that a person conducts using a mobile phone) may fall within the “certain methods of organizing human activity” grouping. 2019 PEG Update 5. Appellant did not quote the full discussion in the 2019 PEG Update. Preceding the disclosure reproduced by Appellant in the Appeal Brief, the 2019 PEG Update explained the scope of the abstract idea of “certain methods of organizing human activity”: The term “certain” qualifies the “certain methods of organizing human activity” grouping as a reminder of several important points. First, not all methods of organizing human activity are abstract ideas (e.g., “a defined set of steps for combining particular ingredients to create a drug formulation” is not a “certain method of organizing human activity”). Second, this grouping is limited to activity that falls within the enumerated sub-groupings of fundamental economic principles or practices, commercial or legal interactions, managing personal behavior, and relationships or interactions between people, and is not to be expanded beyond these enumerated sub-groupings except in 2 Available at https://www.uspto.gov/sites/default/files/documents/peg_oct_2019_update.p df (last accessed Dec. 31, 2020) (“2019 PEG Update”). Appeal 2020-005370 Application 14/862,656 15 rare circumstances as explained in Section III(C) of the 2019 PEG. PEG Update 4–5 (footnote omitted). The discussion in the 2019 PEG Update of activities between humans or a human and a computer was not exclusive, but simply another subgrouping considered to fall within the category of certain methods of organizing human activity. The 2019 PEG Update specifically lists Inventor Holdings as an example a fundamental economic practice (2019 PEG Update 5), and as explained above, the claims in Inventor Holdings were similar to those at issue in this appeal because they involved transactions between a customer and a merchant. Because we find that the Examiner correctly found that claim 1 recites an abstract idea, we proceed to Step 2A, Prong Two, of the analysis. Step 2A, Prong Two Prong Two of Step 2A under the 2019 Eligibility Guidance asks whether there are additional elements that integrate the exception into a practical application. We must look at the claim elements individually and “as an ordered combination” to determine whether the additional elements integrate the recited abstract idea into a practical application. As explained in the 2019 Eligibility Guidance, integration may be found when an additional element “reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field” or “applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception.” Id. at 55. The 2019 Appeal 2020-005370 Application 14/862,656 16 PEG Update further explains that “the specification should be evaluated to determine if the disclosure provides sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement.” PEG Update 12. Appellant contends that the “technological improvement” provided by the claims is “that particular types of network traffic are conditionally blocked in order to mitigate the use of fraudulent transactions.” Appeal Br. 12. Appellant states that “transaction data from one or more channels of transactions is utilized to score transactions, and such transaction score is then utilized to identify and block fraudulent transactions.” Id. Appellant argues that the “automated payment relationship-based graph generation” and “automated transaction blocking” are additional elements which integrate “the alleged judicial exception into a practical application.” Id. at 13. Appellant also asserts that the claims are patent-eligible because “the features of Claim 1 do not come anywhere close [to] tying up the science or technology of ‘mitigating transaction risk’ (the alleged abstract idea, per the last two lines on page 54 of the final Office Action).” Id. at 7. Specifically, Appellant argues that “fraudulent transactions could be identified without using a graph-based process” and features extracted from it. Id. at 8. The improvement and additional elements described by Appellant correspond to steps 2 through 6 of claim 1. In step 2, a graph of transaction payment relationships between accounts is generated. Features from the graph are extracted (step 3) and a fraud score for a “current transaction” is generated based on the extracted features (step 4). The score for the current transaction is compared to a “fraudulent transaction threshold value to Appeal 2020-005370 Application 14/862,656 17 determine a level of suspicion regarding the current transaction” in step 5 of the claim. When the current transaction is determined to be fraudulent in step 5, the current transaction is blocked from being completed (step 6). Steps 2–5 of the claim constitute the rules which are followed in order to determine whether a current payment transaction should be blocked as being fraudulent. The question before us is whether these rules are a technological improvement to a process of identifying fraudulent transactions or whether they are the abstract idea, itself. We address these claim limitations below. The rules recited in the claim are performed by a “data processing system.” The Specification describes a “data processing system” as “a network of computers and other devices,” pointing to Figure 1 which shows servers, a storage device, and client devices connected to a “network.” Spec. ¶ 28. All the steps recited in the claims are performed on this system. Features from the graph recited in step 2 are extracted and used to determine a fraud score in steps 3 and 4. The graph and the extraction of features from it do not impart “an improvement in the functioning of a computer, or an improvement to other technology or technical field” (84 Fed. Reg. 55), but rather provide an improvement to how a fraud score is computed by the data processing system, which is integral to the fundamental practice of mitigating risk of a fraudulent transaction. For this reason, we are not persuaded that the graph and the feature extraction are additional elements of the claim; rather, we find them to be part of the abstract idea of determining a fraud score. Our reasoning is explained in more detail below by contrasting the rejected claims with claims in which a software improvement was found to confer patent-eligibility. Appeal 2020-005370 Application 14/862,656 18 Specifically, we find that the rejected claims in this appeal are distinguishable from the claims in Enfish, LLC v. Microsoft Corp., 822 F.3d 1327 (Fed. Cir. 2016) and Finjan, Inc. v. Blue Coat Sys., Inc., 879 F.3d 1299 (Fed. Cir. 2018), each of which involved software improvements implemented on a computer. For example, in Enfish, 822 F.3d at 1339, a self-referential table recited in the claims was found by the court to be “a specific type of data structure designed to improve the way a computer stores and retrieves data in memory.” In Finjan, 879 F.3d at 1304, the court found that the claim of the patent was directed to a “behavior-based” computer virus scan in which the claimed method “scans a downloadable and attaches the virus scan results to the downloadable in the form of a newly generated file: a ‘security profile that identifies suspicious code in the received Downloadable.’” The court asked “whether this behavior-based virus scan in the ’844 patent constitutes an improvement in computer functionality” and answered the question in the affirmative. Id. As the court explained, “the method of claim 1 employs a new kind of file that enables a computer security system to do things it could not do before.” Id. at 1305. The graph in the claim identified by Appellant as an “additional element” does not add a new functionality to a computer as it did in Enfish and Finjan, but rather is a representation of the payment transactions to facilitate the computation of the fraud score by the data processing system without imparting any change to the system, itself. Figure 3 of the Specification, copied below, shows an example of a payment relationship graph: Appeal 2020-005370 Application 14/862,656 19 Figure 3, reproduced above, shows transaction payment relationship graph 300 showing various transactions that occur between accounts. For example, as explained in the Specification, “Source account vertex 302 represents account ‘1234’ and destination account vertex 304 represents account ‘5678’. Accounts ‘1234’ and ‘5678’ have multiple transactions 306 performed between them.” Spec. ¶ 68. The transaction payment relationship graph 300 “also shows transaction 312 between account ‘5678’ and a point- of-sale terminal, which corresponds to point-of-sale terminal vertex 314.” Spec. ¶ 69. The transaction payment relationship graph therefore depicts transactions that occur between accounts to facilitate observing/viewing which of these transactions have a level of suspicion. The data processing system is being used as tool to “draw” the graph; this is not a technological improvement, but rather is a representation of the transaction data of step 1 to facilitate the extraction of features from it. In SAP Am., Inc. v. InvestPic, LLC, 898 F.3d 1161, 1167 (Fed. Cir. 2018), where “the focus of the claims” was on “selecting certain information, analyzing it using mathematical Appeal 2020-005370 Application 14/862,656 20 techniques, and reporting or displaying the results of the analysis,” the court identified the claimed steps involving the manipulation and display of the data as an abstract principle. The claims in this appeal are also distinguishable from those in McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1315 (Fed. Cir. 2016). In McRO, the claim recited a series of steps that “produce[d] lip synchronization and facial expression control of said animated characters.” McRO found that the recited steps “are limiting in that they define morph weight sets as a function of the timing of phoneme sub-sequences.” Id. at 1313. The court found that the “claimed process uses a combined order of specific rules that renders information into a specific format that is then used and applied to create desired results: a sequence of synchronized, animated characters.” Id. at 1315. For this reason, the claimed process was found to be patent-eligible under 35 U.S.C. § 101. Thus, as explained in SAP, the claims in McRO were “directed to the creation of something physical—namely, the display of ‘lip synchronization and facial expressions’ of animated characters on screens for viewing by human eyes.” SAP, 898 F.3d at 1167. Here, the result of generating the graph and extracting features from it to generate a fraud score for a transaction (steps 2–4) is to know when to block a transaction from being completed. There is no change to a physical process and no change to the process in which the transaction is even blocked. The asserted “additional element” is an integral part of the underlying computation to determine when a transaction is fraudulent to mitigate the risk of fraudulent payment. The claims are also ineligible for similar reasons as in Parker v. Flook, 437 U.S. 584 (1978). In Flook, the claim was directed to a “method Appeal 2020-005370 Application 14/862,656 21 for updating the value of at least one alarm limit on at least one process variable involved in a process comprising the catalytic chemical conversion of hydrocarbons.” Flook, 437 U.S. at 596–97 (Appendix to Opinion). The steps comprised determining a new alarm base using a mathematical algorithm, using the alarm base to update an alarm limit, and then adjusting the alarm limit to the updated value. Id. The alarm limit was used in a catalytic chemical process. The Court held that the “application simply provides a new and presumably better method for calculating alarm limits” which did not confer patent eligibility on the claim. Id. at 595. Here, we find the same deficiency. The rules recited in the claim of generating a graph to determine a fraudulent transaction is a part of the abstract idea, and not the process in which the transaction is blocked from completion. The claim’s ineligibility is also clear when contrasted with Diehr, in which the claims were directed to a method of operating a rubber-molding press to mold a compound by curing it in a mold cavity. 450 U.S. at 179, n. 5. The temperature in the mold during the rubber-molding process was constantly determined and provided to a digital computer. Id. The computer calculated the Arrhenius equation for the reaction time during the cure to determine when the compound was cured and to automatically open the press. Id. Although the claim recited a mathematical algorithm, the Arrhenius equation, the Court held that the claim was eligible for a patent. [W]hen a claim containing a mathematical formula implements or applies that formula in a structure or process which, when considered as a whole, is performing a function which the patent laws were designed to protect (e.g., transforming or reducing an article to a different state or thing), then the claim satisfies the requirements of § 101. Appeal 2020-005370 Application 14/862,656 22 Diehr, 450 U.S. at 192–93. In this case, the graph, and the step of extracting features from it, is not used to control or change the operation of a non-abstract process. While the steps in the rejected claim instruct how to determine a fraud score and a fraudulent transaction, the steps at best improve the abstract process, in contrast to how the mathematical formula in Diehr was used to inform when to open the mold to obtain the cured product. In our view, as explained in Diehr, the patent laws were not designed to protect an improvement to the fundamental economic practice of mitigating risk of a fraudulent transaction by determining a fraud score as recited in the claims. Appellant also argues that claim 1 does not tie up the technology of mitigating the risk of fraudulent transactions and that such fraud could be identified without the graph. Appeal Br. 7, 8. However, as explained above, the steps of the claim of using a graph and extracting features from it to determine a fraud score are part of the abstract idea and therefore do not serve as an additional element that integrates the exception into a practical application. Unlike in Diehr and McRO where the specific rules in the claim were used to change how a process is accomplished — opening a mold in Diehr and animating a character in McRO — claim 1 does not change how the process of blocking the transaction is achieved. Rather, as in Flook, the asserted improvement resides in the rules which embody the abstract idea of risk mitigation, and not in the process of blocking the transaction. Moreover, there is no specific detail in the claim describing how the graph is generated or how the features are extracted. Thus, even if our analysis above under Diehr and McRO is flawed, the claim still fails. As explained in Dropbox, Inc. et al. v. Synchronism Technologies, Inc., 815 Appeal 2020-005370 Application 14/862,656 23 Fed. Appx. 529, 533 (Fed. Cir. 2020) (nonprecedential), it has been “consistently held that an ‘inventive concept’ exists when a claim ‘recite[s] a specific, discrete implementation of the abstract idea’ where the ‘particular arrangement of elements is a technical improvement over [the] prior art.’ [BASCOM Glob. Internet Servs. v. AT&T Mobility LLC, 827 F.3d 1341, 1350 (Fed. Cir. 2016) (“Bascom”)].” As further explained in that case, The patent has to describe how to solve the problem in a manner that encompasses something more than the “principle in the abstract.” See [ChargePoint, Inc. v. SemaConnect, Inc., 920 F.3d 759, 769 (Fed. Circ. 2019)] (explaining that an invention may not be patent eligible if the “claims ‘were drafted in such a result-oriented way that they amounted to encompassing the ‘principle in the abstract’ no matter how implemented’” (quoting Interval Licensing LLC v. AOL, Inc., 896 F.3d 1335, 1343 (Fed. Cir. 2018))). Dropbox, 815 Fed. Appx. at 533. The steps in the claim recite neither how the graph is made nor how the features are extracted from it. Instead, the steps are recited in a “result- oriented way” in which the result is described in the claim, but not how the result is accomplished. The steps are therefore the “principle in the abstract” and it has not been salvaged from ineligibility by limiting how the determination is made. We contrast this to McRO where the claim recited a series of steps that “produce[d] lip synchronization and facial expression control of said animated characters.” The court in McRO found that the recited steps “are limiting in that they define morph weight sets as a function of the timing of phoneme sub-sequences.” 837 F.3d at 1313. The court further found that the “claimed process uses a combined order of specific rules that renders information into a specific format that is then used and applied to create desired results: a sequence of synchronized, animated Appeal 2020-005370 Application 14/862,656 24 characters.” Id. at 1315. For this reason, the claimed process was found to be patent-eligible under 35 U.S.C. § 101. In contrast, claim 1 on appeal does not recite how steps [2] and [3] of the claim are accomplished. The steps are abstract and therefore cannot serve as the additional element which goes beyond the judicial exception. 84 Fed. Reg. 54–55. Thus, we are not persuaded by Appellant’s argument that an alleged technical improvement integrates the recited abstract idea into a practical application. Step 2B Because we determined that the judicial exception is not integrated into a practical application, we proceed to Step 2B of the Eligibility Guidelines, which asks whether there is an inventive concept. In making this Step 2B determination, we must consider whether there are specific limitations or elements recited in the claim “that are not well-understood, routine, conventional activity in the field, which is indicative that an inventive concept may be present,” or whether the claim “simply appends well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, indicative that an inventive concept may not be present.” Eligibility Guidance, 84 Fed. Reg. 56 (footnote omitted). In this part of the analysis, we consider “the elements of each claim both individually and ‘as an ordered combination’” to determine “whether the additional elements ‘transform the nature of the claim’ into a patent-eligible application.” Alice, 573 U.S. at 217. Reciting all the specific steps in claim 1, Appellant states that the “claim recites features that go well beyond merely implementing a methodology of ‘mitigating transaction risk’ . . . using a generic computer Appeal 2020-005370 Application 14/862,656 25 process.” Appeal Br. 14. Appellant responds to the Examiner’s arguments, but does not persuade us the ordered combination of steps in claim 1 provide an inventive concept. For example, Appellant argues that the Examiner improperly found that step 1 of the claim is “mere data gathering.” Appeal Br. 15. We do not agree. As explained in the 2019 Eligibility Guidance, “a mere data gathering such as a step of obtaining information about credit card transactions so that the information can be analyzed in order to detect whether the transactions were fraudulent” is insignificant extra-solution activity which is insufficient to integrate the judicial exception into a practical application. 84 Fed. Reg. 55 (fn. 31) (citing CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366 (Fed. Cir. 2011). While Appellant refers to this step under Step 2B, Appellant does not explain how this step in combination with the other steps in the claim provide an inventive step. Appeal Br. 15. The principal deficiency in Appellant’s arguments is that the steps in the claim in which a graph is generated and used to determine a fraud score are all steps of the abstract idea, and do not provide any additional element, that in combination, provide an inventive step. The transaction relationship graph, itself, is described in Jastrebski, as an approach to analyzing transaction relationships between accounts.3 The graph is also use to identify 3 “In some example embodiments, 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. Further, the accounts may be represented as nodes in a graph and the relationships between these accounts may be represented as edges connecting these accounts.” Jastrebski ¶ 36. Appeal 2020-005370 Application 14/862,656 26 fraud.4,5 Thus, the Examiner properly found that it was well-known and conventional to generate a graph in step 2 of the claim and use features of it to determine fraud. Dependent claims Appellant provides separate arguments for claims 2, 4–16, and 20. The arguments are all basically the same, namely, that a fraud score could be generated that does not use the specific limitations recited in the claim and therefore the abstract idea of mitigating the risk of a fraudulent transaction is not tied up. As illustrative of the claims, claims 14 and 16 are reproduced below: 14. The computer-implemented method of claim 13, wherein the data processing system determines whether the current transaction is fraudulent based on one of the data processing system determining a probability of the current transaction being fraudulent inversely proportional to the shortest path between the source account vertex and the destination account vertex in the at least one graph of transaction payment relationships or the data processing system determining that the current transaction is fraudulent in response to the shortest path being greater than a defined length and determining that the 4 “For example, the graph engine may use a set of rules to identify an account that as suspected of fraud. . . . The graph engine may further generate a set of graph metrics for the graph and a score for the graph . . . The agent may review the graph to identify whether the graph is suspected of fraudulent activity or includes other interesting activity. The agent may further review the graph to identify whether the graph includes accounts that are suspected of fraudulent activity” Jastrebski ¶ 37. 5 “The graph is highlighted. For example, new activity in the form of additional transactions, nodes or links, may be highlighted on the graph. Also for example, transactions that are risky may be highlighted on the graph” Jastrebski ¶ 81. Appeal 2020-005370 Application 14/862,656 27 current transaction is not fraudulent in response to the shortest path being less than or equal to the defined length. 16. The computer-implemented method of claim 5, wherein the data processing system utilizes monetary flow between the source account vertex and the destination account vertex in the at least one graph of transaction payment relationships between the accounts for transaction fraud scoring, and wherein the data processing system determines that the current transaction is fraudulent based on one of the data processing system determining a probability of the current transaction being fraudulent inversely proportional to a maximum monetary flow between the source account vertex and the destination account vertex corresponding to the current transaction or the data processing system determining that the monetary flow between the source account vertex and the destination account vertex in the at least one graph of transaction payment relationships is less than a monetary flow threshold value. We agree with Appellant that at least claims 14 and 16 recite a specific ways in which the fraudulent transactions are determined. However, as discussed above, that the rules recited in these claims are abstract and a part of the fundamental economic practice of mitigating risk by determining which transactions are fraudulent. Specifically, the steps in the claim identify the features in the graph to determine the fraud score. Unlike in McRO where the computations performed in the claim were used to animate characters, here, the computations are a part of the fundamental economic practice of mitigating risk by determining whether a transaction is fraudulent. For the foregoing reasons, we affirm the rejection of claims 1, 2, and 14–20 for lack of patent eligibility. Claims not argued separately fall with Appeal 2020-005370 Application 14/862,656 28 claim 1, etc., because separate arguments for their patentability were not made. 37 C.F.R. § 41.37(c)(1)(iv). CONCLUSION In summary: Claims Rejected 35 U.S.C. § Reference(s)/Basis Affirmed Reversed New Ground 1, 2, 4–8, 10–12, 18–20 103 Jastrebski, Choudhuri 1, 2, 4–8, 10–12, 18–20 10–12 103 Jastrebski, Choudhuri 10–12 1 103 Jastrebski, Choudhuri 1 1, 2, 4– 20 101 Eligibility 1, 2, 4–20 Overall Outcome 1, 2, 4–20 1 TIME PERIOD FOR RESPONSE This decision contains a new ground of rejection pursuant to 37 C.F.R. § 41.50(b). Section 41.50(b) provides “[a] new ground of rejection pursuant to this paragraph shall not be considered final for judicial review.” Section 41.50(b) also provides: When the Board enters such a non-final decision, the appellant, within two months from the date of the decision, must exercise one of the following two options with respect to the new ground of rejection to avoid termination of the appeal as to the rejected claims: (1) Reopen prosecution. Submit an appropriate amendment of the claims so rejected or new Evidence relating to Appeal 2020-005370 Application 14/862,656 29 the claims so rejected, or both, and have the matter reconsidered by the examiner, in which event the prosecution will be remanded to the examiner. The new ground of rejection is binding upon the examiner unless an amendment or new Evidence not previously of Record is made which, in the opinion of the examiner, overcomes the new ground of rejection designated in the decision. Should the examiner reject the claims, appellant may again appeal to the Board pursuant to this subpart. (2) Request rehearing. Request that the proceeding be reheard under §41.52 by the Board upon the same Record. The request for rehearing must address any new ground of rejection and state with particularity the points believed to have been misapprehended or overlooked in entering the new ground of rejection and also state all other grounds upon which rehearing is sought. Further guidance on responding to a new ground of rejection can be found in the MPEP § 1214.01. No time period for taking any subsequent action in connection with this appeal may be extended under 37 C.F.R. § 1.136(a)(1). See 37 C.F.R. §§ 41.50(f), 41.52(b). AFFIRMED; 37 C.F.R. § 41.50(b) Copy with citationCopy as parenthetical citation