DETAILED ACTION
Notice of Pre-AIA or AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of the Claims
2. Applicant filed the Amendment on 01/21/2026. Claims 1-13 are pending. Claims 1-2, 6-7, 9, and 12 are amended.
Claim Rejections - 35 USC §101
3. 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.
4. Claims 1-13 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
5. In the instant case, claim 1 is directed to “system for early fraud detection in deferred transactions”.
6. Claim 1 recites “requesting an access to a payment application and processing of a transaction approval”. Specifically, the claim recites receiving … a first request… to access an … payment application; generating … based on the first request, a set of first features representative of device positional data and a set of second features representative of device activity data; sending… a prompt as output prompting the user, in response to the first request, to provide user credentials; receiving … user credentials in response to the prompt; processing … the user credentials to determine a validity… the validity … being based on the set of first features and the set of second features; in response to determining … is valid, retrieving transaction details … the transaction details comprising a profile of the third party and a profile of a subject of an … transaction; processing … the transaction details to determine a validity of the transaction details; and in response to determining that the transaction details are valid, transmitting an approval … to access the … payment application to perform an … transaction …, wherein the validity … is determined based on a pattern of behavior associated with … according to a specified criterion, the pattern of behavior being determined based on the set of first features and the set of second features of the device data”. Subject matter grouped under “Certain methods of organizing human activity” (e.g., commercial or legal interactions) and an abstract idea in prong one of step 2A (MPEP 2106.04(a)).
7. This judicial exception is not integrated into a practical application because, when analyzed under prong two of step 2A (MPEP 2106.04 II), the additional elements of claim 1 such as “a processor”, “a non-transitory computer readable medium”, “an interface located on a user device respective of a third party device”, “a user device”, “an electronic payment application”, “a first set of modules”, “an electronic transaction”, and “a second set of modules” represent the use of a computer as a tool to perform an abstract idea and/or does no more than generally link the abstract idea to a particular field of use. Therefore, the additional elements do not integrate the abstract idea into a practical application as they do no more than represent a computer performing functions that correspond to (i.e., automate) the acts of requesting an access to a payment application and processing of a transaction approval. With respect to “receiving … a first request for a user device to access an electronic payment application”, “sending … a prompt as output prompting the user, in response to the first request, to provide user credentials”, “receiving … user credentials in response to the prompt”, and “transmitting an approval of the user device to access the electronic payment application to perform an electronic transaction between the user device and the third party device” is simply transmitting data “[use] of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice) does not integrate a judicial exception into a practical application or provide significantly more”, (MPEP 2106.05(f)(2)).
8. When analyzed under step 2B (MPEP 2106.04 II), the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception itself. Viewed as a whole, the combination of elements recited in the claim merely describes the concept of requesting to access to a payment application and processing of the transaction approval using computer technology. Therefore, as the use of these additional elements do no more than employ a computer as a tool to automate and/or implement the abstract idea, they cannot provide significantly more than the abstract idea itself (MPEP 2106.05(I)(A)(f) & (h)).
9. Hence, claim 1 is not patent eligible.
10. The following dependent claims recent additional elements not addressed above:
claim 3 recites “a credential stuffing module; a synthetic identity theft module; an account takeover module; and a trojan threat module”;
claim 5 recites “a machine learning model training via adversarial learning”;
claim 7 recites “a classifier of the trojan threat module”;
claim 8 recites “a triangulation module; and a chargeback fraud module”;
claim 10 recites “a device associated with the merchant”; and
claim 13 recites “one or more nodes of a distributed ledger”.
When considered individually, and as a whole, each of these additional elements amount to merely "apply it", as they are merely applying the abstract idea to the technical environment of the credential stuffing module, the synthetic identity theft module, the account takeover module, the trojan threat module, the machine learning model training via adversarial learning, the classifier of the trojan threat module, the triangulation module, the chargeback fraud module, the device associated with the merchant, and the one or more nodes of a distributed ledger.
Dependent claims 2-13 merely expand upon the abstract ideas of the independent claim 1, and are therefore rejected under the same rationale as claim 1.
Conclusion of 35 USC §101
11. The claims as a whole do not amount to significantly more than the abstract idea itself. This is because the claims do not effect an improvement to another technology or technical field; the claims do not amount to an improvement to the functioning of a computer system itself; and the claims do not move beyond a general link of the use of an abstract idea to a particular technological environment.
12. Accordingly, there are no meaningful limitations in the claims that transform the judicial exception into a patent eligible application such that the claims amount to significantly more than the judicial exception itself.
Claim Rejections - 35 USC § 103
13. 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 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.
14. 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.
15. The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
16. Claim 1 is rejected under 35 U.S.C. 103 as being unpatentable over US20230052407A1 to McGrandle et al. in view of US9754255B1 to Ma et al.
17. As per claim 1:
McGrandle et al. discloses the following limitations:
A system comprising: a processor; and a non-transitory computer readable medium stored thereon instructions comprising a plurality of modules that are executable by the processor to perform operations comprising: ([0007] discloses a system with a processor, memory, and computer-executable instructions stored on a non-transitory medium.)
receiving, via an interface located on a user device respective of a third party device, a first request for a user device to access an electronic payment application ([0059] discloses a user device receiving a request to access a secure payment application (banking application, digital wallet) through an interface and the remote website operated by merchant constitutes the third party device context)
generating, by a first set of modules based on the first request, a set of first features representative of device positional data and a set of second features representative of device activity data ([0055] discloses device activity data (app activations, network connections, user interaction patterns) as a second set of features)
sending, to the user device via the interface, a prompt as output prompting the user, in response to the first request, to provide user credentials ([0040], [0070] discloses sending a prompt to the user device for active authentication (credentials such as PIN, password, fingerprint, facial scan) in response to an access request)
receiving, from the user device via the interface, user credentials in response to the prompt ([0053], [0070] discloses the system receiving user credentials (fingerprint, PIN, password) from the user device in response to the authentication prompt and processing the successful authentication result)
processing, via the first set of modules, the user credentials to determine a validity of the user device, the validity of the user device being based on the set of first features and the set of second features ([0066]-[0067] discloses the first set of modules (passive authentication system) processing suer credentials and determining device validity based on both condition information (first features: positional data like GPS, orientation) and interaction data (second features: activity data like app usage, connections). The combination of both feature sets determines the validity)
in response to determining that the transaction details are valid, transmitting an approval of the user device to access the electronic payment application to perform an electronic transaction between the user device and the third party device ([0069], [0033] discloses that upon successful authentication, the payment transaction is approved and processed between the user’s mobile device and the retailer (third party), completing the electronic transaction)
wherein the validity of the user device is determined based on a pattern of behavior associated with the user device according to a specified criterion, the pattern of behavior being determined based on the set of first features and the set of second features of the device data ([0056]-[0058] discloses determining device validity based on a behavioral pattern (user profile) using specified criteria (fuzzy logic, ML weighting thresholds). The pattern is determined from both positional features (GPS location, orientation) and activity features (Wi-Fi connections, application usage, browsing behavior)
McGrandle et al. does not disclose, however, Ma et al., as shown, teaches the following limitations:
in response to determining that the user device is valid, retrieving transaction details from the third party device, the transaction details comprising a profile of the third party and a profile of a subject of an electronic transaction (Col/line 7/66-8/4; col.5, lines 31-35; col.6, lines 51-54; discloses retrieving transaction details from the retailer (third party), including the retailer’s profile (retailer location, retailer branch identity) and the subject of the transaction (purchase order details, price range))
processing, via a second set of modules, the transaction details to determine a validity of the transaction details (Col.8, lines 7-10, 50-56; discloses the Verification/Authentication unit (second set of modules relative to the secure processor) processing transaction details (retail location, price, retailer branch, transaction time) to determine their validity against established patterns)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate devices and methods of employing a location tracking function within a mobile device, such that a geographical location is tracked in real-time for the purpose of authenticating a user and a trusted transaction of Ma et al. (‘255, col.2, lines 38-42) with teaching of McGrandle et al. for authenticating a user of a computing device that is in network communication with other computing devices using a passive authentication system that tracks the actions of the user and the conditions of a user device associated with the user after the user has performed an authentication on the user device (‘407, [0016]) for retrieving transaction details from the retailer, including the retailer’s location, retailer branch and the transaction details such as credit card usage, price range, and processing transaction data such as retail location, price, retailer branch, transaction time to determine their validity against established patterns (‘255, col.5, lines 31-35; col.6, lines 51-54; col.8, lines 7-10, 50-53).
18. Claim 2 is rejected under 35 U.S.C. 103 as being unpatentable over US20230052407A1 to McGrandle et al. in view of US9754255B1 to Ma et al. and US10977654B2 to Kumar et al.
19. As per claim 2:
Neither McGrandle et al. nor Ma et al. disclose, however, Kumar et al., as shown, teaches the following limitations:
The system of claim 1, wherein the operations further comprise: receiving, from the third party device, an indication that the subject of the transaction has been transferred to the user device (Col/line 3/67-4/3; discloses receiving transaction information/requests)
in response to the indication, executing a first transfer of a first amount of funds to the third party device, the first amount based on the transaction details (Col.14, lines 54-56; discloses executing payment transfers based on transaction information)
prompting the user device for a second transfer of a second amount of funds according to the transaction details (Col.6, lines 62-65; discloses prompting user devices for actions)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate devices and methods of employing a location tracking function within a mobile device, such that a geographical location is tracked in real-time for the purpose of authenticating a user and a trusted transaction of Ma et al. (‘255, col.2, lines 38-42) and a machine learning engine for fraud detection related to cross-location online transaction processing that trained using artificial intelligence techniques of Kumar et al. (‘654, abstract) with teaching of McGrandle et al. for authenticating a user of a computing device that is in network communication with other computing devices using a passive authentication system that tracks the actions of the user and the conditions of a user device associated with the user after the user has performed an authentication on the user device (‘407, [0016]) for receiving transaction processing request that includes transaction details, notifying via the user interface of the user’s device of transaction details, and debiting an account of the user and providing the payment to the account of the merchant (‘654, col.4, lines 1-2; col.6, lines 62-65; col.14, lines 54-56).
20. Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over US20230052407A1 to McGrandle et al. in view of US9754255B1 to Ma et al. and US10290053B2 to Priess et al.
21. As per claim 3:
Neither McGrandle et al. nor Ma et al. disclose, however, Priess et al., as shown, teaches the following limitations:
The system of claim 1, wherein the first set of modules comprise: a credential stuffing module (Col.6, lines 18-22; discloses the acknowledgment credential related fraud, i.e., stolen credentials, (e.g., concept of such module))
a synthetic identity theft module (Col.9, lines 48-52; discloses a Predictive Fraud Module (PFM) can differentiate synthetic identity vs. real user behavior patterns thru probabilistic analysis)
an account takeover module (Col.6, lines 18-22; discloses that the account takeover as a fraud type to be prevented)
a trojan threat module (Col.99, lines 35-36, 39-41; discloses that malware like a trojan threats compromise devices)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate devices and methods of employing a location tracking function within a mobile device, such that a geographical location is tracked in real-time for the purpose of authenticating a user and a trusted transaction of Ma et al. (‘255, col.2, lines 38-42) and a fraud prevention system for use in the prevention of account fraud and identity theft, that provides real-time risk management solutions and protect online and off-line channels of Priess et al. (‘053, col.3, lines 54-57) with teaching of McGrandle et al. for authenticating a user of a computing device that is in network communication with other computing devices using a passive authentication system that tracks the actions of the user and the conditions of a user device associated with the user after the user has performed an authentication on the user device (‘407, [0016]) for providing functions to prevent online fraud, off-line fraud, and multi-channel fraud that includes account takeover fraud, using session or event data for generating a probability of users at large, disclosing malware that used to steal credentials and utilizing user’s computer (‘053, col.6, lines 18-21; col.9, lines 49-52; col.99, lines 35-36, 39-41).
22. Claims 4 and 6-7 are rejected under 35 U.S.C. 103 as being unpatentable over US20230052407A1 to McGrandle et al. in view of US9754255B1 to Ma et al., US10290053B2 to Priess et al., and US10977654B2 to Kumar et al.
23. As per claim 4:
Neither McGrandle et al. nor Ma et al. or Priess et al. disclose, however, Kumar et al., as shown, teaches the following limitations:
The system of claim 3, wherein processing the first request comprises: determining, by the synthetic identity theft module, that the user credentials are associated with a real user (Col.1, lines 18-21; discloses credential based user authentication/identity determination)
in response to the determination, determining that the first request is valid (Col.6, lines 47-49 discloses determining transaction validity based on fraud assessment)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate devices and methods of employing a location tracking function within a mobile device, such that a geographical location is tracked in real-time for the purpose of authenticating a user and a trusted transaction of Ma et al. (‘255, col.2, lines 38-42), a fraud prevention system for use in the prevention of account fraud and identity theft, that provides real-time risk management solutions and protect online and off-line channels of Priess et al. (‘053, col.3, lines 54-57), and a machine learning engine for fraud detection related to cross-location online transaction processing that trained using artificial intelligence techniques of Kumar et al. (‘654, abstract) with teaching of McGrandle et al. for authenticating a user of a computing device that is in network communication with other computing devices using a passive authentication system that tracks the actions of the user and the conditions of a user device associated with the user after the user has performed an authentication on the user device (‘407, [0016]) for establishing authentication credentials used to authenticate user identity and authorize account use and assessing to indicate whether the transaction is low risk and therefore allowed to be processed (‘654, col.1, lines 19-21; col.6, lines 47-49).
24. As per claim 6:
Neither McGrandle et al. nor Ma et al. or Priess et al. disclose, however, Kumar et al., as shown, teaches the following limitations:
The system of claim 3, wherein processing the first request comprises: accessing an activity history from the device data of the user, the second set of features being representative of the activity history (Col.4, lines 48-50; discloses accessing user activity/transaction history)
deriving, by the account takeover module, a pattern of activity based on the activity history (Col.5, lines 53-56; discloses pattern derivation from activity history)
reviewing a session history of the user, the session history comprising actions taken by the user immediately prior to placing the first request (Col.3, lines 62-66; discloses reviewing activity history with the merchant)
comparing the derived pattern of activity to the session history (Col.6, lines 32-34; discloses comparing transaction data to historical patterns or rules)
in response to the derived pattern matching the session history, determining that the first request is valid (Col.6, lines 47-49; discloses determining transaction validity based on pattern/risk assessment)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate devices and methods of employing a location tracking function within a mobile device, such that a geographical location is tracked in real-time for the purpose of authenticating a user and a trusted transaction of Ma et al. (‘255, col.2, lines 38-42), a fraud prevention system for use in the prevention of account fraud and identity theft, that provides real-time risk management solutions and protect online and off-line channels of Priess et al. (‘053, col.3, lines 54-57), and a machine learning engine for fraud detection related to cross-location online transaction processing that trained using artificial intelligence techniques of Kumar et al. (‘654, abstract) with teaching of McGrandle et al. for authenticating a user of a computing device that is in network communication with other computing devices using a passive authentication system that tracks the actions of the user and the conditions of a user device associated with the user after the user has performed an authentication on the user device (‘407, [0016]) for accessing to previous transaction information, identifying purchased items together based on transaction histories, accessing the account via GUI that display transactions, determining a fraud/risk assessment corresponding to a score, probability, and assessing to indicate whether the transaction is low risk and therefore allowed to be processed (‘654, col.4, lines 48-49; col.5, lines 54-56; col.3, lines 62-66; col.6, lines 32-34, 47-49).
25. As per claim 7:
Neither McGrandle et al. nor Ma et al. or Priess et al. disclose, however, Kumar et al., as shown, teaches the following limitations:
The system of claim 3, wherein processing the first request comprises: collecting metadata from the device data in the first request, the set of first features being representative of the metadata (Col/line 4/66-5/3; discloses metadata/feature collection from request data)
receiving an activity history of the user from the device data, the set of second features being representative of the activity history (Col.4, lines 51-54; discloses receiving activity history as input features)
processing, by the trojan threat module, the set of first features representative of the metadata and the set of second features representative of the activity history (Col.6, lines 27-28; discloses usage user and transaction data)
based on the set of first features and the set of second features, determining, by a classifier of the trojan threat module that receives the set of first features and the set of second features as input, that the first request is associated with a benign user (Col.4, lines 16-18; discloses multi-feature classifier assessment)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate devices and methods of employing a location tracking function within a mobile device, such that a geographical location is tracked in real-time for the purpose of authenticating a user and a trusted transaction of Ma et al. (‘255, col.2, lines 38-42), a fraud prevention system for use in the prevention of account fraud and identity theft, that provides real-time risk management solutions and protect online and off-line channels of Priess et al. (‘053, col.3, lines 54-57), and a machine learning engine for fraud detection related to cross-location online transaction processing that trained using artificial intelligence techniques of Kumar et al. (‘654, abstract) with teaching of McGrandle et al. for authenticating a user of a computing device that is in network communication with other computing devices using a passive authentication system that tracks the actions of the user and the conditions of a user device associated with the user after the user has performed an authentication on the user device (‘407, [0016]) for collecting input features that include user location, transaction location, transaction count, receiving an account transaction history that user purchased items, processing by the machine learning engine the transaction with risk rules, and assessing whether the transaction is fraudulent (‘654, col.5, lines 1-3; col.4, lines 51-53; col.6, lines 27-28; col.4, lines 16-18).
26. Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over US20230052407A1 to McGrandle et al. in view of US9754255B1 to Ma et al., US10290053B2 to Priess et al., US10977654B2 to Kumar et al., and US10789530B2 to Bruss et al.
27. As per claim 5:
Neither McGrandle et al. nor Ma et al. or Priess et al. and Kumar et al. disclose, however, Bruss et al., as shown, teaches the following limitations:
The system of claim 4, wherein the synthetic identity theft module comprises a machine learning model training via adversarial learning (Col.4, lines 55-58 discloses adversarial style training with positive/negative pairs, supporting adversarial learning concepts)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate devices and methods of employing a location tracking function within a mobile device, such that a geographical location is tracked in real-time for the purpose of authenticating a user and a trusted transaction of Ma et al. (‘255, col.2, lines 38-42), a fraud prevention system for use in the prevention of account fraud and identity theft, that provides real-time risk management solutions and protect online and off-line channels of Priess et al. (‘053, col.3, lines 54-57), a machine learning engine for fraud detection related to cross-location online transaction processing that trained using artificial intelligence techniques of Kumar et al. (‘654, abstract), and a method for providing techniques to learn a low-dimensional dense representation for each entity in a network graph of transactions of Bruss et al. (‘530, col.2, lines 6-8) with teaching of McGrandle et al. for authenticating a user of a computing device that is in network communication with other computing devices using a passive authentication system that tracks the actions of the user and the conditions of a user device associated with the user after the user has performed an authentication on the user device (‘407, [0016]) for having the training data that includes negative samples from the transaction data and/or the graphs where a negative sample is defined as an artificially generated relationship that does not exist (‘530, col.4, lines 55-58).
28. Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over US20230052407A1 to McGrandle et al. in view of US9754255B1 to Ma et al., US10789530B2 to Bruss et al. and US10937023B2 to Kote
29. As per claim 8:
Neither McGrandle et al. nor Ma et al. disclose, however, Bruss et al., as shown, teaches the following limitations:
The system of claim 1, wherein the second set of modules comprise: a triangulation module (Col.8, lines 28-31; discloses merchant/user similarity analysis)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate devices and methods of employing a location tracking function within a mobile device, such that a geographical location is tracked in real-time for the purpose of authenticating a user and a trusted transaction of Ma et al. (‘255, col.2, lines 38-42), and a method for providing techniques to learn a low-dimensional dense representation for each entity in a network graph of transactions of Bruss et al. (‘530, col.2, lines 6-8) with teaching of McGrandle et al. for authenticating a user of a computing device that is in network communication with other computing devices using a passive authentication system that tracks the actions of the user and the conditions of a user device associated with the user after the user has performed an authentication on the user device (‘407, [0016]) for identifying using embeddings of the neural network merchants located in NYC that are similar to merchants located in Washington, D.C. that the customer has previously transacted with (‘530, col.8, lines 28-31).
Neither McGrandle et al. nor Ma et al. or Bruss et al. disclose, however, Kote, as shown, teaches the following limitations:
a chargeback fraud module (Col.1, lines 16-18; discloses chargeback systems)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate devices and methods of employing a location tracking function within a mobile device, such that a geographical location is tracked in real-time for the purpose of authenticating a user and a trusted transaction of Ma et al. (‘255, col.2, lines 38-42), a method for providing techniques to learn a low-dimensional dense representation for each entity in a network graph of transactions of Bruss et al. (‘530, col.2, lines 6-8), and systems for reporting, recording, and/or publishing chargeback requests in association with completed transactions performed in a distributed crypto currency system of Kote (‘023, col.2, lines 55-58) with teaching of McGrandle et al. for authenticating a user of a computing device that is in network communication with other computing devices using a passive authentication system that tracks the actions of the user and the conditions of a user device associated with the user after the user has performed an authentication on the user device (‘407, [0016]) for identifying online and/or mobile payments and more particularly to a chargeback system for distributed crypto currencies (‘023, col.1, lines 16-18).
30. Claims 9-11 are rejected under 35 U.S.C. 103 as being unpatentable over US20230052407A1 to McGrandle et al. in view of US9754255B1 to Ma et al., US10789530B2 to Bruss et al. US10937023B2 to Kote, and US10977654B2 to Kumar et al.
31. As per claim 9:
Neither McGrandle et al. nor Ma et al. or Kote disclose, however, Bruss et al., as shown, teaches the following limitations:
The system of claim 8, wherein processing the transaction details to determine the validity of the transaction details comprises: scraping, from at least one third-party source, public profile data (Col.3, lines 35-37; discloses data gathering)
generating, by the triangulation module, a set of embeddings comprising: a merchant embeddings respective of the merchant profile (Col.2, lines 17-18; col/line 6/65-7/2; discloses merchant embeddings)
a product embeddings respective of the product profile; and a user embeddings respective of the user profile (Col.5, lines 8-15; discloses user/account embeddings)
aggregating the merchant embeddings, the product embeddings, and the user embeddings to a transaction embeddings (Col/line 6/65-7/3; discloses aggregating user/merchant/product attributes into one transaction embedding vector)
generating, by the triangulation module based on the transaction embeddings as input, a risk score indicative of a validity of the second request (Col.7, lines 38-40; discloses generating a risk/probability score from the transaction embedding vector)
in response to the risk score being less than a threshold, determining that the transaction details are valid (Col.9, lines 38-42; discloses threshold based validity determination via similarity score)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate devices and methods of employing a location tracking function within a mobile device, such that a geographical location is tracked in real-time for the purpose of authenticating a user and a trusted transaction of Ma et al. (‘255, col.2, lines 38-42), systems for reporting, recording, and/or publishing chargeback requests in association with completed transactions performed in a distributed crypto currency system of Kote (‘023, col.2, lines 55-58), and a method for providing techniques to learn a low-dimensional dense representation for each entity in a network graph of transactions of Bruss et al. (‘530, col.2, lines 6-8) with teaching of McGrandle et al. for authenticating a user of a computing device that is in network communication with other computing devices using a passive authentication system that tracks the actions of the user and the conditions of a user device associated with the user after the user has performed an authentication on the user device (‘407, [0016]) for providing transaction data that is updated periodically as new transactions are processed, that embeddings for each entity form of an embeddings layer of a neural network, the embedding function generate a vector based on the account ID, merchant name, location, and purchase amount, each unique entity ID in the graph and/or transaction data is assigned a unique identifier, aggregating user/merchant/product attributes into one transaction embedding vector, triggering a fraud alert on the account if the probability exceeds an expected value, and threshold based validity determination via similarity score (‘530, col.3, lines 35-37; col.2, lines 17-18; col.6, line 65-67; col.5, lines 8-15; col.7, lines 38-40; col.9, lines 38-42).
Neither McGrandle et al. nor Ma et al. or Kote and Bruss et al. disclose, however, Kumar et al., as shown, teaches the following limitations:
assembling, by the triangulation module, a user profile for the user based on the public profile data (Col.4, lines 48-49; discloses assembly of profiling)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate devices and methods of employing a location tracking function within a mobile device, such that a geographical location is tracked in real-time for the purpose of authenticating a user and a trusted transaction of Ma et al. (‘255, col.2, lines 38-42), systems for reporting, recording, and/or publishing chargeback requests in association with completed transactions performed in a distributed crypto currency system of Kote (‘023, col.2, lines 55-58), and a method for providing techniques to learn a low-dimensional dense representation for each entity in a network graph of transactions of Bruss et al. (‘530, col.2, lines 6-8), and a machine learning engine for fraud detection related to cross-location online transaction processing that trained using artificial intelligence techniques of Kumar et al. (‘654, abstract) with teaching of McGrandle et al. for authenticating a user of a computing device that is in network communication with other computing devices using a passive authentication system that tracks the actions of the user and the conditions of a user device associated with the user after the user has performed an authentication on the user device (‘407, [0016]) for providing access to user’s previous transaction information (‘654, col.4, lines 48-49).
32. As per claim 10:
Neither McGrandle et al. nor Ma et al. or Bruss et al. disclose, however, Kumar et al., as shown, teaches the following limitations:
The system of claim 9, wherein the merchant profile comprises: a category of the merchant (Col.5, lines 16-17; discloses merchant categorization via verticals)
a location of the merchant (Col.4, lines 42-44; discloses merchant location)
an IP address of a device associated with the merchant (Col.4, lines 39-40; discloses IP address as location data)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate devices and methods of employing a location tracking function within a mobile device, such that a geographical location is tracked in real-time for the purpose of authenticating a user and a trusted transaction of Ma et al. (‘255, col.2, lines 38-42), and a method for providing techniques to learn a low-dimensional dense representation for each entity in a network graph of transactions of Bruss et al. (‘530, col.2, lines 6-8), and a machine learning engine for fraud detection related to cross-location online transaction processing that trained using artificial intelligence techniques of Kumar et al. (‘654, abstract) with teaching of McGrandle et al. for authenticating a user of a computing device that is in network communication with other computing devices using a passive authentication system that tracks the actions of the user and the conditions of a user device associated with the user after the user has performed an authentication on the user device (‘407, [0016]) for identifying merchants by merchant clusters in the same locations, determining location based on transaction, and corresponding to IP address (‘654, col.4, lines 39-40, 42-44; col.5, lines 16-17).
Neither McGrandle et al. nor Ma et al. or Bruss et al. and Kumar et al. disclose, however, Kote, as shown, teaches the following limitations:
a reputation of the merchant, the reputation derived from one or more public data sources (Col.11, lines 50-53; col.12, line 39; discloses merchant (payee) reputation derived from public chargeback ledger)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate devices and methods of employing a location tracking function within a mobile device, such that a geographical location is tracked in real-time for the purpose of authenticating a user and a trusted transaction of Ma et al. (‘255, col.2, lines 38-42), a method for providing techniques to learn a low-dimensional dense representation for each entity in a network graph of transactions of Bruss et al. (‘530, col.2, lines 6-8), a machine learning engine for fraud detection related to cross-location online transaction processing that trained using artificial intelligence techniques of Kumar et al. (‘654, abstract), and systems for reporting, recording, and/or publishing chargeback requests in association with completed transactions performed in a distributed crypto currency system of Kote (‘023, col.2, lines 55-58), with teaching of McGrandle et al. for authenticating a user of a computing device that is in network communication with other computing devices using a passive authentication system that tracks the actions of the user and the conditions of a user device associated with the user after the user has performed an authentication on the user device (‘407, [0016]) for avoiding by users that payee (merchant) having repeatedly chargebacks and refusal satisfy those chargebacks with low “payee ratings” (‘023, col.11, lines 50-53; col.12, line 39).
33. As per claim 11:
Neither McGrandle et al. nor Ma et al. or Bruss et al. disclose, however, Kote, as shown, teaches the following limitations:
The system of claim 9, wherein the product profile comprises: a category of the product (Col.18, lines 4-6; discloses product information)
a cost of the product (Col.9, lines 9-11; discloses transaction/product cost)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate devices and methods of employing a location tracking function within a mobile device, such that a geographical location is tracked in real-time for the purpose of authenticating a user and a trusted transaction of Ma et al. (‘255, col.2, lines 38-42), a method for providing techniques to learn a low-dimensional dense representation for each entity in a network graph of transactions of Bruss et al. (‘530, col.2, lines 6-8), and systems for reporting, recording, and/or publishing chargeback requests in association with completed transactions performed in a distributed crypto currency system of Kote (‘023, col.2, lines 55-58), with teaching of McGrandle et al. for authenticating a user of a computing device that is in network communication with other computing devices using a passive authentication system that tracks the actions of the user and the conditions of a user device associated with the user after the user has performed an authentication on the user device (‘407, [0016]) for including to the refund response information associated with product involved in the transaction and a requested chargeback amount (‘023, col.18, lines 4-6; col.9, lines 9-11).
Neither McGrandle et al. nor Ma et al. or Bruss et al. and Kote disclose, however, Kumar et al., as shown, teaches the following limitations:
or a quantity of the product (Col.4, lines 54-55; discloses transaction counts per vertical)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate devices and methods of employing a location tracking function within a mobile device, such that a geographical location is tracked in real-time for the purpose of authenticating a user and a trusted transaction of Ma et al. (‘255, col.2, lines 38-42), a method for providing techniques to learn a low-dimensional dense representation for each entity in a network graph of transactions of Bruss et al. (‘530, col.2, lines 6-8), systems for reporting, recording, and/or publishing chargeback requests in association with completed transactions performed in a distributed crypto currency system of Kote (‘023, col.2, lines 55-58), and a machine learning engine for fraud detection related to cross-location online transaction processing that trained using artificial intelligence techniques of Kumar et al. (‘654, abstract) with teaching of McGrandle et al. for authenticating a user of a computing device that is in network communication with other computing devices using a passive authentication system that tracks the actions of the user and the conditions of a user device associated with the user after the user has performed an authentication on the user device (‘407, [0016]) for providing a number of transactions over a selected period of time (‘654, col.4, lines 54-55).
34. Claim 12 and 13 are rejected under 35 U.S.C. 103 as being unpatentable over US20230052407A1 to McGrandle et al. in view of US9754255B1 to Ma et al. and US10937023B2 to Kote.
35. As per claim 12:
Neither McGrandle et al. nor Ma et al. disclose, however, Kote, as shown, teaches the following limitations:
The system of claim 8, wherein processing the transaction details to determine the validity of the transaction details comprises: retrieving a stored list of chargeback fraud events associated with the user device (Col.9, lines 39-43; discloses retrieving a stored list of chargeback events)
analyzing, by the chargeback fraud module, the stored list to derive a set of behaviors associated with chargeback fraud (Col.12, lines 31-33; discloses analyzing chargebacks to derive abusive behaviors)
comparing, by the chargeback fraud module, the pattern of behavior associated with the user device to the set of behaviors associated with chargeback fraud (Col.12, lines 22-25; discloses comparing behavior pattern against chargeback-fraud behaviors)
determining a risk score based on the comparison of the pattern of behavior of the user device to the set of behaviors (Col.12, line 39-42; discloses risk-score (rating) derived from chargeback behavior comparison)
in response to the risk score being less than a threshold value, determining that the transaction details are valid (Col.11, line 50; col.12, lines 4-6; discloses threshold based decisioning from chargeback ratings)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate devices and methods of employing a location tracking function within a mobile device, such that a geographical location is tracked in real-time for the purpose of authenticating a user and a trusted transaction of Ma et al. (‘255, col.2, lines 38-42) and systems for reporting, recording, and/or publishing chargeback requests in association with completed transactions performed in a distributed crypto currency system of Kote (‘023, col.2, lines 55-58) with teaching of McGrandle et al. for authenticating a user of a computing device that is in network communication with other computing devices using a passive authentication system that tracks the actions of the user and the conditions of a user device associated with the user after the user has performed an authentication on the user device (‘407, [0016]) for including many more chargeback reports in chargeback ledger, analyzing chargeback data by the third party entity, and conducted transactions across the system reported chargebacks, providing payee and payer ratings, and determining whether avoid doing business with particular merchant (‘023, col.9, lines 39-40; col.11, line 50; col.12, lines 4-6, 22-25, 31-33, 39-42).
36. As per claim 13:
Neither McGrandle et al. nor Ma et al. disclose, however, Kote, as shown, teaches the following limitations:
The system of claim 12, wherein the stored list is stored on one or more nodes of a distributed ledger (Col.17, lines 38-42; discloses storing the chargeback list on nodes of a distributed (public) ledger)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate devices and methods of employing a location tracking function within a mobile device, such that a geographical location is tracked in real-time for the purpose of authenticating a user and a trusted transaction of Ma et al. (‘255, col.2, lines 38-42) and systems for reporting, recording, and/or publishing chargeback requests in association with completed transactions performed in a distributed crypto currency system of Kote (‘023, col.2, lines 55-58) with teaching of McGrandle et al. for authenticating a user of a computing device that is in network communication with other computing devices using a passive authentication system that tracks the actions of the user and the conditions of a user device associated with the user after the user has performed an authentication on the user device (‘407, [0016]) for providing the refund report in a first block generated for a distributed refund public ledger (‘023, col.17, lines 38-39).
Response to Arguments
37. Applicant filed the Amendment on 01/21/2026. Claims 1-13 are pending. Claims 1-2, 6-7, 9, and 12 are amended. Claims 1-13 are rejected. After careful consideration of applicant arguments, the examiner finds them to be not persuasive.
Rejection under 35 USC § 101
38. Applicant’s arguments toward 35 U.S.C. § 101 rejection is not persuasive. Amended independent claim 1 do not have additional elements that could lead to an improvement in the functioning of a computer, or an improvement to other technology or technical field.
39. Applicant is of the opinion that “amended claim 1 is not directed to the abstract idea of ‘certain methods of organizing human activity (i.e., commercial or legal interactions) because the claim limitations are not directed to marketing or sales activities or behaviors. None of the limitations of amended claim 1 set forth or describe the judicial exception”.
Examiner respectfully disagrees.
Claims as a whole directed to requesting an access to a payment application and processing of a transaction approval which is grouped under “Certain methods of organizing human activity (e.g., commercial or legal interactions)”.
40. Applicant is of the opinion that “[the] additional limitations of amended claim 1, when viewed as a whole, integrate the claim into a practical application within that technological field that transforms the claim as a whole into patent-eligible subject matter. That is, the claim limitations are directed to reducing risks associated with electronic transactions between user devices and third-party devices by validating the user device based not only on the user credentials but also based on features (i.e., first set of features and the second set of features) from the device data”.
Examiner respectfully disagrees.
Mentioned above the elements of the claims performed by using the computer components. The use of a processor/computer as a tool to implement the abstract idea does not integrate the abstract idea into a practical application because it requires no more than a computer performing functions that correspond to acts required to carry out the abstract idea. The additional elements do not involve improvements to the functioning of a computer, or to any other technology or technical field. An ordered combination of the limitations – determine a validity of the user device, the validity of the user device being based on the set of first features and the set of second features, in response to determining that the transaction details are valid, transmitting an approval of the user device to access the electronic payment application to perform an electronic transaction between the user device and the third party device, and the pattern of behavior being determined based on the set of first features and the set of second features of the device data – merely implement an abstract idea (commercia/legal interaction) using the additional elements such as a processor, a non-transitory computer readable medium, an interface located on a user device respective of a third party device, a user device, an electronic payment application, a first set of modules, an electronic transaction, and a second set of modules. The claims do not, for example, purport to improve the functioning of a computer. Nor do they effect an improvement in any other technology or technical field. Accordingly, the additional elements do not impose any meaningful limits on practicing the abstract idea, and the claim is directed to the abstract idea.
41. Applicant is of the opinion that the claims recite significantly more than the judicial exception, and concludes that “generating the sets of features from the device data and the validation of the user device based on the user credentials and the sets of features are additional limitations that do not recite the alleged abstract idea and are specific limitations other than what is well-understood, routine, and conventional in the field because the limitations confine the claims to a particular useful application of validating the user device and transaction details prior to enabling the electronic transaction from being performed. Therefore, amended claim 1 is patentable subject matter under Step 2B”.
Examiner respectfully disagrees.
Applicant’s argument is not persuasive for the reasons already discussed above – the additional elements do not involve improvements to the functioning of a computer, or to any other technology or technical field. As per the identification of the “additional elements” under Step 2A Prong Two and Step 2B, the rejection properly identifies the elements which are recited in the claim beyond the abstract idea, including “determine a validity of the user device, the validity of the user device being based on the set of first features and the set of second features”, “transmitting an approval of the user device to access the electronic payment application to perform an electronic transaction between the user device and the third party device”. Under Step 2A Prong Two, the “additional elements” have been identified and the limitations are not indicative of integration into a practical application. Under Step 2B, the additional elements have been evaluated and do not amount to “significantly more”. Note that Revised Step 2A overlaps with Step 2B, and thus, many of the considerations need not be reevaluated in Step 2B because the answer will be the same. The identification of the additional elements in the claim from Step 2A Prong Two is carried over as well as the conclusion from Step 2A Prong Two on the considerations discussed in MPEP 2106.05(a)-(c), (e), (f), and (h).
The claims are not patent eligible.
Rejections under 35 U.S.C. § 112 (b)
42. Rejections of claims 7 and 12 due to claims’ amendments are withdrawn.
Rejections under 35 U.S.C. § 102
43. Rejection of claims 1-5 and 8 due to amendments of claim 1 are withdrawn.
Rejections under 35 U.S.C. § 102 and 103
44. Applicant argues that prior art references do not teach claims 1-13 limitations.
Applicant arguments are no longer applicable because they are moot in light of the new ground of rejection.
Conclusion
45. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US20220076252A1 – Prabhu et al – Discloses a method for verifying transactions, wherein the method includes receiving a transaction request for performing a transaction between a user account and a merchant account.
46. 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.
47. Any inquiry concerning this communication or earlier communications from the examiner should be directed to AMANULLA ABDULLAEV whose telephone number is (571)272-4367. The examiner can normally be reached Monday-Friday 9:30AM -4:30PM ET.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ryan D Donlon can be reached at 571-270-3602. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/AMANULLA ABDULLAEV/ Examiner, Art Unit 3692
/Anita Y Coupe/ Supervisory Patent Examiner, Art Unit 3619
Prosecution Insights