DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This action is responsive to claims filed 02/11/2026 and Applicant’s correspondence regarding application 15/704136 filed 02/11/2026.
Claims 1-20 have been examined with this office action.
Claim Terms
permission attributes – [0117] … Authorized entities 102, 104, 106, 108, 110, and 112 can be granted permission attributes or access to write new blocks to the blockchain using the interface processor 308. [0227] … Each party can have well defined roles, with pre-defined business authorizations to allow them access to data or operations based on permission attributes.
security device – [0226] The credit score platform 300 can have different security tools including an authentication unit 716, an identity management unit 718 and fraud management unit 718, a permissions unit 720, and an audit logging unit 722.
Thus, applicant’s security device is read in view of the specification as the credit score platform which is described a general-purpose computer [0148]. The “plurality of security tools comprising an authentication unit, identity management unit, permissions unit and audit logging unit” is merely software running on the general purpose computer.
access channel – [Figure 7A] is shown as the source of data from a user (debtor, creditor, FI, Credit Bureau, 3rhd party) “[0226] FIGS. 7A, 7B, 7C, and 7D provide a system context diagram according to some embodiments. The credit score platform 300 connects to computing devices debtor device 704, creditor device 706, financial institution device 708, credit bureau device 710, third party device 712 by way of channel access connections 714 to receive data for the distributed ledger. Channel access connections 714 can provide for contract management, electronic signatures, bid management, loan matching and insurance coverage”. Thus, the access channel is merely a source of data.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea of maintaining credit scores and identity records without significantly more.
Subject Matter Eligibility Standard
When considering subject matter eligibility under 35 U.S.C. 101, it must be determined whether the claim is directed to one of the four statutory categories of invention, i.e., process, machine, manufacture, or composition of matter. If the claim does fall within one of the statutory categories, it must then be determined whether the claim is directed to a judicial exception (i.e., law of nature, natural phenomenon, and abstract idea), and if so, it must additionally be determined whether the claim is a patent-eligible application of the exception. If an abstract idea is present in the claim, any element or combination of elements in the claim must be sufficient to ensure that the claim amounts to significantly more than the abstract idea itself. Examples of abstract ideas include fundamental economic practices; certain methods of organizing human activities; an idea itself; and mathematical relationships/formulas. Alice Corporation Pty. Ltd. v.CLS Bank International, et al., 573 U.S. _ (2014) as provided by the interim guidelines FR 12/16/2014 Vol. 79 No. 241.
Analysis
Step 1, the claimed invention must be to one of the four statutory categories. 35 U.S.C. 101 defines the four categories of invention that Congress deemed to be the appropriate subject matter of a patent: processes, machines, manufactures and compositions of matter. In this case independent claims 1, 19 and 20 and all claims which depend from it are directed toward a system. As such, all claims fall within one of the four categories of invention deemed to be the appropriate subject matter.
Step 2A Prong 1, Under Step 2 A, Prong 1 of the 2019 Revised § 101 Guidance, it is determined whether the claims are directed to a judicial exception such as a law of nature, a natural phenomenon, or an abstract idea (See Alice, 134 S. Ct. at 2355) by identify the specific limitation(s) in the claim that recites abstract idea(s); and then determine whether the identified limitation(s) falls within at least one of the groupings of abstract ideas enumerated in the 2019 PEG.
Specifically, claim 1 comprises inter alia the functions or steps of “A system for a decentralized, permissioned, and secured network of a plurality of nodes providing a distributed ledger for automatically monitoring credit events and generating electronic credit and digital identity records using blocks stored on storage devices, wherein such that the distributed ledger is only accessible to authorized entities having appropriate permissions, wherein the system has access channels interacting with interface applications of user devices and third party devices to transmit the credit alerts to the user devices using a set of identifiers, receive data and events from multiple data sources, and update visualizations of the interface applications to indicate the impact of credit events on electronic credit history records, the system comprising: non-transitory storage devices storing a distributed ledger of a plurality of nodes, each node having at least a storage device, the storage devices for storing a plurality of blocks, each block comprising identification data linked to a set of identifiers for an individual, one or more permission attributes, transaction data, a timestamp indicating when the block was created, and a hash reference for the distributed ledger, each identifier of the set of identifiers being linked to data records from different data sources, the set of identifiers being used as an index to generate credit, wherein a digital identity record for the individual comprises blocks of the plurality of blocks, wherein the blocks forming the digital identity record for the individual are linked by one or more identifiers of a set of identifiers for the individual; a user device with a hardware processor coupled to a memory storing instructions including an interface application to transmit a credit request and display an on demand real time visualization of an electronic credit history record, credit score, data points with weightings to indicate impact of credit data points on the credit score; and gamification features to encourage improving the credit score; an access channel and a plurality of channel access connections with different types of interfaces to connect to different requesting devices and a plurality of data sources having credit data, the different types of interfaces comprising an interface to connect to the user device, wherein the plurality of channel access connections with the different types of interfaces enable integration with third party devices in different channels of choice and are extensible and configurable to facilitate reusability across the third party devices, wherein the plurality of channel access connections connect the storage devices of the plurality of nodes of the distributed ledger connect to the requesting devices and the plurality of data sources by way of the plurality of channel access connections to receive data and events related to credit worthiness to record relevant events on the distributed ledger, the data and events comprising loans, transactions, payment events; a security device in communication with the access channel to verify the different requesting devices and the plurality of data sources that connect to the different types of interfaces the security device comprising a processor coupled to a memory storing instructions for an authentication unit, identity management unit, permissions unit and audit logging unit, wherein the security device verifies the different requesting devices using permission attributes prior to providing read access to the electronic credit history record and prior to granting write permissions to update the electronic credit history record, wherein the permissions attributes differentiate between roles of the nodes and the requesting devices to define the roles with pre-defined authorizations to allow the nodes and the requesting devices to access data or operations based on the permissions attributes, wherein the security device compares credentials to the permissions attributes, wherein the security device manages a hierarchical model for party identities to enroll, activate, deactivate, and renew the credentials, wherein the security device uses a public and private key infrastructure to maintain the identities while being decentralized, wherein the identity management unit integrates with identity providers to acquire additional identifiers or verify identifiers;
wherein the security device verifies the user device using credentials of the user device and permissions attributes for a digital identity record prior to providing access to the electronic credit history record, wherein the security device reads and write protects the data of the storage devices of the plurality of nodes of the distributed ledger from other network participants to comply with regulatory requirements and to prevent network participants from gaining competitive advantages, wherein the security device verifies the plurality of data sources having the credit data prior to granting write permissions to update the electronic credit history record with the credit data, wherein the digital identity record comprises signature data;
wherein the security device verifies at least one node of the plurality of nodes using the set of identifiers and the permission attributes for the digital identify record to authorize the at least one node to generate the electronic credit history record;
a computer hardware device with a transmitter, receiver and at least one processor coupled to a memory storing instructions, the computer hardware device in communication with the security device and the access channel, the at least one processor configured to: receive, from the verified user device, the credit request for an individual corresponding to a first set of identifiers for the digital identity record; convert the credit data from the verified plurality of data sources into a set of blocks of the plurality blocks by accessing the storage devices of the plurality of nodes of the distributed ledger, each block of the set of blocks having an identifier of the first set of identifiers for the digital identity record, the set of blocks including an initial block for storing at least the portion of the credit data, the initial block comprising attributes for the individual, and the permission attributes for the digital identity record, wherein the security device uses the permission attributes to authorize at least one node of the plurality of nodes to create a new block for insertion into the set of blocks, update an existing block of the set of blocks, delete or mark the existing block of the set of blocks or extract data from one or more blocks of the set of blocks;
store the set of blocks on storage devices of nodes of the plurality of nodes of the distributed ledger;
uses the access channel to access the storage devices of the nodes of the distributed ledger and generates the on demand real time visualization of the electronic credit history record, credit score and data points using the first set of identifiers to identify the set of blocks, each identified block having an identifier of the first set of identifiers, wherein the at least one processor computes the credit score on demand and in near real time using machine learning rules and in response to the received credit request;
wherein the access channel automatically updates the interface application for the user device to display the on demand real time visualization of the electronic credit history record, credit score and data points populated by the data extracted from the set of blocks stored on the storage devices; a smart contract middleware application with a processor configured to access the storage devices to store smart contract code on a block of the set of blocks;
an integration middleware layer with a processor configured to trigger notification of a credit event by executing the smart contract code stored on the block of the set of blocks, the notification having an identifier of the first set of identifiers and credit event attributes;
wherein the at least one processor is configured to:
generate the credit event using an event object, the event object having an identifier, name, date, triggered by party, and description; generate the permissions attributes using a permission object, the permission object having a name, type, and function; convert the credit event into an additional block for storing on the distributed ledger using the notification for the credit event, wherein the security device verifies the at least one node of the plurality of nodes using the permissions attributes to authorize the at least one node to create the additional block for insertion into the set of blocks, the additional block having the identifier of the first set of identifiers and the credit event attributes;
validate, using the plurality of nodes, the additional block for insertion into the set of blocks to generate validation information;
store the additional block on a storage device of a node of the plurality of nodes of the distributed ledger to record the credit event as part of the electronic credit history record, wherein the validation information is stored as part of the set of blocks; and
detect and determine an impact of the credit event on the electronic credit history record based on the additional block having the identifier of the first set of identifiers stored on the storage device of the node of the plurality of nodes of the distributed ledger; upon detecting the impact of the credit event on the electronic credit history, generate the credit alert indicating the impact of the credit event; and transmit the credit alert indicating the impact of the credit event to the interface application; and
wherein the access channel interacts with the interface application of the user device to transmit the credit alert indicating the impact of the credit event to the user device and any third party devices authorized by the individual corresponding to the first set of identifiers for the digital identity record using the first set of identifiers and update the visualization of the interface application to indicate the impact of the credit event on the electronic credit history record:
the integration middleware layer operating with an integration gateway device wherein the integration middleware layer identifies corrupted or fraudulent data records in real time and eliminates the corrupted or fraudulent data records from the distributed ledger, restores the distributed ledger to a last known good state upon detecting ledger corruption, and identifies and contains double spend attacks
wherein the integration middleware layer comprises an administrative application configured to monitor information for each node of the plurality of nodes, an access control application to manage permissions for each node and authorized entities enrolled in the network, and a data analytics application to perform data mining on the credit data and debtor preferences and generate signals representing recommended offers to be transmitted to the user device, the information for each node comprising activity, status, and broadcasting events of the node: and
a machine learning processor configured to process credit data relating to transaction behavior to define rules for predicting a positive or negative impact on credit scores, detect and predict the impact of the credit event to the credit record using the rules, and triggers generation and transmission of the credit alert upon the detection and prediction of the impact, wherein the machine learning processor processes credit data relating to transaction behavior to define machine learning rules for predicting the impact and refines the machine learning rules based on training data, wherein the machine learning processor detects predictive impacts from credit data and triggers notifications, wherein the machine learning processor implements preventive measures using predictive credit alerts to improve credit scores, wherein the machine learning processor verifies and validates data stored on the distributed ledger, including verifying the signature data using handwriting recognition to identify the individual and verify the credit data, wherein the machine learning processor refines and updates digital identity records using different learning processes on data stored on the distributed ledger to expand digital identity data, including implementing face recognition to identify the individual from images of faces stored in the digital identity record, wherein the machine learning processor trains using different learning processes on data stored on the distributed ledger to refine and update credit score calculations, wherein the machine learning processor learns transaction behaviours that implicate credit ability including spending patterns and payment patterns,, wherein the machine learning rules refine score calculation based on training results to update credit score calculation to enable re-use of credit data with the refined score calculation to increase the accuracy of the credit score”.
Claim 19 comprises inter alia the functions or steps of “A system for a decentralized, permissioned, and secured network of a plurality of nodes providing a distributed ledger for automatically monitoring credit events and generating electronic credit and digital identity records using blocks stored on storage devices, wherein such that the distributed ledger is only accessible to authorized entities having appropriate permissions, wherein the system has access channels interacting with interface applications of user devices and third party devices to transmit the credit alerts to the user devices using a set of identifiers, receive data and events from multiple sources, and update visualizations of the interface applications to indicate the impact of credit events on electronic credit history records, the system comprising: non-transitory storage devices storing a distributed ledger of a plurality of nodes, the storage devices for storing a plurality of blocks, each block comprising identification data linked to a set of identifiers for an individual, one or more permission attributes, transaction data, a timestamp indicating when the block was created, and a hash reference for the distributed ledger, each identifier of the set of identifiers being linked to data records from different data sources, the set of identifiers being used as an index to generate credit data, wherein a digital identity record for the individual comprises blocks of the plurality of blocks, wherein the blocks forming the digital identity record for the individual are linked by one or more identifiers of a set of identifiers for the individual; a user device with a hardware processor coupled to a memory storing instructions including an interface application to transmit a credit request and display an on demand real time visualization of an electronic credit history record; an access channel and a plurality of channel access connections with different types of interfaces to connect to different requesting devices and a plurality of data sources having credit data, the different types of interfaces comprising an interface to connect to the user device, wherein the plurality of channel access connections with the different types of interfaces enable integration with third party devices in different channels of choice and are extensible and configurable to facilitate reusability across the third party devices, wherein the plurality of channel access connections connect the storage devices of the plurality of nodes of the distributed ledger to the requesting devices and the plurality of data sources to receive data and events related to credit worthiness to record relevant events on the distributed ledger, the data and events comprising loans, transactions, payment events; a security device in communication with the access channel to verify the different requesting devices and the plurality of data sources that connect to the different types of interfaces, the security device comprising a processor coupled to a memory storing instructions for an authentication unit, identity management unit, permissions unit and audit logging unit, wherein the security device verifies the different requesting devices using permission attributes prior to providing read access to the electronic credit history record and prior to granting write permissions to update the electronic credit history record, wherein the permissions attributes differentiate between roles of the nodes and the requesting devices to define the roles with pre-defined authorizations to allow the nodes and the requesting devices to access data or operations based on the permissions attributes, wherein the security device compares credentials to the permissions attributes, wherein the security device manages a hierarchical model for party identities to enroll, activate, deactivate, and renew the credentials, wherein the security device uses a public and private key infrastructure to maintain the identities while being decentralized, wherein the identity management unit integrates with identity providers to acquire additional identifiers or verify identifiers; wherein the security device verifies the user device using credentials of the user device and permissions attributes for a digital identity record prior to providing access to the electronic credit history record so that data of the storage devices of the plurality of nodes of the distributed ledger is read and write protected from other network participants to comply with regulatory requirements and to prevent network participants from gaining competitive advantages, wherein the security device verifies the plurality of data sources having the credit data prior to granting write permissions to update the electronic credit history record with the credit data; wherein the security device verifies at least one node of the plurality of nodes using the set of identifiers and the permission attributes for the digital identify record to authorize the at least one node to generate the electronic credit history record; at least one processor in communication with the security device and the access channel, the at least one processor configured to: in response to the credit request, access storage devices of the plurality of nodes of the distributed ledger and use the at least one node to generate the electronic credit history record using the set of identifiers for the digital identity record to identify a set of blocks on the storage devices, each identified block having an identifier of the set of identifiers for the digital identity record, wherein the set of blocks store the permission attributes for the digital identify record for the security device to authorize the at least one node of the plurality of nodes to create a new block for insertion into the set of blocks and extract data from one or more blocks of the set of blocks, and extract data from the set of blocks stored on the storage devices, wherein the security device uses the permission attributes for the digital identify record to authorize the at least one node to populate the electronic credit history record with data for a set of loan offers, each loan offer indicating a creditor and loan terms; wherein the access channel transmits the credit history record to the interface application and updates the interface application to display the on demand real time visualization of the electronic credit history record populated by the data extracted from the set of blocks stored on the storage devices using the permission attributes; receive, from the interface application, a selected loan offer indicating a selected creditor and selected loan terms; transmit a notification of the selected loan offer to the selected creditor; receive an acceptance of the selected loan offer from the selected creditor; a smart contract middleware application with a processor configured to generate smart contract code with the selected loan terms, the smart contract being linked to an identifier of the set of identifiers and the selected creditor, the smart contract having an electronic signature and transaction terms; and access the storage devices to record a new block for storing on the distributed ledger using the permissions attributes to authorize a node of the plurality of nodes to create the additional block for insertion into the set of blocks, validate or verify the new block for insertion into the set of blocks to generate validation information, and initiating propagation of the new block to the plurality of nodes, the new block having the smart contract code, the identifier, the validation information, and the selected creditor; wherein the at least one processor is configured to detect and determine an impact of the credit event on the electronic credit history record based on the additional block having the identifier of the first set of identifiers stored on the storage device of the node of the plurality of nodes of the distributed ledger, upon detecting the impact of the credit event on the electronic credit history, generate a credit alert indicating the impact of the credit event; and transmit the credit alert indicating the impact of the credit event to the interface application; and wherein the access channel interacts with the interface application of the user device to transmit the credit alert to the user device and any third party devices authorized by the individual corresponding to the first set of identifiers for the digital identity record using the first set of identifiers to update the visualization of the interface application to indicate the impact of the credit event on the electronic credit history record; an integration middleware layer operating with an integration gateway device, wherein the integration middleware layer identifies corrupted or fraudulent data records in real time and eliminates the corrupted or fraudulent data records from the distributed ledger, restores the distributed ledger to a last known good state upon detecting ledger corruption, and identifies and contains double spend attacks, wherein the integration middleware layer comprises an administrative application configured to monitor information for each node of the plurality of nodes, an access control application to manage permissions for each node and authorized entities enrolled in the network, and a data analytics application to perform data mining on the credit data and debtor preferences and generate signals representing recommended offers to be transmitted to the user device, the information for each node comprising activity, status, and broadcasting events of the node: and
a machine learning processor configured to processes credit data relating to transaction behavior to define rules for predicting a positive or negative impact on credit scores, detect and predict the impact of the credit event to the credit record using the rules and trigger generation and transmission of a notification upon the detection and prediction of the impact; wherein the machine learning processor processes credit data relating to transaction behavior to define machine learning rules for predicting the impact and refines the machine learning rules based on training data, wherein the machine learning processor detects predictive impacts from credit data and triggers notifications, wherein the machine learning processor implements preventive measures using predictive credit alerts to improve credit scores, wherein the machine learning processor verifies and validates data stored on the distributed ledger, including implementing face recognition to identify the individual from images of faces stored in the digital identity record, wherein the machine learning processor refines and updates digital identity records using different learning processes on data stored on the distributed ledger to expand digital identity data, wherein the machine learning processor trains using different learning processors processes on data stored on the distributed ledger to refine and update credit score calculations, wherein the machine learning processor learns transaction behaviours that implicate credit ability including spending patterns and payment patterns, wherein the machine learning rules refine score calculation based on training results to update credit score calculation to enable re-use of credit data with the refined score calculation to increase the accuracy of the credit score”.
Claim 20 comprises inter alia the functions or steps of “A computer-implemented system for a decentralized, permissioned, and secured network of a plurality of nodes providing a distributed ledger for generating electronic credit and digital identity records using blocks stored on storage devices, wherein such that the distributed ledger is only accessible to authorized entities having appropriate permissions, wherein the system has access channels interacting with interface applications of user devices and third party devices to transmit the credit alerts to the user devices using a set of identifiers, receive data and events from multiple sources, and update visualizations of the interface applications to indicate the impact of credit events on electronic credit history records, the system comprising: non-transitory storage devices storing a distributed ledger of a plurality of nodes, each node including at least a computing device, the storage devices storing a plurality of blocks; each block comprising identification data linked to a set of identifiers for a digital identity record, one or more permission attributes, transaction data, a timestamp indicating when the block was created, a hash reference for the distributed ledger, each identifier of the set of identifiers being linked to data records from different data sources, the set of identifiers being used as an index to generate credit data, wherein a digital identity record for the individual comprises blocks of the plurality of blocks, wherein the blocks forming the digital identity record for the individual are linked by one or more identifiers of a set of identifiers for the individual; a user device with a hardware processor coupled to a memory storing instructions including an interface application to transmit a credit request and display an on demand real time visualization of an electronic credit history record, credit score, and data points with weightings to indicate impact of credit data points on the credit score, and gamification features to encourage improving the credit score; an access channel and a plurality of channel access connections with different types of interfaces to connect to different requesting devices and a plurality of data sources having credit data, the different types of interfaces comprising an interface to connect to the user device, wherein the plurality of channel access connections with the different types of interfaces enable integration with third party devices in different channels of choice and are extensible and configurable to facilitate reusability across the third party devices, wherein the plurality of channel access connections connect the storage devices of the plurality of nodes of the distributed ledger to the requesting devices and the plurality of data sources to receive data and events related to credit worthiness to record relevant events on the distributed ledger, the data and events comprising loans, transactions, payment events; a security device in communication with the access channel to verify the different requesting devices and the plurality of data sources that connect to the different types of interfaces, the security device comprising a processor coupled to a memory storing instructions for an authentication unit, identity management unit, permissions unit and audit logging unit, wherein the security device verifies the different requesting devices using permission attributes prior to providing read access to the electronic credit history record and prior to granting write permissions to update the electronic credit history record, wherein the permissions attributes differentiate between roles of the nodes and the requesting devices to define the roles with pre-defined authorizations to allow the nodes and the requesting devices to access data or operations based on the permissions attributes, wherein the security device compares credentials to the permissions attributes, wherein the security device manages a hierarchical model for party identities to enroll, activate, deactivate, and renew the credentials, wherein the security device uses a public and private key infrastructure to maintain the identities while being decentralized, wherein the identity management unit integrates with identity providers to acquire additional identifiers or verify identifiers; wherein the security device verifies the user device using credentials of the user device and permissions attributes for a digital identity record prior to providing access to the electronic credit history record, wherein the security device reads and write protects the data of the storage devices of the plurality of nodes of the distributed ledger from other network participants to comply with regulatory requirements and to prevent network participants from gaining competitive advantages, wherein the security device verifies the plurality of data sources having the credit data prior to granting write permissions to update the electronic credit history record with the credit data, wherein the digital identity record comprises signature data; wherein the security device verifies at least one node of the plurality of nodes using the set of identifiers and the permission attributes for the digital identify record to authorize the at least one node to generate the electronic credit history record; at least one processor configured to, in response to the credit request for an individual corresponding to the set of identifiers for the digital identity record, access storage devices of the plurality of nodes of the distributed ledger, use the at least one node to generate an electronic credit record using the set of identifiers for the digital identity record to identify the set of blocks on the storage devices, each identified block having an identifier of the set of identifiers for the digital identity record, wherein the set of blocks store the permission attributes for the digital identify record for the security device to authorize the at least one node of the plurality of nodes to create a new block for insertion into the set of blocks and extract data from one or more blocks of the set of blocks, and extract data from the set of blocks stored on the storage devices, wherein the security device uses the permission attributes for the digital identify record to authorize the at least one node to populate the electronic credit record with the digital identity record and validation information for the set of blocks, the digital identity record comprising data from a second set of blocks stored on the storage devices, each block of the second set of blocks linked to the set of identifiers, and further configured to update the interface application to display the on demand real time visualization of the electronic credit history record and the digital identity record; a smart contract middleware application with a processor configured to access the storage devices to store smart contract code on a block of the set of blocks; and an integration middleware layer with a processor configured to trigger of a notification of credit event to the interface by executing the smart contract code stored on the block of the set of blocks by accessing the storage devices; wherein the at least one processor is configured to detect and determine an impact of the credit event on the electronic credit history record based on the additional block having the identifier of the first set of identifiers stored on the storage device of the node of the plurality of nodes of the distributed ledger, and upon detecting the impact of the credit event on the electronic credit history, generate a credit alert indicating the impact of the credit event; and transmit the credit alert indicating the impact of the credit event to the interface application; and wherein the access channel interacts with the interface application of the user device to transmit the credit alert to the user device and any third party devices authorized by the individual corresponding to the first set of identifiers for the digital identity record using the first set of identifiers to update the visualization of the interface application to indicate the impact of the credit event on the electronic credit history record, wherein the security device verifies the user device using credentials of the user device prior to providing access to the electronic credit history record;
the integration middleware layer operating with an integration gateway device, wherein the integration middleware layer identifies corrupted or fraudulent data records in real time and eliminates the corrupted or fraudulent data records from the distributed ledger, restores the distributed ledger to a last known good state upon detecting ledger corruption, and identifies and contains double spend attacks, wherein the integration middleware layer comprises an administrative application configured to monitor information for each node of the plurality of nodes, an access control application to manage permissions for each node and authorized entities enrolled in the network, and a data analytics application to perform data mining on the credit data and debtor preferences and generate signals representing recommended offers to be transmitted to the user device, the information for each node comprising activity, status, and broadcasting events of the node: and
a machine learning processor configured to process credit data relating to transaction behaviour to define rules for predicting a positive or negative impact on credit scores, detect and predict the impact of the credit event to the credit record using the rules and trigger generation and transmission of a notification upon the detection and prediction of the impact, wherein the machine learning processes credit data relating to transaction behaviour to define machine learning rules for predicting the impact and refines the machine learning rules based on training data, wherein the machine learning processor detects predictive impacts from credit data and triggers notifications, wherein the machine learning processor implements preventive measures using predictive credit alerts to improve credit scores, wherein the machine learning processor verifies and validates data stored on the distributed ledger including verifying signature data using handwriting recognition to identify the individual and verify the credit data,, wherein the machine learning processor refines and updates digital identity records using different learning processes on data stored on the distributed ledger to expand digital identity data including implementing face recognition to identify the individual from images of faces stored in the digital identity record, wherein the machine learning processor trains using different learning processes on data stored on the distributed ledger to refine and update credit score calculations, wherein the machine learning processor learns transaction behaviours that implicate credit ability including spending patterns and payment patterns, wherein the machine learning rules refine score calculation based on training results to update credit score calculation to enable re-use of credit data with the refined score calculation to increase the accuracy of the credit score”.
Those claim limits in bold are identified as claim limits directed toward the abstract idea, while those that are un-bolded are identified as additional elements.
The cited limitations as drafted are systems and methods that, under their broadest reasonable interpretation, covers performance of a method of organizing human activity, but for the recitation of the generic computer components. Further, none of the limitations recite technological implementations details for any of the steps but, instead, only recite broad functional language being performed by the generic use of at least one processor.
Maintaining credit scores and identity records is a fundamental economic practice long prevalent in commerce systems. If a claim limitation, under its broadest reasonable interpretation, covers a fundamental economic principle or practice but for the general linking to a technological environment, then it falls within the organizing human activity grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
Step 2A Prong 2, Next, it is determined whether the claim is directed to the abstract concept itself or whether it is instead directed to some technological implementation or application of, or improvement to, this concept, i.e., integrated into a practical application. See, e.g., Alice, 573 U.S. at 223, discussing Diamond v. Diehr, 450 U.S. 175 (1981). The mere introduction of a computer or generic computer technology into the claims need not alter the analysis. See Alice, 573 U.S. at 223—24. “[T]he relevant question is whether the claims here do more than simply instruct the practitioner to implement the abstract idea on a generic computer.” Alice, 573 U.S. at 225.
In the present case, the judicial exception is not integrated into a practical application. The claim limitations are not indicative of integration into a practical application by claiming an improvement to the functioning of the computer or to any other technology or technical field. Further, the claim limitations are not indicative of integration into a practical application by applying or using the judicial exception in some other meaningful way.
In particular, the claims contain the following additional elements:
system;
a decentralized, permissioned, and secured network;
a plurality of nodes;
electronic / on demand real time;
an administrative/ a data analytics / an access control application;
transmit;
the visualization of the interface application;
the integration middleware layer operating with an integration gateway device;
storage devices;
access channels interacting with interface applications of user devices and third party devices / an access channel and a plurality of channel access connections with different types of interfaces to connect to different requesting devices / wherein the plurality of channel access connections with the different types of interfaces enable integration with third party devices in different channels of choice and are extensible and configurable to facilitate reusability across the third party devices;
the user devices;
non-transitory storage devices;
a security device in communication with the access channel;
the different types of interfaces the security device comprising a processor coupled to a memory storing instructions for an authentication unit, identity management unit, permissions unit and audit logging unit, wherein the security device verifies the different requesting devices;
the security device uses a public and private key infrastructure;
a computer hardware device with a transmitter, receiver and at least one processor coupled to a memory storing instructions, the computer hardware device in communication with the security device and the access channel; machine learning; training machine learning; handwriting recognition; face recognition. However, the specification description of the additional elements
system ([Figures 7A-D] [0188] [0195] [0226] [0247] “Throughout the foregoing discussion, numerous references will be made regarding servers, services, interfaces, portals, platforms, or other systems formed from computing devices. It should be appreciated that the use of such terms is deemed to represent one or more computing devices having at least one processor configured to execute
software instructions stored on a computer readable tangible, non-transitory medium. For example, a server can include one or more computers operating as a web server, database server, or other type of computer server in a manner
to fulfill described roles, responsibilities, or functions”);
a decentralized, permissioned, and secured network ([0218] “… a distributed
and decentralized ledger platform, providing trusted and permissioned access to an electronic loan Marketplace …” [0220]);
a plurality of nodes ([0032]);
electronic / on demand real time (interpreted as functions performed by software running on processor [0246-0247]);
an administrative/ a data analytics / an access control application (interpreted as functions performed by software running on processor [0246-0247]);
transmit ([0093] [0110]);
the visualization of the interface application ([0115] [0124-0125] [0130]);
the integration middleware layer operating with an integration gateway device ([0105-0107] [0112-0113] [0230] [0236]);
storage devices ([0149] [0188]);
access channels interacting with interface applications of user devices and third party devices / an access channel and a plurality of channel access connections with different types of interfaces to connect to different requesting devices / wherein the plurality of channel access connections with the different types of interfaces enable integration with third party devices in different channels of choice and are extensible and configurable to facilitate reusability across the third party devices ([Figure 7A, element 714] [0196-0197] [0206-207] [0211] [0214] [0226] “..Standalone APis or SDKs
can also be provided to enable integrations within third party systems in different channels of choice. These APis can to be extensible and configurable to facilitate reusability across parties” where the specific APIs and SKDs are not further described in the Specification.);
the user devices ([0207]);
non-transitory storage devices ([0247] [0250]);
a security device in communication with the access channel ([0152]);
the different types of interfaces the security device comprising a processor coupled to a memory storing instructions for an authentication unit (software), identity management unit (software), permissions unit and audit logging unit (software), wherein the security device verifies the different requesting devices ([0154] [0190]);
the security device uses a public and private key infrastructure ([0154] “…using suitable encryption and cryptographic techniques ( e.g., public/private key pairs, hashing, "proof of work" generation); among others…” [0190] “…cryptography unit 422 may be configured for encrypting and/or otherwise transforming information provided by information extraction unit 426, for example,
applying various encryption algorithms and/or techniques (e.g., public key/private key encryption) to extracted elements of information…” );
a computer hardware device with a transmitter, receiver and at least one processor coupled to a memory storing instructions, the computer hardware device in communication with the security device and the access channel ([Figure 7A] [0251]);
machine learning ([0115] [0126-0127] [0148]);
training machine learning ([0115] [0127]); handwriting recognition ([0115]); face recognition ([0115]) are at a high level of generality using exemplary language or as part of a generic technological environment and are functions any general purpose computer performs such that it amount no more than mere instruction to apply the exception to a particular technological environment. Further, none of the limitations recite technological implementations details for any of the steps but, instead, only recite broad functional language being performed by the generic use of at least one processor. Accordingly, these additional elements do not integrate the abstract idea into a practical application because it does not impose any meaning limits on practicing the abstract idea. Thus, the claim is directed toward an abstract idea.
Step 2B, the claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements when considered both individually and as an ordered combination do not amount to significantly more that the abstract idea(s). As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a processor to perform the abstract idea(s) amounts to no more than mere instructions to apply the exaction using a generic computer component. Mere instruction to apply an exertion using a generic computer component cannot provide an inventive concept. These generic computer components are claimed at a high level of generality to perform their basic functions which amount to no more than generally linking the use of the judicial exception to the particular technological environment of field of use (Specification as cited above for additional elements) and further see insignificant extra-solution activity MPEP § 2106.05 I. A. iii, 2106.05(b), 2106.05(b) III, 2106.05(g). Thus, the claims are not patent eligible.
As for dependent claims 2-18 these claims recite limitations that further define the same abstract idea using previously identified additional elements noted from the respective independent claims from which they depend. Therefore, the cited dependent claims are considered patent ineligible for the reasons given above.
Prior Art
The claims overcome the prior art of record such that none of the cited prior art reference’s disclosures can be applied to form the basis of a 35 USC § 102 rejection nor can they be combined to fairly suggest in combination, the basis of a 35 USC § 103 rejection when the limitations directed toward the specific data involved in credit data points on the credit score are read in the particular environment of the claims. Therefore, the claims may be allowable if amended to overcome the rejection(s) under 35 U.S.C. 101, set forth in this Office action.
Response to Arguments
Applicant's arguments with regards to claims have been fully considered but they are not persuasive.
EXAMINER’S RESPONSE TO APPLICANT REMARKS CONCERNING Claim Rejections - 35 USC § 101: The Examiner respectfully disagrees with Applicant’s arguments. The amended claims merely add additional abstract ideas. There is no improvement to the computer or a technology recited in the amended claims. The abstract idea merely applies the use of a technological environment. Regarding applicant’s arguments that “The claims do not recite any abstract ideas, such as a mathematical concept, mental process, or a method of organizing human activity such as a fundamental economic concept or managing interactions between people”, the examiner disagrees. Maintaining credit scores and identity records is a fundamental economic practice long prevalent in commerce systems. If a claim limitation, under its broadest reasonable interpretation, covers a fundamental economic principle or practice but for the general linking to a technological environment, then it falls within the organizing human activity grouping of abstract ideas. Accordingly, the claim recites an abstract idea. The hardware devices (memory, processor, display, plurality of nodes, and interfaces), distributed ledger, and machine learning are described and claimed at a high level of generality and are merely applied to the abstract idea of the claims.
Regarding applicant’s argument that “The claims are specifically directed to a technological system that has a practical application with a specific implementation to provide an improved system for a decentralized, permissioned, and secured network of a plurality of nodes providing a distributed ledger for generating electronic credit and digital identity records using blocks stored on storage devices such that the ledger is only accessible to authorized entities having appropriate permissions” and “that the approach is directed to improving the functioning of a computer to allow multiple users and user devices to access and share comprehensive information about credit and digital identity records in a standardized block format on the distributed ledger, including real-time updates to digital identity records, credit records, and information about detected and predicted impacts on credit scores (see, for example, paragraphs [0074], [0125] and [0144]). The claimed subject matters provides these improvements while being able to identify, efficiently recover from failures and reconstruct the system state. For example, this is useful when an individual wishes to improve or fix their credit score and/or certain third parties require access to the individual’s electronic credit history records, but there are fraudulent or corrupted data stored on the distributed ledger”, the examiner disagrees. There is no improvement to the hardware devices, distributed ledger, the use of permissions attributes, the use of public or private keys, or machine learning described in the specification or claimed. The cited paragraphs [0219-0221 0110-0111 0079 0123-0125 0098 0106 0227 0181 0185 0079 0088 0089 0116 0120 0075] merely describe the underlying technological environment upon which the abstract idea is performed. There is no improvement to the underlying technological environment. Even in combination, these additional elements do not integrate the abstract idea into a practical application and do not amount to significantly more than the abstract idea itself. The access channels are claimed and described in the specification as merely generally linked to the abstract idea as sources of data to be processed. Additionally, hierarchical permission is merely a feature of distributed ledger, permissions, and communication channels (see cited references in the Conclusion section of this office action) and merely requires comparing the sources of data to a database containing permission attributes.
Regarding applicant’s argument that “The claimed system involves a security device that verifies different requesting devices using permission attributes prior to providing read access to the electronic credit history record and prior to granting write permissions to update the electronic credit history record. The permissions attributes differentiate between roles of the nodes and the requesting devices to define the roles with pre-defined authorizations to allow the nodes and the requesting devices to access data or operations based on the permissions attributes. The security device compares credentials to the permissions attributes, and manages a hierarchical model for party identities to enroll, activate, deactivate, and renew the credentials. The security device uses a public and private key infrastructure to maintain the identities while being decentralized. Further, the identity management unit integrates with identity providers to acquire additional identifiers or verify identifiers. Accordingly, the claimed system provides a particular decentralized, permissioned, and secured network of a plurality of nodes for data and event management”, the examiner disagrees. There is no improvement to the underlying technological environment. Even in combination, these additional elements do not integrate the abstract idea into a practical application and do not amount to significantly more than the abstract idea itself. The access channels are claimed and described in the specification as merely generally linked to the abstract idea as sources of data to be processed. Additionally, hierarchical permission is merely a feature of distributed ledger, permissions, and communication channels (see cited references in the Conclusion section of this office action) and merely requires comparing the sources of data to a database containing permission attributes. However, the specific use of permission attributes are merely described at a high level of generality with no further description of the specifics found in the Specification. Thus, the use of various channels is merely applied to the abstract idea of the claims.
Regarding applicant’s argument directed toward machine learning and Example 42, 46, 47, and Enfish, the machine leaning is claimed and described in the specification ([0115] [0126-0127] [0148]) at a high-level of generality such that it is generally linked its use to the abstract idea of the claims whereas, the claims in Examples 42, 46, 47, and Enfish made an improvement to a technology. Thus, Examples 42, 46, 47, and Enfish are readily distinguishable from the present claims.
Regarding applicant’s argument that “The system also provides improved fault-tolerance and resilience by enabling identification of corrupted or fraudulent data records in real time and eliminating them from the distributed ledger to contain any corruption”, the examiner maintains that the fault-tolerance and resilience by enabling identification of corrupted or fraudulent data records as disclosed and claimed invention is part of the abstract idea of the claims. There is no technical improvement to the technological environment.
Regarding applicant’s argument that “the claimed system uses a specific approach to connect with third party devices. In particular, a plurality of channel access connections with the different types of interfaces enable integration with third party devices in different channels of choice and are extensible and configurable to facilitate reusability across the third party devices, wherein the storage devices of the plurality of nodes of the distributed ledger connect to the requesting devices and the plurality of data sources by way of the plurality of channel access connections to receive data and events related to credit worthiness to record relevant events on the distributed ledger, the data and events comprising loans, transactions, payment events”, the examiner disagrees. Paragraph [0226] states that “Standalone APis or SDKs can also be provided to enable integrations within third party systems in different channels of choice. These APis can to be extensible and configurable to facilitate reusability across parties”. However, the specific APIs and SKDs are merely described at a high level of generality with no further description of the specifics found in the Specification. Thus, the use of various channels is merely applied to the abstract idea of the claims.
Regarding applicant’s argument that “The claims recite a computer system that is necessarily rooted in computer technology because the claimed subject matter exists only in relation to a decentralized, peer-to-peer, secured network in a closed loop, permissioned environment. Computer technology is utilized to provide a solution for providing data privacy and methods for securely detecting and predicting credit events from several data sources that would impact an individual’s credit score”, the examiner, again, reiterates that there is no improvement to decentralized, peer-to-peer, secured network in a closed loop, permissioned environment. The is recited at a high-level of generality such that it is generally linked its use to the abstract idea of the claims.
As such, the examiner maintains the rejection.
Conclusion
For prior art made of record and not relied upon is considered pertinent to applicant's disclosure see Notice of References Cited items A-G submitted 11/27/2024 used as prior art and in the conclusion section in the office action submitted 11/27/2024.
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 extension fee 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 date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Gregory A Pollock whose telephone number is (571) 270-1465. The examiner can normally be reached M-F 8 AM - 4 PM.
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/Gregory A Pollock/Primary Examiner, Art Unit 3691
03/06/2026