DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
The following is a Final Office Action in response to communications received Aug. 28. 2024. No Claim(s) have been canceled. No Claims have been amended. No new claims have been added. Therefore, claims 1-20 are pending and addressed below.
Priority
Application No. 18817332 filed 08/28/2024 is a Continuation in Part of 18389126 , filed 11/13/2023.
Applicant Name/Assignee: iBusiness Funding LLC
Inventor(s): Levy, Justin
Information Disclosure Statement
The IDS submitted 08/28/2024 has been reviewed and considered.
Drawings
The drawings are objected to as failing to comply with 37 CFR 1.84(p)(4) because reference character “550” has been used to designate both memory unit and power supply unit (para 0114-0115, para 0117). Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
The drawings are objected to as failing to comply with 37 CFR 1.84(p)(5) because they include the following reference character(s) not mentioned in the description: Fig. 5 ref # 540. Corrected drawing sheets in compliance with 37 CFR 1.121(d), or amendment to the specification to add the reference character(s) in the description in compliance with 37 CFR 1.121(b) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
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 instant application is directed to non-patentable subject matter. Specifically, the claims are directed toward at least one judicial exception without reciting additional elements that amount to significantly more than the judicial exception. The rationale for this determination is in accordance with the guidelines of USPTO, applies to all statutory categories, and is explained in detail below.
In reference to Claims 1-10:
STEP 1. Per Step 1 of the two-step analysis, the claims are determined to include a system, as in independent Claim 1 and the dependent claims. Such systems fall under the statutory category of "machine." Therefore, the claims are directed to a statutory eligibility category.
STEP 2A Prong 1. The claimed invention is directed to an abstract idea without significantly more. System claim 1 recites a operational process (1) acquire user data (2) analyze data (3) determine features (4) search local user database…causing …retrieval of [data], (5) generate …feature vector based on …features and …data (6) execute …model…comprising providing…vector as input to…model …predictive model is generated…producing lending parameter (5) output …data structure comprising information related to …lending verdict, …data structure …to effectuate …transfer of …assets…
The claimed limitations which under its broadest reasonable interpretation, covers performance of transaction process. The specification describes applying digital assets for loan applications as part of leverage for loan applications (para 0003). The claimed systems is applied to collect user data related to loan applications, effectuate mechanisms to remit, deny or curate loan application results for users to secure assets (para 0005) Accordingly, when considered as a whole, in light of the specification, the claimed subject matter is directed toward receiving and analyzing financial data generate feature vector data as input to a model in order to generate lending parameters and outputting data structures comprising lending verdicts to effectuate transfer of assets. Such concepts can be found in the abstract category of commercial interactions and transactions. These concepts are enumerated in Section I of the 2019 revised patent subject matter eligibility guidance published in the federal register (84 FR 50) on January 7, 2019) is directed toward abstract category of methods of organizing human activity.
STEP 2A Prong 2: The identified judicial exception is not integrated into a practical application because the claims fail to provide indications of patent eligible subject matter that integrate the alleged abstract idea into a practical application. The additional elements recited in the claim beyond the abstract idea include a system comprising “a processor”, “a network”, “artificial intelligence model” and “a predictive model”
The claimed processor applied to perform the operations of “acquire…data” over a network, “search over the network” and based on query “retrieve data”.
The predictive model applied to output data structure comprising lending verdict.
which According to MPEP 2106.05(d) II (see also MPEP 2106.05(g)) is insignificant extra solution activity. The courts have recognized the following computer functions are claimed in a merely generic manner (e.g., at a high level of generality) where technology is merely applied to perform the abstract idea or as insignificant extra-solution activity.
Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014)
Electronic recordkeeping, Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 225, 110 USPQ2d 1984 (2014) (creating and maintaining "shadow accounts"); Ultramercial, 772 F.3d at 716, 112 USPQ2d at 1755 (updating an activity log);
Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93
The claim limitations (“acquiring” [receiving], “retrieving”, “output” [transmitting] ) are recited at a high level of generality without details of technical implementation and thus are insignificant extra solution activity.
The additional element “a processor” is applied to “analyze” data to determine plurality of features, “search” a local database based on query, “generate at least one feature vector”, “execute …model” comprising “providing…feature vector as input to the …model ...”, which are processes not directed toward technology or any other indications of patent eligible subject matter but rather to apply technology to analyze user data for lending analysis and to vectorize data which is mere data manipulation that is inputted into a model for analysis in order to generate lending parameters
The additional element “artificial intelligence model” applied to “generate…at least one lending parameter” which is a process that is not directed toward technology but rather a commercial activity.
The operations performed by the “processor” and “model” are recited at a high-level of generality such that it amounts to no more than applying the exception using generic computer components for the purpose of analyzing financial transaction data to mitigate fraud and perform a deposit transaction. The claim limitations when considered individually fail to provide any indications of patent eligible subject matter, according to MPEP guidance (see MPEP 2106.05 (a)-(c), (e )-(h).
(i) an improvement to the functioning of a computer;
(ii) an improvement to another technology or technical field;
(iii) an application of the abstract idea with, or by use of, a
particular machine;
(iv) a transformation or reduction of a particular article to a
different state or thing; or
(v) other meaningful limitations beyond generally linking the
use of the abstract idea to a particular technological environment.
When the claims are taken as an ordered combination or as a whole, the combination of limitations, the combination of limitations (1) “acquire”, (2) “analyze” data and (3) “determine based on analysis features” and (4) “search database based on query for retrieval of user related data that corresponds to determined features of limitations (1)-(3) which is directed toward collecting, analyzing and manipulating user data for a financial activity. The limitations (5) generate a vector feature from limitations 1-4 combined with limitation (6) executing a model comprising the vector of limitation (5) for input to the model where the model generates a predictive model that produces a lending parameter – which as a combination is mot directed toward technology but rather applying a model to analyze manipulated inputted data in order to generate a lending parameter which is a for a financial activity. The combination of limitations 1-6 and (7) “output…data structure comprising information related to lending verdict…”
– which when considered as a combinations is directed toward collecting, analyzing user data in order to generate lending parameters and output lending verdict which is not an indication of patent eligibility under step 2A, but rather a commercial interaction.
MPEP guidance (see MPEP 2106.05 (a)-(c), (e )-(h). The claim limitations as a whole, as an ordered combination and the combination of steps not integrate the judicial exception into a practical application as the claim process fails to impose meaningful limits upon the abstract idea. This is because the claimed subject matter fails to provide additional elements or combination or elements that go beyond applying technology as a tool to perform the identified abstract idea. The functions recited by the mobile device in the claims recite the concept of a financial activity. The claim limitations and specification lacks technical disclosure on what the technical problem was and how the claimed limitations provide a technical solution to a technical problem rather than a solution to a problem found in the abstract idea. Taking the claim elements separately, or as a combination, the operation performed by the mobile device processor and communication unit at each step of the process is purely in terms of results desired and devoid of implementation of details. Technology is not integral to the process as the claimed subject matter is so high level that any generic programming could be applied and the functions could be performed by any known means. Furthermore, the claimed functions do not provide an operation that could be considered as sufficient to provide a technological implementation or application of/or improvement to this concept (i.e. integrated into a practical application).
The integration of elements do not improve upon technology or improve upon computer functionality or capability in how computers carry out one of their basic functions. The integration of elements do not provide a process that allows computers to perform functions that previously could not be performed. The integration of elements do not provide a process which applies a relationship to apply a new way of using an application. The limitations do not recite a specific use machine or the transformation of an article to a different state or thing. The limitations do not provide other meaningful limits beyond generally linking the use of the abstract idea to a particular technological environment. The resource claimed performing the steps is merely a “field of use” application of technology. The instant application, therefore, still appears only to implement the abstract idea to the particular technological environments apply what generic computer functionality in the related arts. The steps are still a combination made to perform a financial activity and does not provide any of the determined indications of patent eligibility set forth in the 2019 USPTO 101 guidance. The additional steps only add to those abstract ideas using generic functions, and the claims do not show improved ways of, for example, an particular technical function for performing the abstract idea that imposes meaningful limits upon the abstract idea. Moreover, Examiner was not able to identify any specific technological processes that goes beyond merely confining the abstract idea in a particular technological environment, which, when considered in the ordered combination with the other steps, could have transformed the nature of the abstract idea previously identified. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim provides no technical details regarding how the operations performed by the “resource”. Instead, similar to the claims at issue in Intellectual Ventures I LLC v. Capital One Financial Corp., 850 F.3d 1332 (Fed. Cir. 2017), “the claim language . . . provides only a result-oriented solution with insufficient detail for how a computer accomplishes it. Our law demands more.” Intellectual Ventures, 850 F.3d at 1342 (citing Elec. Power Grp. LLC v. Alstom, S.A., 830 F.3d 1350, 1356 (Fed. Cir. 2016)). The claim is directed to 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 as discussed above with respect to concepts of the abstract idea into a practical application. The additional elements recited in the claim beyond the abstract idea include a system comprising “a processor”, “a network”, “artificial intelligence model” and “a predictive model”
Taking the claim elements separately, the function performed by the computer elements at each step of the process is purely conventional. Using computer components (processor, network, artificial intelligence model and predictive model) to perform the operations “acquire”, “analyze”, “determine”, “search”, “retrieval”, “generate”, “execute…model…providing …vector as input”, “producing …lending vector”, “output…data structure comprising information…” ----are some of the most basic functions of a computer.
The claimed operations of the artificial intelligence model and predictive model amounts to no more than mere instructions to “apply” the abstract idea. According to Alice, limitations that are “applied” (or an equivalent) with the abstract idea as mere instructions to implement the abstract idea on a computer or requiring no more than a generic compute to perform generic computer functions that are well understood activities known to the industry, are not enough to qualify as “significantly more”. As a result, none of the hardware recited by the system claims offers a meaningful limitation beyond generally linking the use of the method to a particular technological environment, that is, implementation via computers.... The claim limitations do not recite that any of the “devices” perform more than a high level generic function .... None of the limitations recite technological implementation details for any of these steps, but instead recite only results desired to be achieved by any and all possible means. .. . Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept.
When the claims are taken as a whole, as an ordered combination, the combination of steps does not add “significantly more” by virtue of considering the steps as a whole, as an ordered combination. All of these computer functions are generic, routine, conventional computer activities that are performed only for their conventional uses. See Elec. Power Grp. v. Alstom S.A., 830 F.3d 1350, 1353 (Fed. Cir. 2016). Also see In re Katz Interactive Call Processing Patent Litigation, 639 F.3d 1303, 1316 (Fed. Cir. 2011) Absent a possible narrower construction of the terms “acquire”, “analyze”, “determine”, “search”, “retrieval”, “generate”, “execute…model…providing …vector as input”, “producing …lending vector”, “output…data structure comprising information…” , whether considered individually or as a sequence combination ... are functions can be achieved by any general purpose computer without special programming. None of these activities are used in some unconventional manner nor do any produce some unexpected result. In short, each step does no more than require a generic computer to perform generic computer functions.
As to the data operated upon, "even if a process of collecting and analyzing information is 'limited to particular content' or a particular 'source,' that limitation does not make the collection and analysis other than abstract." SAP America, Inc. v. Invest Pic LLC, 898 F.3d 1161, 1168 (Fed. Cir. 2018). Considered as an ordered combination, the computer components of Applicant’s claimed functions add nothing that is not already present when the steps are considered separately. The sequence of data reception-analysis modification-output is equally generic and conventional. See Ultramercial, Inc. v. Hulu, LLC, 772 F.3d 709, 715 (Fed. Cir. 2014) (“acquire”, “analyze”, “determine”, “search”, “retrieval”, “generate”, “execute…model…providing …vector as input”, “producing …lending vector”, “output…data structure comprising information…” recited as an abstraction), Inventor Holdings, LLC v. Bed Bath & Beyond, Inc., 876 F.3d 1372, 1378 (Fed. Cir. 2017) (sequence of data retrieval, analysis, modification, generation, display, and transmission), Two-Way Media Ltd. v. Comcast Cable Communications, LLC, 874 F.3d 1329, 1339 (Fed. Cir. 2017) (sequence of processing, routing, controlling, and monitoring). The ordering of the steps is therefore ordinary and conventional. The analysis concludes that the claims do not provide an inventive concept because the additional elements recited in the claims do not provide significantly more than the recited judicial exception.
According to 2106.05 well-understood and routine processes to perform the abstract idea is not sufficient to transform the claim into patent eligibility. As evidence the examiner provides:
[0007] In accordance with one or more embodiments, a system is provided that includes one
or more processors and/or computing devices configured to provide functionality in accordance
with such embodiments. In accordance with one or more embodiments, functionality is embodied
in steps of a method performed by at least one computing device. In accordance with one or more
embodiments, program code (or program logic) executed by a processor(s) of a computing device
to implement functionality in accordance with one or more such embodiments is embodied in, by
and/or on a non-transitory computer-readable medium
[0028] Certain embodiments and principles will be discussed in more detail with reference to
the figures. According to some embodiments, the present disclosure provides systems and methods for a DI-based framework that can perform automated loan processing/approval based on users 'related data. As discussed herein, a user should be understood to be a user or entity, and for
purposes of this disclosure will be referenced as a "user" without limiting the scope, as understood
by those of ordinary skill in the art. As discussed below, the disclosed DI framework can
implement any type of known or to be known artificial intelligence and/or machine learning
(Al/ML) algorithms, techniques, models, and the like.
[0074] In some embodiments, the electronic documents (e.g., digital assets) can be securely
stored in a database, which as discussed herein, can be any type of known or to be known
centralized or decentralized storage. For example, the storage can be a public blockchain, private
blockchain, look-up table (LUT), memory, memory stack, distributed ledger and/or any other type
of secure data repository.
[0076] At block 304, the processor 204 may parse the user data to derive a plurality of features.
According to some embodiments, processor 204 can analyze the user data by parsing the data, and extracting, deriving or otherwise identifying the plurality of features.
[0077] In some embodiments, as discussed above, such analysis can be performed via process
204 implementing any type of known or to be known computational analysis technique, algorithm,
mechanism or technology to analyze the user data.
[0078] In some embodiments, processor 204 may execute and/or include a specific trained
artificial intelligence / machine learning model (Al/ML), a particular machine learning model
architecture, a particular machine learning model type (e.g., convolutional neural network (CNN),
recurrent neural network (RNN), autoencoder, support vector machine (SVM), and the like), or
any other suitable definition of a machine learning model or any suitable combination thereof.
[0115] Consistent with an embodiment of the disclosure, the aforementioned CPU 520, the
bus 530, the memory unit 550, a PSU 550, and the plurality of 1/0 units 560 may be implemented
in a computing device, such as computing device 500. Any suitable combination of hardware,
software, or firmware may be used to implement the aforementioned units. For example, the CPU
520, the bus 530, and the memory unit 550 may be implemented with computing device 500 or
any of other computing devices 500, in combination with computing device 500. The
aforementioned system, device, and components are examples and other systems, devices, and
components may comprise the aforementioned CPU 520, the bus 530, the memory unit 550,
consistent with embodiments of the disclosure.
[0116] At least one computing device 500 may be embodied as any of the computing elements
illustrated in all of the attached figures, including the LS node 102 (FIG. 2). A computing device
500 does not need to be electronic, nor even have a CPU 520, nor bus 530, nor memory unit 550.
The definition of the computing device 500 to a person having ordinary skill in the art is "A device
that computes, especially a programmable [usually] electronic machine that performs high-speed
mathematical or logical operations or that assembles, stores, correlates, or otherwise processes
information." Any device which processes information qualifies as a computing device 500,
especially if the processing is purposeful.
The instant application, therefore, still appears to only implement the abstract ideas to the particular technological environments using what is generic components and functions in the related arts. The claim is not patent eligible.
The remaining dependent claims—which impose additional limitations—also fail to claim patent-eligible subject matter because the limitations cannot be considered statutory. In reference to claims 2-10 these dependent claim have also been reviewed with the same analysis as independent claim 1. Dependent claim 2 is directed toward performing the operations “receive …data”, “derive a language metadata” and “parse call data based on language metadata to derive a plurality of key features” which is directed toward data manipulation, organization and categorization- directed toward data organization and not the technology itself. For data, mere “manipulation” of basic mathematical constructs [i.e.,] the paradigmatic ‘abstract idea,’" has not been deemed a transformation. CyberSource v. Retail Decisions, 654 F.3d 1366, 1372 n.2, 99 USPQ2d 1690, 1695 n.2 (Fed. Cir. 2011) (quoting /n re Warmerdam, 33 F.3d 1354, 1355, 1360 (Fed. Cir. 1994). (see MPEP 2106.05(a) I). Dependent claim 3 is directed toward “retrieve …data”-insignificant extra solution activity. Dependent claim 4 is directed toward “generate…feature vector” -mere data manipulation and not the technology itself - CyberSource v. Retail Decisions, 654 F.3d 1366, 1372 n.2, 99 USPQ2d 1690, 1695 n.2 (Fed. Cir. 2011) (quoting /n re Warmerdam, 33 F.3d 1354, 1355, 1360 (Fed. Cir. 1994). Dependent claim 5 is directed toward “generate …user profile data…”- directed toward data organization and not the technology itself (see MPEP 2106.05(a) I. Dependent claim 6 is directed toward “periodically monitor…user profile data… [for a condition]” -insignificant extra solution activity. Dependent claim 7 is directed toward “responsive to …value of …user data deviating from the value of the previous user profile data…exceeding the pre-set threshold value”, “generate an updated feature vector…” and “generate the lending verdict…”- directed toward based on data value parameter generating updated vectors for analysis to generate a lending verdict -which is analyzing financial data to generate financial parameter a business practice. Dependent claim 8 is directed toward record lending parameter on …ledger- insignificant extra solution activity. Dependent claim 9 is directed toward “retrieve …parameter from the blockchain responsive to …consensus among LS node and …lender entity node”- insignificant extra solution activity. Dependent claim 10 is directed toward “execute smart contract to record data…” -insignificant extra solution activity.
The dependent claim(s) have been examined individually and in combination with the preceding claims, however they do not cure the deficiencies of claim 1. Where all claims are directed to the same abstract idea, “addressing each claim of the asserted patents [is] unnecessary.” Content Extraction & Transmission LLC v. Wells Fargo Bank, Nat 7 Ass ’n, 776 F.3d 1343, 1348 (Fed. Cir. 2014). If applicant believes the dependent claims 2-10 are directed towards patent eligible subject matter, they are invited to point out the specific limitations in the claim that are directed towards patent eligible subject matter.
In reference to Claims 11-16:
STEP 1. Per Step 1 of the two-step analysis, the claims are determined to include a method, as in independent Claim 11 and the dependent claims. Such methods fall under the statutory category of "process." Therefore, the claims are directed to a statutory eligibility category.
STEP 2A Prong 1. The steps of Method claim 11 corresponds to operations of system claim 1. Therefore, claim 11 has been analyzed and rejected as being directed toward an abstract idea of the categories of concepts directed toward methods of organizing human activity previously discussed with respect to claim 1.
STEP 2A Prong 2: The steps of Method claim 11 corresponds to operations of system claim 1. The additional elements recited in the claim beyond the abstract idea include a “device”, “artificial intelligence model” and “predictive model” where the device performs the steps corresponding to the system processor of claim 1 and the “artificial intelligence model” and “predictive model” perform the steps corresponding to the operations performed by the “artificial intelligence model” and “predictive model” of claim 1. Therefore, claim 11 has been analyzed and rejected as failing to provide limitations that are indicative of integration into a practical application, as previously discussed with respect to claim 1.
STEP 2B; The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because as discussed above with respect to concepts of the abstract idea into a practical application. The additional elements beyond the abstract idea include a “device”, “artificial intelligence model” and “predictive model” –is purely functional and generic. Nearly every computer device for implementing a method is capable of performing the basic computer functions -of “acquiring…data”, “analyzing…data”, “searching….database”, “search causing …retrieval…data”, “generating…feature vector”, “executing…model…providing vector feature as input to model”, “generate predictive model”, the “predictive model” output…data structure…lending verdict” - As a result, none of the hardware or models recited by the method claims offers a meaningful limitation beyond generally linking the use of the method to a particular technological environment, that is, implementation via computers.
The steps of Method claim 11 steps corresponds to system functions claim 1. Therefore, claim 11 has been analyzed and rejected as failing to provide additional elements that amount to an inventive concept –i.e. significantly more than the recited judicial exception. Furthermore, as previously discussed with respect to claim 1, the limitations when considered individually, as a combination of parts or as a whole fail to provide any indication that the elements recited are unconventional or otherwise more than what is well understood, conventional, routine activity in the field.
According to 2106.05 well-understood and routine processes to perform the abstract idea is not sufficient to transform the claim into patent eligibility. As evidence the examiner provides:
[0028] Certain embodiments and principles will be discussed in more detail with reference to
the figures. According to some embodiments, the present disclosure provides systems and methods for a DI-based framework that can perform automated loan processing/approval based on users 'related data. As discussed herein, a user should be understood to be a user or entity, and for
purposes of this disclosure will be referenced as a "user" without limiting the scope, as understood
by those of ordinary skill in the art. As discussed below, the disclosed DI framework can
implement any type of known or to be known artificial intelligence and/or machine learning
(Al/ML) algorithms, techniques, models, and the like.
[0074] In some embodiments, the electronic documents (e.g., digital assets) can be securely
stored in a database, which as discussed herein, can be any type of known or to be known
centralized or decentralized storage. For example, the storage can be a public blockchain, private
blockchain, look-up table (LUT), memory, memory stack, distributed ledger and/or any other type
of secure data repository.
[0076] At block 304, the processor 204 may parse the user data to derive a plurality of features.
According to some embodiments, processor 204 can analyze the user data by parsing the data, and extracting, deriving or otherwise identifying the plurality of features.
[0077] In some embodiments, as discussed above, such analysis can be performed via process
204 implementing any type of known or to be known computational analysis technique, algorithm,
mechanism or technology to analyze the user data.
[0078] In some embodiments, processor 204 may execute and/or include a specific trained
artificial intelligence / machine learning model (Al/ML), a particular machine learning model
architecture, a particular machine learning model type (e.g., convolutional neural network (CNN),
recurrent neural network (RNN), autoencoder, support vector machine (SVM), and the like), or
any other suitable definition of a machine learning model or any suitable combination thereof.
[0114] Embodiments of the present disclosure may comprise a computing device having a
central processing unit (CPU) 520, a bus 530, a memory unit 550, a power supply unit (PSU) 550,
and one or more Input/ Output (1/0) units. The CPU 520 coupled to the memory unit 550 and the
plurality of 1/0 units 560 via the bus 530, all of which are powered by the PSU 550. It should be
understood that, in some embodiments, each disclosed unit may actually be a plurality of such
units for the purposes of redundancy, high availability, and/or performance. The combination of
the presently disclosed units is configured to perform the stages of any method disclosed herein.
[0115] Consistent with an embodiment of the disclosure, the aforementioned CPU 520, the
bus 530, the memory unit 550, a PSU 550, and the plurality of 1/0 units 560 may be implemented
in a computing device, such as computing device 500. Any suitable combination of hardware,
software, or firmware may be used to implement the aforementioned units. For example, the CPU
520, the bus 530, and the memory unit 550 may be implemented with computing device 500 or
any of other computing devices 500, in combination with computing device 500. The
aforementioned system, device, and components are examples and other systems, devices, and
components may comprise the aforementioned CPU 520, the bus 530, the memory unit 550,
consistent with embodiments of the disclosure.
The instant application, therefore, still appears to only implement the abstract ideas to the particular technological environments using what is generic components and functions in the related arts. The claim is not patent eligible.
The remaining dependent claims—which impose additional limitations—also fail to claim patent-eligible subject matter because the limitations cannot be considered statutory. In reference to claims 12-16 these dependent claim have also been reviewed with the same analysis as independent claim 11. The steps of Dependent claim 12 corresponds to the operations of dependent claim 2. Therefore, dependent claim 12 has been analyzed and rejected as previously discussed with respect to claim 2. The steps of Dependent claim 13 corresponds to the operations of dependent claim 3. Therefore, dependent claim 13 has been analyzed and rejected as previously discussed with respect to claim 3. The steps of Dependent claim 14 corresponds to the operations of dependent claim 4. Therefore, dependent claim 14 has been analyzed and rejected as previously discussed with respect to claim 4. Dependent claim 15 is directed toward generating a user profile data based on data sets to determine if value of user profile data deviates from a value of previous user profile data by margin exceeding pre-set threshold value- analyzing and organizing user transaction data to determine value deviations according to threshold margins applied for a business practice. The steps of Dependent claim 16 corresponds to the operations of dependent claim 7. Therefore, dependent claim 16 has been analyzed and rejected as previously discussed with respect to claim 7.
The dependent claim(s) have been examined individually and in combination with the preceding claims, however they do not cure the deficiencies of claim 1. Where all claims are directed to the same abstract idea, “addressing each claim of the asserted patents [is] unnecessary.” Content Extraction & Transmission LLC v. Wells Fargo Bank, Nat 7 Ass ’n, 776 F.3d 1343, 1348 (Fed. Cir. 2014). If applicant believes the dependent claims 2-10 are directed towards patent eligible subject matter, they are invited to point out the specific limitations in the claim that are directed towards patent eligible subject matter.
In reference to Claims 17-20:
STEP 1. Per Step 1 of the two-step analysis, the claims are determined to include a non-transitory computer-readable medium, as in independent Claim 17 and the dependent claims. Such mediums fall under the statutory category of "manufacture." Therefore, the claims are directed to a statutory eligibility category.
STEP 2A Prong 1. The instructions of medium claim 17 corresponds to operations of system claim 1. Therefore, claim 17 has been analyzed and rejected as being directed toward an abstract idea of the categories of concepts directed toward methods of organizing human activity previously discussed with respect to claim 1.
STEP 2A Prong 2: The instructions of medium claim 17 corresponds to operations of system claim 1. The additional elements recited in the claim beyond the abstract idea include a “non-transitory computer-readable medium encoded with computer-executable instructions …executed by a processor of a device” performs the instruction corresponding to the system processor of claim 1 and the “artificial intelligence model” and “predictive model” perform the instructions corresponding to the operations performed by the “artificial intelligence model” and “predictive model” of claim 1. Therefore, claim 17 has been analyzed and rejected as failing to provide limitations that are indicative of integration into a practical application, as previously discussed with respect to claim 1.
STEP 2B; The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because as discussed above with respect to concepts of the abstract idea into a practical application. The additional elements beyond the abstract idea include a “non-transitory computer-readable medium encoded with computer-executable instructions …executed by a processor of a device”, “artificial intelligence model” and “predictive model” –is purely functional and generic. Nearly every computer device for implementing a method is capable of performing the basic computer functions -of “acquiring…data”, “analyzing…data”, “searching….database”, “search causing …retrieval…data”, “generating…feature vector”, “executing…model…providing vector feature as input to model”, “generate predictive model”, the “predictive model” output…data structure…lending verdict” - As a result, none of the hardware executable instructions or models recited by the method claims offers a meaningful limitation beyond generally linking the use of the method to a particular technological environment, that is, implementation via computers. Even though the claim is directed to a manufacture, the claim is not "truly drawn to a specific" computer readable medium, but rather is directed toward the method of performing the identified abstract idea. Furthermore, the "incidental use" of a computer does not allow the claim to meet the Alice 2A or 2B requirements, by providing “significantly more” than the identified abstract idea.
The instructions of medium claim 17 steps correspond to system functions claim 1. Therefore, claim 17 has been analyzed and rejected as failing to provide additional elements that amount to an inventive concept –i.e. significantly more than the recited judicial exception. Furthermore, as previously discussed with respect to claim 1, the limitations when considered individually, as a combination of parts or as a whole fail to provide any indication that the elements recited are unconventional or otherwise more than what is well understood, conventional, routine activity in the field.
According to 2106.05 well-understood and routine processes to perform the abstract idea is not sufficient to transform the claim into patent eligibility. As evidence the examiner provides:
[0067] The LS node 102 may also include a non-transitory computer readable medium 212
that may have stored thereon machine-readable instructions executable by the processor 204.
Examples of the machine-readable instructions are shown as 214-222 and are further discussed
below. Examples of the non-transitory computer readable medium 212 may include an electronic,
magnetic, optical, or other physical storage device that contains or stores executable instructions.
For example, the non-transitory computer readable medium 212 may be a Random-Access
memory (RAM), an Electrically Erasable Programmable Read-Only Memory (EEPROM), a hard
disk, an optical disc, or other type of storage device.
[0106]… The above embodiments of the present disclosure may be implemented in hardware, in computer-readable instructions executed by a processor, in firmware, or in a combination of the above. The computer computer readable instructions may be embodied on a computer-readable medium, such as a storage medium. For example, the computer computer-readable instructions may reside in random access memory ("RAM"), flash memory, read-only memory ("ROM"), erasable programmable read-only
memory ("EPROM"), electrically erasable programmable read-only memory ("EEPROM"),
registers, hard disk, a removable disk, a compact disk read-only memory ("CD-ROM"), or any
other form of storage medium known in the art.
The instructions of Dependent claim 18 corresponds to the operations of dependent claim 8. Therefore, dependent claim 18 has been analyzed and rejected as previously discussed with respect to claim 8. The instructions of Dependent claim 19 corresponds to the operations of dependent claim 9. Therefore, dependent claim 19 has been analyzed and rejected as previously discussed with respect to claim 9. The instructions of Dependent claim 20 corresponds to the operations of dependent claim 10. Therefore, dependent claim 20 has been analyzed and rejected as previously discussed with respect to claim 10.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1, 11 and 17 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by US Pub No. 2020/0302335 A1 by Golding (Golding)
In reference to Claim 1:
Golding teaches:
A system ((Golding) in at least para 0006) comprising:
a processor ((Golding) in at least FIG. 14A; para 0006, para 0009, para 0167) configured to:
acquire, over a network, user data from an entity ((Golding) in at least para 0153, para 0176);
analyze the user data by performing a computational analysis on the user data, and determine, based on the computational analysis, a plurality of features ((Golding) in at least para 0078, para 0080, para 0096-0097, para 0121-0122, para 0128, para 0181);
search, over the network, a local users database based on a query comprising the plurality of features, the search causing electronic retrieval of local historical users-related data that corresponds to the plurality of features ((Golding) in at least para 0027 wherein the prior art teaches information about users include loan history of the user, para 0141-0143 wherein the prior art teaches the database includes list of records and transaction data, para 0182, para 0184-0185);
generate at least one feature vector based on the plurality of features and the local historical users-related data ((Golding) in at least para 0005-0008, para 0026-0027, para 0033, para 0044, para 0046, para 0049, para 0122-0125, para 0141-0143 wherein the prior art teaches the database includes list of records and transaction data);
execute an artificial intelligence / machine learning (AI/ML) model, the execution comprising providing the at least one feature vector as input to the AI/ML model, such that a predictive model is generated, the predictive model producing at least one lending parameter ((Golding) in at least Abstract; para 0005-0006, para 0008, para 0026-0027, para 0033, para 0044-0045, para 0046, para 0049, para 0052, para 0056, para 0063, para 0072, para 0094, para 0122-0124, para 0128-0130, para 0146, para 0149, para 0165, para 0172-0173); and
output, based on execution of the AI/ML model via the predictive model, a data structure comprising information related to a user-related lending verdict, the data structure being executable so as to effectuate a secure transfer of digital assets to an electronic account of the user ((Golding) in at least para 0028-0029, para 0031, para 0036, para 0053-0054, para 0056, para 0060, para 0072, para 0090, para 0146).
In reference to Claim 11:
Golding teaches:
The steps of method claim 11 correspond to the operations of system claim 1. The additional limitations recited in claim 1 that go beyond the limitations of claim 1 include a “device” ((Golding) in at least para 0025, para 0030) to perform the operation that correspond to claim 1. Therefore, claim 11 has been analyzed and rejected as previously discussed with respect to claim 1.
In reference to Claim 17:
Golding teaches:
The instructions of medium claim 17 executed by a processor correspond to the operations of system claim 1. The additional limitations recited in claim 17 that go beyond the limitations of claim 1 include a “non-transitory computer readable medium comprising instructions executable by a processor, ((Golding) in at least abstract; para 0008, para 0171) to perform the operation that correspond to claim 1. Therefore, claim 17 has been analyzed and rejected as previously discussed with respect to claim 1.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
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.
Claim(s) 2 of claim 1 above; Claim(s) 12 of claim 11 above is/are rejected under 35 U.S.C. 103 as being unpatentable over US Pub No. 2020/0302335 A1 by Golding (Golding) as applied to claim 1 above, and further in view of US Patent No. 11,860,852 B1 by Harvey (Harvey) and US Pub No. 2020/0311808 A1 by Srivastava et al. (Srivastava).
In reference to Claim 2:
Golding teaches:
The system of claim 1 (see rejection of claim 1 above), wherein the processor is further configured to:
Golding does not explicitly teach:
receive user call data from a chat bot associated with the at least on lender entity node, the call data comprising data generated during user’s communication with the chat bot;
derive a language metadata from the call data; and
parse the call data based on the language metadata to derive a plurality of key features.
Harvey teaches:
receive user call data from a chat bot associated with the at least on lender entity …, the call data comprising data generated during user’s communication with the chat bot ((Harvey) in at least Abstract; Col 2 lines 5-11, Col 2 lines 24-33, Col 4 lines 20-24, lines 47-67, Col 6 lines 29-39, Col 8 lines 5-13);
derive a language metadata from the call data ((Harvey) in at least Col 4 lines 47-67, Col 6 lines 39-51, Col 8 lines 5-18, 31-50); and
parse the call data based on the language metadata to derive a plurality of key features. ((Harvey) in at least abstract; Col 2 lines 11-15, lines 31-37, Col 6 lines 53- Col 7 lines 1-15, lines 27-37, Col 12 lines 10-18)
Both Golding and Harvey are directed toward collecting data for loan 38. applications. Harvey teaches the motivation of applying chatbot for collecting data as well as parsing call data to derive key features in order to verify the veracity of statements. It would have been obvious to one having ordinary skill at the time of effective filing the invention to modify Ref. Golding to include chatbot for collecting data of in Ref. Harvey since Harvey teaches the motivation of applying chatbot for collecting data as well as parsing call data to derive key features in order to verify the veracity of statements.
Srivastava teaches:
associated with the at least on lender entity node receive borrower data ((Srivastava) in at least para 0027-0028, para 0038-0039, para 0042-0043, para 0045, para 0084)
Both Golding and Srivastava are directed toward collecting data for loan applications that applies blockchain node technology to represent features of a loan process. Srivastava teaches the motivation of blockchain nodes being established for entities such as lenders in order to model lender approvals. It would have been obvious to one having ordinary skill at the time of effective filing the invention to modify Ref. Golding to include lender node feature in Ref. Srivastava since Srivastava teaches the motivation of blockchain nodes being established for entities such as lenders in order to model lender approvals.
In reference to Claim 12:
Golding teaches:
The steps of method claim 12 corresponds to operations of system claim 2. Therefore, claim 12 has been analyzed and rejected as previously discussed with respect to claim 2
Claim(s) 3-8 and 10 of claim 2 above, Claims 13-16 of claim 12 above; and Claims(s) 18 and 20 of claim 17 above is/are rejected under 35 U.S.C. 103 as being unpatentable over US Pub No. 2020/0302335 A1 by Golding (Golding) in view of US Patent No. 11,860,852 B1 by Harvey (Harvey) and US Pub No. 2020/0311808 A1 by Srivastava et al. (Srivastava) as applied to claim 2 above, and further in view of US Pub No. 2020/010491 A1 by Suvajac et al (Suvajac)
In reference to Claim 3:
The combination of Golding, Harvey and Scrivastava discloses the limitations of dependent claim 2. Golding further discloses the limitations of dependent claim 3
The system of claim 2 (see rejection of claim 2 above), wherein the processor is further configured to
Golding does not explicitly teach:
retrieve remote historical users’-related data from at least one remote users’ database based on the local historical users’-related data, wherein the remote historical users’-related data is collected at locations associated with a plurality of lender entities affiliated with financial institutions.
Harvey teaches:
retrieve remote historical users’-related data from at least one remote users’ database based on the …historical users’-related data, wherein the remote historical users’-related data is collected at locations associated with a plurality of lender entities affiliated with financial institutions. ((Harvey) in at least Col 2 lines 5-10, lines 30-35, Col 4 lines 10-17, Col 5 lines 60-67, Col 6 lines 11-13 wherein the prior art teaches records may be retrieved from a plurality of different sources such as a database or another computing device associated with a third party; Col 10 lines 66-Col 11 lines 1-10)
Both Golding and Harvey are directed toward analyzing financial data with respect to loan applications. Harvey teaches the motivation of analyzing historical user financial statements in order to identify indicators of inaccurate/false or true values or aspects in the historical statements. It would have been obvious to one having ordinary skill at the time of effective filing the invention to modify Ref. Golding to analyze historical data from a plurality of different sources as taught by Harvey since Harvey teaches the motivation of analyzing historical user financial statements in order to identify indicators of inaccurate/false or true values or aspects in the historical statements
Suvajac teaches:
retrieve remote historical users’-related data from at least one remote users’ database based on the local historical users’-related data, wherein the remote historical users’-related data is collected at locations associated with a plurality of lender entities affiliated with financial institutions. ((Suvajac) in at least para 0004-0005, para 0030, para 0032-0034, para 0037-0041, para 0050, para 0057-0058, para 0062, para 0064, para 0068-0069, para 0077)
Both Golding and Suvajac are directed toward collecting data related to loans and transactions. Suvajac teaches the motivation of collecting remote historical data of users collected at locations associated with a plurality of lender entities in order to determine the amount of available credit. It would have been obvious to one having ordinary skill at the time of effective filing the invention to modify Ref. Golding to include historical financial data of Suvajac since It would have been obvious to one having ordinary skill at the time of effective filing the invention to modify Ref. Golding to include lender historical data of Suvajac.
In reference to Claim 4:
The combination of Golding, Harvey, Scrivastava and Suvajac discloses the limitations of dependent claim 3. Golding further discloses the limitations of dependent claim 4.
The system of claim 3 (see rejection of claim 3 above),
wherein the processor is further configured to generate the at least one feature vector based on the plurality of features and the local historical users’-related data combined with the remote historical users’-related data and the plurality of key features. ((Golding) in at least para 0005-0008, para 0026-0027, para 0033, para 0044, para 0046, para 0049, para 0070, para 0122-0125, para 0027 wherein the prior art teaches information about users include loan history of the user, para 0141-0143 wherein the prior art teaches the database includes list of records and transaction data, para 0184, para 0186).
Srivastave teaches:
…the plurality of features and the local historical borrowers'-related data combined with the remote historical borrowers'-related data and the plurality of key features ((Srivastave) in at least para 0044-0045, para 0058, para 0072, para 0075, para 0077-0078),
Both Golding and Srivastave are directed toward collecting loan application data.
Srivastave teaches the motivation of different historical borrower related data in order to determine risk for lenders in a loan application. It would have been obvious to one having ordinary skill at the time of effective filing the invention to modify Ref. Golding to nclude the borrowers historical related data of Srivastave since Srivastave teaches the motivation of different historical borrower related data in order to determine risk for lenders in a loan application.
In reference to Claim 5:
The combination of Golding, Harvey, Scrivastava and Suvajac discloses the limitations of dependent claim 4. Golding further discloses the limitations of dependent claim 5.
The system of claim 4 (see rejection of claim 4 above), wherein the processor is further configured to
generate a user profile data based on the user data and the plurality of key features. ((Golding) in at least para 0070)
In reference to Claim 6:
The combination of Golding, Harvey, Scrivastava and Suvajac discloses the limitations of dependent claim 5. Golding further discloses the limitations of dependent claim 6.
The system of claim 5 (see rejection of claim 5 above), wherein the processor is further configured to
periodically monitor the user profile data to determine if at least one value of the user profile data deviates from a value of previous user profile data by a margin exceeding a pre-set threshold value.
Suvajac teaches:
periodically monitor the user profile data to determine if at least one value of the user profile data deviates from a value of previous user profile data by a margin exceeding a pre-set threshold value.((Suvajac) in at least para 0097-0099, para 0142)
Both Golding and Suvajac are directed toward collecting data for determining risk 46. for loan applications. Suvajac teaches the motivation of monitoring profile exchanges of data in order to determine probability of change in metric value of risk It would have been obvious to one having ordinary skill at the time of effective filing the invention to modify Ref. Golding credit analysis to include the periodic profile monitoring of Suvajac since Suvajac teaches the motivation of monitoring profile exchanges of data in order to determine probability of change in metric value of risk
In reference to Claim 7:
The combination of Golding, Harvey, Scrivastava and Suvajac discloses the limitations of dependent claim 6. Golding further discloses the limitations of dependent claim 7
The system of claim 6 (see rejection of claim 6 above),
wherein the processor is further configured to, responsive to the at least one value of the user profile data deviating from the value of the previous user profile data by the margin exceeding the pre-set threshold value, generate an updated feature vector based on current user profile data and generate the lending verdict based on the at least one lending parameter produced by the predictive model in response to the updated feature vector.
Suvajac teaches:
wherein the processor is further configured to, responsive to the at least one value of the user profile data deviating from the value of the previous user profile data by the margin exceeding the pre-set threshold value ((Suvajac) in at least para 0097-0099, para 0105, para 0118-0119, para 0142), generate an updated feature vector based on current user profile data and generate the lending verdict based on the at least one lending parameter produced by the predictive model in response to the updated feature vector. ((Suvajac) in at least para 0045, para 0074, para 0086-0088, para 0102-0104).
Both Golding and Suvajac are directed toward collecting data for determining risk for loan applications where a lending verdict and parameter is determined and outputted. Suvajac teaches the motivation of monitoring profile exchanges of data in order to determine probability of change in metric value of risk It would have been obvious to one having ordinary skill at the time of effective filing the invention to modify Ref. Golding loan analysis to include the periodic profile monitoring of Suvajac since Suvajac teaches the motivation of monitoring profile exchanges of data in order to determine probability of change in metric value of risk
In reference to Claim 8:
The combination of Golding, Harvey, Scrivastava and Suvajac discloses the limitations of dependent claim 7. Golding further discloses the limitations of dependent claim 8
The system of claim 7 (see rejection of claim 7 above),
wherein the processor is further configured to record the at least one lending parameter on a blockchain ledger along with the user profile data. ((Golding) in at least abstract; para 0005, para 0007, para 0140-0143)
In reference to Claim 10:
The combination of Golding, Harvey, Scrivastava and Suvajac discloses the limitations of dependent claim 8. Golding further discloses the limitations of dependent claim 10
The system of claim 8 (see rejection of claim 8 above), wherein the processor is further configured to
Golding does not explicitly teach:
execute a smart contract to record data reflecting a loan approved for the user associated with the lending verdict and the at least one lender entity node on the blockchain for future audits.
Scrivastava teaches:
execute a smart contract to record data reflecting a loan approved for the user associated with the lending verdict and the at least one lender entity node on the blockchain for future audits. ((Srivastava) in at least para 0034, para 0047, para 0054, para 0057, para 0074).
Both Golding and Srivastava are directed toward loan processing activities. 48. Srivastava teaches the motivation of smart contract between buyer and seller for verifying the information of the customer and to help prevent the same customer from obtaining a product from the buyer across two or more sellers. It would have been obvious to one having ordinary skill at the time of effective filing the invention to modify Ref. Golding loan process to include a smart contract as taught by Srivastava since Srivastava teaches the motivation of smart contract between buyer and seller for verifying the information of the customer and to help prevent the same customer from obtaining a product from the buyer across two or more sellers.
In reference to Claim 13:
The combination of Golding, Harvey and Scrivastava discloses the limitations of dependent claim 12. Golding further discloses the limitations of dependent claim 13
The steps of method claim 13 corresponds to operations of system claim 3. Therefore, claim 13 has been analyzed and rejected as previously discussed with respect to claim 3
In reference to Claim 14:
The combination of Golding, Harvey, Scrivastava and Suvajac discloses the limitations of dependent claim 13. Golding further discloses the limitations of dependent claim 14
The steps of method claim 14 corresponds to operations of system claim 4. Therefore, claim 14 has been analyzed and rejected as previously discussed with respect to claim 4
In reference to Claim 15:
The combination of Golding, Harvey, Scrivastava and Suvajac discloses the limitations of dependent claim 14. Golding further discloses the limitations of dependent claim 15
The steps of method claim 15 corresponds to operations of system claim 6. Therefore, claim 15 has been analyzed and rejected as previously discussed with respect to claim 6
In reference to Claim 16:
The combination of Golding, Harvey, Scrivastava and Suvajac discloses the limitations of dependent claim 15. Golding further discloses the limitations of dependent claim 16
The steps of method claim 16 corresponds to operations of system claim 7. Therefore, claim 16 has been analyzed and rejected as previously discussed with respect to claim 7
In reference to Claim 18:
The combination of Golding, Harvey, Scrivastava and Suvajac discloses the limitations of independent claim 17. Golding further discloses the limitations of dependent claim 18
The instructions of medium claim 18 corresponds to operations of system claim 8. Therefore, claim 18 has been analyzed and rejected as previously discussed with respect to claim 8
In reference to Claim 20:
The combination of Golding, Harvey, Scrivastava and Suvajac discloses the limitations of dependent claim 18. Golding further discloses the limitations of dependent claim 20
The instructions of medium claim 10 corresponds to operations of system claim 10. Therefore, claim 20 has been analyzed and rejected as previously discussed with respect to claim 10
Claim(s) 9 of claim 1 above, Claim(s) 19 of claim 18 above is/are rejected under 35 U.S.C. 103 as being unpatentable over 52. US Pub No. 2020/0302335 A1 by Golding (Golding) in view of US Patent No. 11,860,852 B1 by Harvey (Harvey) and US Pub No. 2020/0311808 A1 by Srivastava et al. (Srivastava) in view of US Pub No. 2020/0104911 A1 by Suvajac et al (Suvajac) as applied to claim 8 above, and further in view of US Pub No. 2021/0226774 A1 by Padmanabhan (Padmanabhan)
In reference to claim 9:
The combination of Golding, Harvey, Scrivastava and Suvajac discloses the limitations of dependent claim 8. Golding further discloses the limitations of dependent claim 9
The system of claim 8 (see rejection of claim 8 above),
Golding does not explicitly teach:
wherein the processor is further configured to wherein the instructions further cause the processor to retrieve the at least one lending parameter from the blockchain responsive to a consensus among the LS node and the at least one lender entity node.
Padmanabhan teaches:
wherein the processor is further configured to wherein the instructions further cause the processor to retrieve the at least one lending parameter from the blockchain responsive to a consensus among the LS node and the at least one lender entity node. ((Padmanabhan) in at least para 0087, para 0089, para 0093, para 0127, para 0197, para 0243-0244, para 0417, para 0445, para 0475)
Both Golding and Padmanabhan are directed toward applying blockchain 53. technology to record data. Padmanabhan teaches the motivation of applying consensus mechanism in order to verify transactions and maintain security. It would have been obvious to one having ordinary skill at the time of effective filing the invention to modify the blockchain function details of Ref. Golding to include consensus with respect to blockchain of Padmanabhan since Padmanabhan teaches the motivation of applying consensus mechanism in order to verify transactions and maintain security.
In reference to Claim 18:
The combination of Golding, Harvey, Scrivastava and Suvajac discloses the limitations of dependent claim 18. Golding further discloses the limitations of dependent claim 19
The instructions of medium claim 19 corresponds to operations of system claim 9. Therefore, claim 19 has been analyzed and rejected as previously discussed with respect to claim 9
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. US Pub No. 2019/0205977 A1 by Way et al; US Pub No. 2014/0249991 A1 by MacInnis
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MARY M GREGG whose telephone number is (571)270-5050. The examiner can normally be reached M-F 9am-5pm.
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/MARY M GREGG/ Examiner, Art Unit 3695