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 04/13/2026 and Applicant’s communication regarding application 18/965674 filed 04/13/2026.
Claims 1 and 12 have been examined with this office action.
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 and 12 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea of climate-impact analytics for evaluating loans 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 claim 1 and all claims which depend from it are directed toward a system, and independent claim 10 and all claims which depend from it are directed toward a method and independent claim 20 all claims which depend from it are directed toward a computer readable medium storing instruction to perform functions/steps. 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 climate-impact analytics system for evaluating loans and mortgages, comprising: one or more processors and one or more non-transitory computer-readable storage media storing instructions that, when executed by the one or more processors, cause the system to implement: a control object algorithm configured to manage data flow between various system components, the control object algorithm routing property data and environmental data to appropriate processing modules for analysis by dynamically adjusting routing based on property type to engage specialized modules, thereby improving evaluation efficiency for residential, commercial, industrial, or agricultural properties; by dynamically routing property data and environmental data to one or more selected processing modules of the system based on (i) a property-type classification of the property data identifying the property as one of residential, commercial, industrial, or agricultural property, and (ii) a real-time risk threshold value, wherein, in response to the real-time risk threshold value being exceeded, the control object algorithm reroutes the property data to a higher-risk processing module of the system; a sliding window algorithm configured to process continuous streams of time- series data, including ambient thermal data, humidity, rainfall, and wind speed data, the sliding window algorithm reducing computational complexity by optimizing data analysis through transformation of nested loops into a single loop for real-time handling of seasonal variations and prediction of environmental impacts on property values; wherein the sliding window algorithm maintains a fixed-size window of most-recent data points of an incoming time-series by appending a newly-arrived data point to the fixed-size window and discarding an oldest data point from the fixed-size window as the window advances, and processes the continuous streams in a single pass over the incoming time-series that transforms a nested-loop computation into a single-loop computation, thereby reducing computational complexity relative to processing an entire dataset; a smart contract module configured to automate secure data exchange between bank server systems and external data sources, by executing one or more smart contracts that, in response to a defined trigger condition derived from at least one of the property data and the environmental data, automatically retrieve a compliance record from a regulatory database, verify the compliance record against an environmental-law rule set, and emit a compliance-verification message to one or more of the system components; an artificial neural network comprising a multi-layered architecture having one or more convolutional layers configured to process geospatial imagery of the property and analyze land features including topography, vegetation, and proximity to water bodies, the artificial neural network applying a backpropagation approach to improve accuracy of property evaluations over time using historical environmental data; a generative adversarial neural network configured to simulate one or more network configurations of the system and to generate synthetic scenarios that assess resilience of the system and test one or more network defenses of the system; a climate environment information processing module configured to a continuous stream of climate data received from one or more environmental monitoring systems and, in response to a real-time update from the one or more environmental monitoring systems, continuously reassess a property-condition evaluation using most-recent climate data within the fixed-size window of the sliding window algorithm; an urban/rural processing module configured to assess population density, economic activity, and land use patterns for the property and to adjust the property evaluation based on an urbanization or rurality factor derived from infrastructure-development trend data of a surrounding area; a township processing module configured to retrieve a property registration record from a government database and to verify the property registration record against a blockchain-based land registry record to provide tamper- proof verification of property boundaries and ownership history; a secure messaging protocol, using a MQTT protocol with a quantum-resistant encryption algorithm, configured to transmit data between a bank server, the smart contract module, and one or more machine learning modules of the system, the secure messaging protocol securing the transmitted data against cryptography- breaking threats; a secure access service edge (SASE) configured to monitor and control access to the system, the secure access service edge enforcing access permissions and applying a micro-segmentation policy that isolates the system into a plurality of network segments to protect property-related data; a spine-leaf network topology configured to interconnect the machine learning modules, the smart contract module, and one or more property databases via a plurality of leaf switches and a plurality of spine switches, each of the plurality of leaf switches being connected to each of the plurality of spine switches, the spine-leaf network topology providing concurrent forwarding paths along which concurrent property evaluations for a plurality of properties are forwarded and minimizing latency during property evaluation; and a digital end-to-end transaction system configured to process and store data records related to property evaluations from initial data input through a final loan-or-mortgage decision output of the system, the digital end-to-end transaction system configured to write each data record to the one or more property databases under control of the smart contract module”.
Claim 12 comprises inter alia the functions or steps of “A climate-impact analytics method for evaluating loans and mortgages performed by a climate-impact analytics system comprising one or more processors and one or more non-transitory computer-readable storage media storing instructions executable by the one or more processors, comprising: dynamically routing, by a control object algorithm executed by the one or more processors, property data and environmental data to one or more selected processing modules of the system based on a property-type classification, including residential, commercial, industrial, and agricultural classifications, and based on a real-time risk threshold value, wherein, in response to the real-time risk threshold value being exceeded, the control object algorithm reroutes the property data to a higher-risk processing module of the system; processing, by a sliding window algorithm executed by the one or more processors, continuous streams of time- series data including ambient thermal data, humidity, rainfall, and wind speed data, the processing comprising maintaining a fixed-size window of most-recent data points of an incoming time-series by appending a newly-arrived data point and discarding an oldest data point as the window advances, and processing the continuous streams in a single pass over the incoming time-series that transforms a nested-loop computation into a single-loop computation, thereby reducing computational complexity relative to processing an entire dataset; executing, by a smart contract module, one or more smart contracts that, in response to a defined trigger condition derived from at least one of the property data and the environmental data, automatically retrieve a compliance record from an external regulatory database, verify the compliance record against a building-code rule set and an environmental-law rule set, and emit a compliance-verification message to one or more of the system components; analyzing, by an artificial neural network having a multi-layered architecture with one or more convolutional layers, geospatial imagery of the property to analyze land features including topography, vegetation, and proximity to water bodies, and updating weights of the artificial neural network using a backpropagation approach on historical environmental data; simulating, by a generative adversarial neural network, one or more network configurations of the system and generating synthetic scenarios that assess resilience of the system and test one or more network defenses of the system; applying, by a climate environment information processing module, the sliding window algorithm to a continuous stream of climate data received from one or more environmental monitoring systems, and, in response to a real-time update from the one or more environmental monitoring systems, continuously reassessing a property-condition evaluation using most-recent climate data within the fixed-size window of the sliding window algorithm; assessing, by an urban/rural processing module, population density, economic activity, and land use patterns for the property, and adjusting the property evaluation based on an urbanization or rurality factor derived from infrastructure-development trend data of a surrounding area; transmitting, by a secure messaging protocol using a MQTT protocol with a quantum-resistant encryption algorithm, data between a bank server, the smart contract module, and one or more machine learning modules, the secure messaging protocol securing the transmitted data against cryptography-breaking threats; enforcing, by a secure access service edge (SASE), access permissions across the system and applying a micro-segmentation policy that isolates the system into a plurality of network segments to protect property-related data; forwarding, via a spine-leaf network topology comprising a plurality of leaf switches and a plurality of spine switches, each of the plurality of leaf switches being connected to each of the plurality of spine switches, concurrent property evaluations for a plurality of properties along concurrent forwarding paths of the plurality of leaf switches and the plurality of spine switches, and minimizing latency during property evaluation; and writing, by a digital end-to-end transaction system, each of a plurality of data records related to property evaluations to one or more property databases under control of the smart contract module, from initial data input through a final loan-or-mortgage decision output”.
Those claim limits in bold are identified as claim limitations which recite 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. Climate-impact analytics for evaluating loans 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 smart contract module configured to automate secure data exchange between financial institution systems and external data sources; an artificial neural network; a generative adversarial neural network; a climate environment information processing module; an urban/rural processing module; a township processing module; a secure messaging protocol, using a MQTT protocol, configured to transmit data between a bank server, the smart contract module, and machine learning modules, the secure messaging protocol ensuring secure and efficient communication during a property evaluation process; a secure access service edge (SASE); a spine-leaf network topology configured to connect the system components, including machine learning modules, smart contracts, and property databases, the spine-leaf network topology providing scalable, high-speed data transfers and minimizing latency during the property evaluation process; a digital end-to-end transaction system; real-time/ without manual intervention / dynamically; a multi-layered architecture with convolutional layers; blockchain-based systems. However, the specification description of the additional elements system ([0057] [0078-0082]); a smart contract module configured to automate secure data exchange between financial institution systems and external data sources ([0034] [0045] [0159]); an artificial neural network ([Figure 6] [0067] [0100] [0121] [0135] [0160] [0192]); a generative adversarial neural network ([0022] [0032] [0034] [0040] [0046] [0053] [0068]); a climate environment information processing module ([0023] [0034] [0041] [0047] [0054] [0063] [0094] [0121] [0135] [0150] [0162]); an urban/rural processing module ([0024] [0034] [0042] [0047] [0055] [0070] [0106] [0122] [0136] [0151] [0163]); a township processing module ([0025] [0035] [0043] [0048] [0056] [0071] [0107] [0123] [0136] [0152] [0164]); a secure messaging protocol, using a MQTT protocol, configured to transmit data between a bank server, the smart contract module, and machine learning modules, the secure messaging protocol ensuring secure and efficient communication during a property evaluation process ([0026] [0035] [0048] [0072] [0087] [0108] [0120] [0133] [0148] [0165]); a secure access service edge (SASE) ([0027] [0035] [0048] [0073] [0085] [0118] [0120] [0131] [0146]); a spine-leaf network topology configured to connect the system components, including machine learning modules, smart contracts, and property databases, the spine-leaf network topology providing scalable, high-speed data transfers and minimizing latency during the property evaluation process ([0035] [0048] [0074] [0109] [0124]); a digital end-to-end transaction system ([0035] [0048] [0115] [0125] [0138] [0158]) [0166]); real-time/ without manual intervention / dynamically ([0078] interpreted as a software executing on a general-purpose or specialized for specific tasks); a multi-layered architecture with convolutional layers ([0039]); blockchain-based systems ([0043] [0048] [0056] [0071] [0107] [0115]) [0152]); 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.
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 are read in the particular environment of the claims. Multiple Cella applications are cited by the applicant. However, none of the applications cited by the applicant or which are found by the examiner’s prior art search are directed toward performing data-driven decision-making tasks related to loan and mortgage evaluations. Additionally, Li (US Patent No. 12197302) teaches sliding window algorithm refers to an algorithm which performs a required operation on an array or a string with a given specific window size. This technology can transform a nested loop in some problems into a single loop, and thus can reduce the time complexity. 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: Applicant's arguments with regards to 35 USC § 101 have been fully considered but are not persuasive. With regard to applicant's argument directed toward Examples 47 and 40, the application in the Examples 47 and 40 made an improvement to an underlying technology, whereas, the present application used a generic technology and computer to implement an abstract idea. Thus, Examples 47 and 40 are readily distinguishable from the present claims. Regarding the claim limitation “wherein the sliding window algorithm maintains a fixed-size window of most-recent data points of an incoming time-series by appending a newly-arrived data point to the fixed-size window and discarding an oldest data point from the fixed-size window as the window advances, and processes the continuous streams in a single pass over the incoming time-series that transforms a nested-loop computation into a single-loop computation, thereby reducing computational complexity relative to processing an entire dataset”, paragraph [0020] states:
To further enhance the processing capabilities, the invention employs a Sliding Window Algorithm (SWA). This algorithm is designed to handle time-series data, such as continuous streams of climate information, in a highly efficient manner. The SWA reduces computational complexity by transforming nested loops into a single loop, significantly improving processing speeds. This optimization is particularly important when dealing with large datasets or real-time data, where traditional methods might struggle to keep up with the volume and speed of information. By utilizing the SWA, the system can process real-time environmental data such as temp, humidity, wind speed, and rainfall, all of which are factors in assessing the potential future value of a property.
Thus, it is the utilization of a Sliding Window Algorithm (SWA) which results in the benefits of reducing computational complexity by transforming nested loops into a single loop, significantly improving processing speeds. There is no detailed description of how the nested loops into a single loop is performed to reduce computational complexity. Further, the Sliding Window Algorithm appears to be a selected list (window) of the most recent environmental data points (Specification [0216]) which appears to be an abstract idea and not a technical solution to a problem. As such, the examiner maintains the rejection.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Li (US Patent No. 12197302) teaches Sliding window: sliding window algorithm refers to an algorithm which performs a required operation on an array or a string with a given specific window size. This technology can transform a nested loop in some problems into a single loop, and thus can reduce the time complexity.
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
09/07/2026
