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 March 16, 2026. No Claim(s) have been canceled. Claims 1, 6-7, 10, 15-16 and 19-20 have been amended. No new claims have been added. Therefore, claim(s) 1-20 are pending and addressed below.
Priority
Application No. 18470555 filed 09/20/2023 Claims Priority from Provisional Application 63525191 , filed 07/06/2023.
Assignee/Applicant: Oracle International Corporation
Inventors: Agrawal, Vikas; Ramanathan, Krishnan; Shishtla, Praneeth Medhatithi; Jagdish Chand.
Response to Amendment/Arguments
Claim Rejections - 35 USC $ 101
Applicant's arguments filed 03/16/2026 have been fully considered but they are not persuasive.
In the remarks applicant argues the claimed subject matter under step 2A prong 1 cannot reasonably be performed using mental concepts. Applicant’s argument is persuasive. The examiner withdraws the 101 rejection under step 2A prong 1 for being directed toward the abstract category. However, the rejection under step 2A prong 1 is maintained for being directed toward mathematical concepts and methods of organizing human activity.
In the remarks applicant argues the claimed subject matter is directed toward a technical solution. Applicant points to the specification ¶ 0038 and Ex parte Desjardins as it relates to machine learning and patent eligible improvement to technology. Applicant argues that similar to Desjardins, the current application use of two different ML models that are trained and tested using historical data to create a regular ML model and creating two or more grace period ML models using historical data with the grace period for training and testing. Applicant argues that the claims reflect improvement in accuracy of variable predictions as compared to known solutions improving accuracy of predictions of ML models which is the improvement to ML model technology. Applicant’s argument is not persuasive.
The specification discloses the grace period as part of the A/C process related to a delay in payments beyond due dates, by analyzing human behavior on late payments to determine a grace period to prevent payment default. Accordingly the specification does not support applicant’s argument that the claimed subject matter is truly drawn to ML model technology itself, but rather the use of ML model technology to by analyzing human behavior on late payments to determine a grace period to prevent payment default, by analyzing different grace period and payment history in order to predict a grace period for late payments of the user.
[0015]… Embodiments further select among the multiple models for each customer by incorporating a grace period into historical AR (account receivable) delays. Embodiments further determine a customer reliability score for each customer.
[0038] Further, if the model algorithms are run by including a grace period, such as median of delays in all invoices (or other percentiles of delays), beyond the payment due date as indicative of a population-wide late payment disposition, then the percentage of defaults over the whole population will go down. A "grace period" model is trained with invoices considered delayed only if the payment was delayed beyond the payment due date and an additional number of days of grace period applied. However, the predictability of payments for the remaining invoices will be worse due to an increased coefficient of variation (i.e., Standard Deviation /Mean). Problems include: (1) how to account for such increased variability and lack of predictability in the models?; (2) how are the customers informed about the lack of predictability in the models so that models can be changed for positive business outcomes; should features be changed?; (3) How do useful predictions get generated? Further, problems include how to ensure that in the models a customer does not automatically look "better" when paying lots of small invoices paid and leaving a few large invoices unpaid? In contrast to known solutions, embodiments in general solve the above problems.
[0041] …cases of extreme class imbalance that is different from what is normally expected, such as 90%
of customers defaulting when the normal rate for default is 5-10% for a typical cash flow, embodiments provide a grace period internally (representing de facto due dates) for modeling purposes to bring down the default rate to what is considered normal for sustainable businesses (e.g., <10%) or choose a grace period based on a median or percentile of delay for a customer or for an industry where such data is obtainable. For example, the grace period may vary depending on the industry that the customer belongs to. For example, for the hospitality or manufacturing industry, the typical payment delay may be 60 days. In this instance, the grace period may be 60 days, and while a payment is actually delayed based on days passed since the payment due date, in fact the company is running their business with such delays across many or most of their customers such that it might have become entrenched as part of their status quo
business process.
[0042] However, the result may be that a customer may be defaulting (i.e., either paying late or not paying at all) even after applying a de facto grace period, but these are also likely to be the most unpredictable customers. Therefore, at 502, for all distributions of class imbalance, in embodiments three (or more) separate groups or segments of customers are created based on their variance of invoice delays using measures such as coefficient of variation, and separate predictive models are generated for each segment or group…
[0043]… The target variable is the AR delay that the model or models is trained to predict, such as the number of days of delay of payment after receipt of the invoice. In embodiments with a grace period, the number of days of delay is determined to be the number of days the payment is delayed after the grace period is added to the payment due date….
[0050]… Creating or generating an ML model in embodiments includes selecting a model algorithm (e.g., a neural network algorithm, a random forest algorithm, etc.),training the algorithm to create a trained ML model, and then testing and validating the trained ML model. The model at 504 is trained/tested/ validated using the training data at 501, and no grace period is used in predicting a delay, resulting in model 510. For customers with distributions of delays such that there is a low mCoV in delays, the customer is considered to have a low variability in delays, which corresponds to their making payments on time or with delays, on a regular basis. The resulting model 510 will generally be a high precision and high recall model because the delays in their invoice payments are in a narrow distribution, and thus more predictable than cases of high variability in the distribution of delays.
[0051] Based on the segmentation, at 506, for the customers with distributions of delays such that there is a medium range MCoV, then a plurality of models is generated. In one embodiment, three models are generated, but more models such as 4, 5 or 6 can be used, with different levels of grace period applied, such as 25th percentile of delay, median of delay, 75th percentile of delay, 90th percentile of delay,
95th percentile of delay etc. This corresponds to a somewhat predictable customer with intermittent payments, and there is a need for a model to predict and find which customers need to be followed up on, with any resulting model having a relatively acceptable precision and recall.
[0052] Of the plurality of models generated at 506, one of the models is the regular model 510. A second model is a model where an invoice payment is considered delayed or defaulted only if it is delayed beyond the payment due date plus the median delay (i.e., grace period) in model 516, such that the number of delayed invoices will be significantly lower than with model 510,… third model can be a model with invoices considered delayed only if their payment is delayed beyond the payment due date plus the goth percentile of delays (which is the grace period for this case). Additional models can be created with different levels of grace period applied, such as 25th percentile of delay, median of delay, 75th percentile of delay, goth percentile of delay, g5th percentile of delay, etc. Here, an invoice payment is considered delayed only if it is delayed beyond the payment due date plus the median delay (called grace period) or higher percentiles of delay, and therefore as higher percentiles are chosen as the grace period, the number of delayed invoices is reduced. This is particularly useful when a customer has, for example, go% of invoices considered delayed, without a de facto grace period being applied as above. Embodiments are able to correct the unnatural class imbalance where most invoices are showing up as delayed, whereas the usual sustainable business scenario tends to be where less than 10% invoice payments are delayed.
[0056] At 512, the MCC is determined for the model without a grace period 510. If the MCC score is low (e.g., MCC < 0.25 -.3), the MCC is then determined for both the grace period models 516, 518 (or others if more than 2 were created). If at 514, it is determined that the MCC for grace period models 516, 518 has improved to above a minimum threshold for deployment (e.g., 0.3-0.5) in comparison to the MCC at 514 then the model can be deployed, as this indicates a consistent business practice (i.e., a de facto grace period) at the customer….
[0057] If the MCC score for model 510 and/or the improved MCC for grace period models 516, 518 at 514 is high (e.g., MCC > 0.6), then at 524 the corresponding trained model 510 without a grace period or one of grace period based models 516, 518 is deployed at 522 and used for predicting AR payment delays for the customer. The grace period model with the highest MCC is chosen for deployment.
[0058] If at 520, it is determined that the MCC for grace period models 516, 518 has become worse in comparison to the MCC at 512, then at 530 the MCC is considered too low for deployment, and all the models are rejected at 540 because no model will provide accurate predictions of AR payment delays based on the training data, given the ML algorithms available and chosen for the models…
In the remarks applicant points to BASCOM, arguing the claimed subject matter’s arrangement of ML models is non-generic and unconventional. The arrangement of more than one model including a “regular” ML model for low variation customer and more “grace period” ML models for variation customers. Applicant’s argument is not persuasive. BASCOM found patent eligibility with the arrangement of generic computer operations which provided a solution to a problem rooted in technology. This is not the case of the current limitations, as the combination of models is not to improve upon or solve a problem rooted in ML model technology, but instead to create models for analyzing human behavior in order to predict for accounts receivable delay of payment periods in order to predict “grace periods” for different customers according to their payment history. Applicant’s argument is not persuasive.
In the remarks applicant points to the USPTO 2025 memo, including examples 39 and 47. Applicant argues that similar to the examples the current claims recite trained models using historical data where the trained models have different grace period parameters for target variables. This model process improves the technical field of ML models and go beyond mere “applying” of the models for implementing any alleged abstract idea. The analysis of a customer requires transactional data where the data is stored within a data warehouse and includes dimensional generation, fact generation and aggregate generation, pointing to the specification para 0079 and 0086. The recitation in the claims including “data plane” and “control plane” are process that are not merely the application of mathematical concepts. The examiner respectfully disagrees. As discussed above, the “grace periods” are merely parameters set within the model for use in analyzing user behavior to predict payment delays to prevent late/default payments in paying invoices. Similar to example 47, claim 2, the limitations training process is high level and as recited can be performed as a generic computer performing generic computer functions. The limitations and specification do not provide any details as to how the training operations, instead focusing on the data acted upon and the output desired in the analysis of human behavior. The specification describes the control plane as software to provide control for cloud/software products offered within SaaS/cloud environments such as off the shelf Oracle Analytics Clouse environment (para 0074). The specification describes the “data plane” as altering/updating frequency of extraction, loading and transforming data edited in the data warehouse, where the software includes a process layer, transformation layer that form the software used to extract data from business applications for use in the data analysis. The control plane and data plane (layered software) are not directed toward a process to improve any of the underlying technology or the models applied to analyze “grace periods” of a business process. The rejection is maintained.
In the remarks applicant argues the additional elements recited in independent claims 6, 15 and 20 claims are unconventional and therefore, patent eligible. Applicant’s response is not persuasive. Applicant has not explained what additional elements or technological technique are unconventional and why. The additional elements beyond the abstract idea of method claim 1 includes a cloud based analytics systems with a control plane, transformation layer and data plane, performing the operations selecting customers, receiving data, extracting data, transforming data into a warehouse format, loading data, determining a costs of a delayed payment, determining average delay of payment, converting cost of delayed payment to a z-score and average delay of payments to second z-score, determining reliability score (Euclidean distance of the first z-score and scone z-score) and displaying results. . The control plane, data plane and transformation layer is merely software per se, amounting to no more than mere instructions to perform insignificant extra solution activity of receiving, extracting, loading and displaying data (MPEP 2106.05(d) II (see also MPEP 2106.05(g)). The software additional provides instructions directed toward data analysis (determining a cost, determining delays, and performing calculations (converting payments to z-scores and determining Euclidean distance). The converting operations is mere data manipulation MPEP § 2106.05(g) & (h). When considered as a combination, similar to Electric Power Group, applying technology to collect data, analyze data and output the result is well understood application of technology. With respect to the selecting step of the amended limitations, the limitation recites “receiving a plurality of trained ML models” , “determining a MCC for the first model”, “determining the MCC for each of the models”, when the first model of the plurality of models MCC is at a criteria, “determining the MCC for each of the plurality of models”, and when the MCC for each of the plurality of models is lower than the MCC of the first model, “not deploying the first model” to predict the target variable and assigning the first customer as the selected customer. The “trained models” do not perform any of the operations of the amended limitations. The steps “receiving”, “determining” and “not deploying” are not operations of the models but instead broad enough to be implemented manually or by the system. Furthermore, similar to the operations discussed above, the ordered combination of the limitations, similar to Electric Power Group recite conventional application of technology of “receiving”, “determining” (analyzing) and “deploying” (outputting the result). The focus of the combination of operations/steps is not the system technology itself or ML models but rather to perform the identified abstract idea. The rejection is maintained.
Claim Interpretation
The examiner is interpreting a Z-score by its ordinary meaning in the art a z-score or standard score of a statistical measure that describes a position of a raw score in terms of distance from the mean, measured in standard deviation where a positive z-score indicates a value above a mean and a negative z-score indicates a value below the mean.
Euclidean distance: In mathematics, the Euclidean distance between two points in Euclidean space is the length of the line segment between them. It can be calculated from the Cartesian coordinates of the points using the Pythagorean theorem, and therefore is occasionally called the Pythagorean distance.
The examiner is interpreting the term “data staging area” to be temporary/intermediate storage for data (see specification para 0083, para 0105; FIG. 8 ref # 124).
Data transformation layer- the examiner is giving the computer element its ordinary meaning in the art - A data transformation layer is a component of a data stack. It enables a business to automate the validation and cleansing of data before it is used downstream. The term “data transformation” when considered in light of the application of the data transformation layer is interpreted as - Data transformation involving the conversion, cleaning, and organizing of data into accessible formats.
Data plane- the examiner in light of the specification the examiner is interpreting the data plane to be a user interface (see para 0079-0080, para 0100) which performs API operations (e.g. data extraction, communication)
The Matthews Coefficient is a formula incorporated in the models trained.
[0054]… For the evaluation of models, embodiments use the Matthews' Correlation
Coefficient ("MCC"), which can measure of the quality of binary (two-class)
classifications, such as, for example, whether a customer will pay accounts receivable
in time or not. MCC can be calculated as follows:
PNG
media_image1.png
88
598
media_image1.png
Greyscale
where TP is the number of true positives, TN the number of true negatives, FP the
number of false positives and FN the number of false negatives. If any of the four sums
in the denominator is zero, the denominator can be arbitrarily set to one, which results
in a Matthews correlation coefficient of zero, which can be shown to be the correct
limiting value. The MCC determination is close to 1 for perfect correct classification,
close to -1 for incorrect classification, and close to 0 for random classification. In
embodiments, the MCC determinations use the test/validation data 307 split from the
training data 304.
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 1-9:
STEP 1. Per Step 1 of the two-step analysis, the claims are determined to include a method, as in independent Claim 1 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 claimed invention is directed to an abstract idea without significantly more. Method claim 1 recites a method steps (1) selecting a customer (2) receiving data (3) extracting historical data to a data staging area (4) transforming historical data into a data warehouse format (5) loading the transformed historical data into a data warehouse (6) determining cost of a delayed payment (7) determining average delay of payments (8) converting cost of delayed payment to a first z-score and average delay of payments to second z-score (9) determining reliability score comprising Euclidean distance of first Z-score and second Z-score (10) displaying score.
The claimed limitations which under its broadest reasonable interpretation, covers performance of mathematical concepts. The limitations when considered as a whole the claimed subject matter is directed toward the calculation of a reliability score. The wherein clause further limits the selecting customer step by receiving a plurality of models, which is not a process that can reasonably be performed using mental processes. The additional limitation to the selecting step include “determining a Matthews’ Correlation Coefficient for the first model”, “determining the MCC for each …trained model” and based on a condition “deploying the first trained model”. The wherein clause therefore recites the abstract concept of a mathematical concept.(spec ¶ 0054).
Furthermore, the specification makes clear that the focus of the invention is to receive customer historical data corresponding to transactions with an organization and targeting a variable including number of days of delayed payment for each transaction and the average delay of payment of the customer. (para 0006). The specification discloses that “reliability score” is calculated to measure variations of customers by distribution of delays in payment for each customer by incorporating grace periods for each customer (para 0015) where the determination of the customer reliability score is a result of analyzing customers based on accounts receivable (para 0061) and how much such delays cost companies when compared to their peers (para 0062). The specification makes clear that the purpose of the reliability score. Such concepts can be found in the abstract category of risk mitigation and sales activities/behaviors. The claim limitations do not focus on the technology for data formatting but instead focuses on the calculation of the score which is a mathematical concept. As discussed above, the specification that the purpose of the analysis and the calculation of the score is to analyze and measure human behavior as it related to cost which is a process directed toward commercial activity, a sub-category of the abstract category of methods of organizing human activity. 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 mathematical concepts and methods of organizing human activity.
STEP 2A Prong 2: The additional elements recited in the claim beyond the abstract idea include a cloud based system comprising a data plane, transformation layer and control panel. The “transformation layer” is software per se and amounts to no more than mere instructions to apply the abstract idea.
The “data plane” applied to perform the operations of “extract …data”, “loading …data”, and “control plane” applied to perform the “displaying …score of the customer”, which according to MPEP 2106.05(d) II (see also MPEP 2106.05(g)) 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)
Electronically scanning or extracting data from a physical document, Content Extraction and Transmission, LLC v. Wells Fargo Bank, 776 F.3d 1343, 1348, 113 USPQ2d 1354, 1358 (Fed. Cir. 2014) (optical character recognition)
The functions “extracting” and “loading” are recited at a high level of generality without details of technical implementation and thus are insignificant extra solution activity.
The additional element “data plane” applied at a high level to perform the operations “transforming …into data warehouse format” without technical details merely provides instructions (transformation layers) to perform a process which have been found to be insufficient to overcome abstract subject matter - as the focus of the limitation is not the transforming process but rather the expected outcome of formatting data for warehouse format, which is mere data manipulation. 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). Whether the transformation is extra-solution activity or a field-of-use (/.e., the extent to which (or how) the transformation imposes meaningful limits on the execution of the claimed method steps). A transformation that contributes only nominally or insignificantly to the execution of the claimed method (e.g., in a data gathering step or in a field-of-use limitation) would not provide significantly more (or integrate a judicial exception into a practical application). Mayo, 566 U.S. at 76, 101 USPQ2d at 1967. The Supreme Court disagreed, finding that this step was only a field-of-use limitation and did not provide significantly more than the judicial exception. /d. See MPEP § 2106.05(g) & (h).
The additional element “data plane” applied at a high level of generality for performing the data analysis process for performing the abstract idea of “determining a cost”, “determining average delay of payments” and mathematical calculations of “converting cost of delayed payments to a first Z-score and the average delay of payment to a second Z-score” and “determining a reliability score of the customer… determining…Euclidean distance of the first Z-score and second Z-score”. The specification discloses that the purpose of the calculation of the reliability score is for use by the vender to access the risk of a particular customer for customer reliability.
The additional element “cloud based analytics system, merely provides a field of use for performing the identified abstract idea.
The wherein clause does not further limit the system. The wherein clause does not tie the receiving of the model to the selection of the customer, instead the wherein clause limits the models received as part of the selecting customer step. The models received do not perform any of the method steps and are not incorporated in the method process beyond being deployed based on a determined criteria.
When the claims are taken as a whole, as an ordered combination, the combination of limitations 1-5 are directed toward collecting, organizing and manipulating data for loading (inputting) into storage for use in analysis for a business practice. The combination of limitations 6- 9 is to perform a mathematical process using the data collected, organized, manipulated and loaded/inputted in limitations 1-5. The combinations of parts is not directed toward any technical process or technological technique or technological solution to a problem rooted in technology.
In addition, when the claims are taken as a whole, as an ordered combination, 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 when considered as a whole is directed toward collecting, organizing and manipulating data that is loaded into a system for analysis where the analysis is a mathematical process for determining a reliability score and outputting the results. The nominal mention of a “cloud based analytics system” which is a field of use environment and “transformation layer” applied to transform data, fails to provide sufficient additional elements or combination or elements to apply or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception. The functions recited in the claims recite the concept of receiving customer data, manipulating and loading collected data merely provides the variables for use in the mathematical process of determining cost of payment delay, determining average delay of payment, converting data into z-values which are applied to calculate a reliability score, which as a combination of parts or as a whole are a process directed toward any of the underlying technology which provides indication of patent eligibility but instead directed toward analyzing and scoring customer risk and mathematical concepts.
Because the claim limitations lack technical disclosure and merely mentions the environment where the method is performed (cloud based analytics system) and the tool (transformation layer) applied to “transform data” without technical details of implementation there is no integration of elements for improving upon technology or improve upon computer functionality or capability in how computers carry out one of their basic functions. This also applies to the “dimensional generation” and “aggregate generation” which in light of the specification has been interpreted as data manipulation and organization without details of technical implementation and so high level as to be implemented by any known means. There is no 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 instant application, therefore, still appears only to implement the abstract idea in a broadly claimed field of use environment for calculating values related to a business practice and mathematical concepts. The steps are still a combination made to perform a mathematical process to calculate a value measuring a business metric and does not provide any of the determined indications of patent eligibility set forth in the 2019 USPTO 101 guidance. The functions are is recited at a high-level of generality without any additional elements beyond the identified abstract idea. The claim limitations lacks technical disclosure and therefore fail to provide any indication of patent eligible subject matter under step 2A prong 2. Taking the claim elements separately, the operation performed by the method at each step of the process is purely in terms of results desired and devoid of technical implementation of the claimed process. Technology is not integral to the process as the claimed subject matter fails to mention any technology. 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 additional elements 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, which, when considered in the ordered combination with the other steps, could have transformed the nature of the abstract idea previously identified. 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 beyond the identified abstract idea include a cloud based analytics system comprising a data plane for analyzing customer data and a transformation layer for transforming data, determining reliability score of a customer for use in determining customer reliability and a “control panel” to display data. The claimed “cloud based analytics system” is nominally mentioned in the preamble whose “data plane” is for use in performing the high level limitations in the body of the claim. Accordingly the “cloud-based analytics system” is merely a field of use recitation (MPEP 2106.05 (h)). Therefore, the “cloud-based analytics system” fails to impose meaningful limits upon the identified conceptual idea discussed above. With respect to the application of the “transformation layer” to perform the step “transforming data” the claim limitation and specification lacks technical details on how the transformation layer performs the step and thus is broad enough to encompass the transformation layer transforming data in its ordinary capacity as such technology was designed to operation. Application of such transformation layer software is known in the art for use in formatting data -WO 2020/039198 A1 by Barnett-“connect to one or more external databases or APIs and extract data of relevance to the model. These APIs or data sources could be open source or freely available and not in a data format which is readily usable by the model. Therefore, once extracted in raw format or in a format specific to the remote system, the data is transformed in to data structures compatible with the connected graph model representation via a data transformation layer. Once transformed, data is loaded into the model directly via an optional data service layer 17.” (FIG. 3); WO 2010/006187 A2 by Rajaraman et al – “The data transformation layer 204 may include code that forms the outlet for custom or platform-specific data manipulation and formatting. This layer 204 may be used for data in both inbound and outbound message Queues.”…(FIG. 2); US Pub No. 2022/0301031 A1 by Iyer-“ the data processing engine 202 instantiates a data transformation layer that maps and transforms data received from a source. For example, the data transformation layer transforms non-XML data format (e.g., of a data source 135) to XML data format for storage. In some implementations, the data processing engine 202 processes, correlates, integrates, and synchronizes the received data streams from disparate devices 115, servers 120, 140, and data sources 135 into a consolidated data stream to perform the functionalities as described herein:”. Using a data transformation layer to transform data----is the most basic functions of such software.
The received trained models do not perform any of the recited step of the method and therefore, do not provide any unconventional technological process or components to the system.
The specification describes the transformation layer in the light of its application in enterprise software with high level functions and expected outcomes…lacking technical disclosure with respect to technical implementation or for a particular transformation data process-
[0078] In accordance with an embodiment, the data plane can include a data pipeline or process layer 120 and a data transformation layer 134, that together process operational or transactional data from an organization's enterprise software application or data environment, such as, for example, business productivity software applications provisioned in a customer's (tenant's) Saas environment. The data pipeline or process can include various functionality that extracts transactional data from business applications and databases that are provisioned in the Saas environment, and then load a transformed data into the data warehouse.
[0079] In accordance with an embodiment, the data transformation layer can include a data model, such as, for example, a knowledge model ("KM"), or other type of data model, that the system uses to transform the transactional data received from business applications and corresponding transactional databases provisioned in the Saas environment, into a model format understood by the data analytics environment. The model format can be provided in any data format suited for storage in a data warehouse. In accordance with an embodiment, the data plane can also include a data and configuration user interface, and mapping and configuration database
[0084] In accordance with an embodiment, when the extract process has completed its extraction, the data transformation layer can be used to begin the transform process, to transform the extracted data into a model format to be loaded into the customer schema of the data warehouse.
[0086] In accordance with an embodiment, the data transformation layer can transform extracted data into a format suitable for loading into a customer schema of data warehouse, for example according to the data model. During the transformation, the data transformation can perform dimension generation, fact generation, and aggregate generation, as appropriate. Dimension generation can include generating dimensions or fields for loading into the data warehouse instance.
[0118]… When the extract process has completed its extraction, the data transformation layer can be
used to begin the transformation process, to transform the extracted data into a model format to be loaded into the customer schema of the data warehouse.
[00125]… When the extract process 108A, 108B for a particular customer has completed its extraction,
the data transformation layer can be used to begin the transformation process, to transform the extracted data into a model format to be loaded into the customer schema of the data warehouse.
The “loading” limitations merely inputs data into a data warehouse at a high level of generality using well-understood database technology performing ordinary database operations. The specification discloses:
[0025] In one embodiment, memory 14 stores software modules that provide functionality when executed by processor 22. The modules include an operating system 15 that provides operating system functionality for system 10. The modules further include an ML AR prediction model module 16 that generates and/or selects one or more ML models for predictions of AR delays, and all other functionality disclosed herein. System 10 can be part of a larger system. Therefore, system 10 can include one or more additional functional modules 18, such as the generated ML models, or a business intelligence or data warehouse application (e.g., "Fusion Analytics Warehouse" from Oracle Corp.) that utilizes the generated ML models. A file storage device or database 17 is coupled to bus 12 to provide centralized storage for modules 16 and 18, including training data used to generate the ML models. In one embodiment, database 17 is a relational database management system ("RDBMS") that can use Structured Query Language ("SOL") to manage the stored data.
[0070] In one embodiment, embodiments of the invention are implemented as part of a cloud based data analytics environment. In general, data analytics enables the computer-based examination or analysis of large amounts of data, in order to derive conclusions or other information from that data; while business intelligence tools provide an organization's business users with information describing their enterprise data in a format that enables those business users to make strategic business decisions.
[0071] Examples of data analytics environments and business intelligence tools/servers include Oracle Business Intelligence Server ("OBIS"), Oracle Analytics Cloud ("OAC"), and Fusion Analytics Warehouse ("FAW"), which support features such as data mining or analytics, and analytic applications.
[0072] Fig. 7 illustrates an example data analytics environment, in accordance with an embodiment. The example embodiment illustrated in Fig. 7 is provided for purposes of illustrating an example of a data analytics environment in association with which various embodiments described herein can be used. In accordance with other embodiments and examples, the approach described herein can be used with other types of data analytics, database, or data warehouse environments. The components and processes illustrated in Fig. 7, and as further described herein with regard to various other embodiments, can be provided as software or program code executable by, for example, a cloud computing system, or other suitably-programmed computer system.
[00120] For example, in accordance with an embodiment, a list of view objects for extractions can be submitted, for example, to an Oracle Bl Cloud Connector ("BICC") component via a ReST call. The extracted files can be uploaded to an object storage component, such as, for example, an Oracle Storage Service ("OSS") component, for storage of the data. The transformation process takes the data files from object storage component (e.g., OSS), and applies a business logic while loading them to a target data warehouse, e.g., an ADW database, which is internal to the data pipeline or process, and is not exposed to the customer (tenant). A load/publish service or process takes the data from the, e.g., ADW database or warehouse, and publishes it to a data warehouse instance that is accessible to the customer (tenant).
Taking the claim elements separately, the steps performed by the method at each step of the process is purely conventional. Accordingly the “cloud based analytics system” as referenced in the claim is not enough to qualify as “significantly more” include “apply it” (or an equivalent) with an abstract idea. As a result, none of the hardware 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. 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. … and therefore amounts to no more than mere instructions to apply an exception using a generic computer component which 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 recited steps performed at a high level 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 “selecting…customer”, “receiving …data”, “extracting …data”, “transforming…data into a…format”, “loading…data”, “determining …cost”, “determining …average…payments”, “converting …cost to a …first z-score and average payment to a …second z-score”, “determining reliability score…determining Euclidean distance…”, “displaying …score” ... 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-transmission is equally generic and conventional. See Ultramercial, Inc. v. Hulu, LLC, 772 F.3d 709, 715 (Fed. Cir. 2014) (sequence of receiving, selecting, offering for exchange, display, allowing access, and receiving payment 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.
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 2-9 these dependent claim have also been reviewed with the same analysis as independent claim 1. Dependent claim 2 is directed toward establishing values for performing a calculation (cost of delayed payment comprises penalty based on sum of number of days delayed times weighed cost) and recording usage over time -mathematical concepts and amount of storage space for use (insignificant extra solution activity. Dependent claim 3, 4 and 5 are directed toward a mathematical formula and calculation using specific variables- mathematical concept. Dependent claim 6 is directed toward further limiting the system of method claim 1 to comprising software components and providing access to data warehouse- well understood computer architecture prevalent in the art and limiting the data plane (software) to comprise data pipeline or process that maintains data analytics schema for each customer (e.g. data management), limiting the data plane to comprise data transformation layer software applied to format data understood by the cloud system (mere data manipulation) and the limit the claimed system to provide customer schema for each tenant and utilize data within warehouse for analysis- - which merely provides a field of use to manage, store data for utilization in analysis of a business process.
Dependent claim 7 is directed toward when MCC calculated is higher than MCC for first trained model and exceed MCC threshold selecting corresponding grace trained model having highest MCC as model for predicting target variable and when first trained model or selected grace period has high MCC deploying first trained model or selected grace period model for predicting target variable of customer- applying a generic algorithm to calculate a business related value which is applied to select a model for predicting a business value – mathematical concepts and business practice. Dependent claim 8 is directed toward when first trained model or selected grace period model has mid-range MCC, segmenting transactions for first customer, segmenting comprising determining a measure of variability of targe variable for each transaction and based on measure of variability classifying each transaction having low, medium or high variation- data analysis, manipulation and organization and mathematical concepts for a business practice.
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 2-9 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 10-18:
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 10 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 claimed invention is directed to an abstract idea without significantly more. Medium 10 recites a executable instructions 1) selecting a customer (2) receiving data (3) extracting historical data to a data staging area (4) transforming historical data into a data warehouse format (5) loading the transformed historical data into a data warehouse (6) determining cost of a delayed payment (7) determining average delay of payments (8) converting cost of delayed payment to a first z-score and average delay of payments to second z-score (9) determining reliability score comprising Euclidean distance of first Z-score and second Z-score (10) displaying score. The claimed limitations which under its broadest reasonable interpretation, covers performance of the limitation in the mind. The claim limitations are silent with respect to any physical structure. Except for the transforming of data into data warehouse format, the recited steps that can easily be performed in the human mind as mental processes because the steps of (1) selecting a customer mimics mental process of decision, the steps (2) receiving data, (3) extracting data, (5) loading data which mimics mental processes of observation and memory. The steps (6) Determining a cost of a delayed payment for each transaction, (7) determining average daily delay of payments, (8) converting cost of delayed payments and average delay of payment into a first and second z-value, (9) determining a reliability score mental process of analysis, mathematical calculations. The claimed subject matter is nothing but a series of mathematical steps and calculations based on selected information. The claimed limitations which under its broadest reasonable interpretation, covers performance of mathematical concepts. The limitations when considered as a whole the claimed subject matter is directed toward the calculation of a reliability score. The wherein clause further limits the selecting customer step by receiving a plurality of models, which is not a process that can reasonably be performed using mental processes. The additional limitation to the selecting step include “determining a Matthews’ Correlation Coefficient for the first model”, “determining the MCC for each …trained model” and based on a condition “deploying the first trained model”. The wherein clause therefore recites the abstract concept of a mathematical concept.(spec ¶ 0054).
The limitations “selecting customer”, “receiving data”, “determining a cost of a delayed payment for each transaction”, “determining average daily delay of payments” and “converting cost of delayed payments and average delay of payment into a first and second z-value” are directed toward the mathematical process of establishing variables applied for determining a reliability score, which is a mathematical process. No mathematical equation can be used, as a practical matter, without establishing values for the variables expressed therein. The obtaining and determining of values dictated by the formula has thus been viewed as a form of mathematical step. If the steps of gathering and determining values were alone sufficient, every mathematical equation, formula, or algorithm having any practical use would be per se subject to patenting as a "process" under § 101. Consideration of whether the determination of specific values is enough to convert the disembodied ideas present in the formula into an embodiment of those ideas, or into an application of the formula, is foreclosed by the current state of the law. The recitation of “cloud based analytics system” merely claims a physical structure at a high level to perform the mental process. The “cloud-based analytics system is nominally mentions and merely automates functions that could reasonably be performed using mental concepts, therefore acting as a generic computer to perform the abstract idea.
Furthermore, when considered as a whole the claimed subject matter is directed toward the calculation of a reliability score. The specification makes clear that the focus of the invention is to receive customer historical data corresponding to transactions with an organization and targeting a variable including number of days of delayed payment for each transaction and the average delay of payment of the customer. (para 0006). The specification discloses that “reliability score” is calculated to measure variations of customers by distribution of delays in payment for each customer by incorporating grace periods for each customer (para 0015) where the determination of the customer reliability score is a result of analyzing customers based on accounts receivable (para 0061) and how much such delays cost companies when compared to their peers (para 0062). The specification makes clear that the purpose of the reliability score. Such concepts can be found in the abstract category of risk mitigation and sales activities/behaviors. The claim limitations do not focus on the technology for data formatting but instead focuses on the calculation of the score which is a mathematical concept. As discussed above, the specification that the purpose of the analysis and the calculation of the score is to analyze and measure human behavior as it related to cost which is a process directed toward commercial activity, a sub-category of the abstract category of methods of organizing human activity. 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 mathematical concepts and methods of organizing human activity.
STEP 2A Prong 2: The identified judicial exception is not integrated into a practical application because the claims limitations merely apply technology to perform the abstract idea. The additional elements recited in the claim beyond the abstract idea include a computer readable medium having stored instructions executed by one or more processors in a cloud based system comprising a data plane, transformation layer and control panel. The “transformation layer” is software per se and amounts to no more than mere instructions to apply the abstract idea.
The “one or more processor” executed instructions applied for “selecting the customer” lacking technical details and is directed toward a business practice
The “one or more processor applied to perform the operations of “receiving …data”, the “data plane” applied to perform the operations “extracting …data”, “loading …data”, and “control plane” applied to perform the “displaying …score of the customer”, which according to MPEP 2106.05(d) II (see also MPEP 2106.05(g)) 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)
Electronically scanning or extracting data from a physical document, Content Extraction and Transmission, LLC v. Wells Fargo Bank, 776 F.3d 1343, 1348, 113 USPQ2d 1354, 1358 (Fed. Cir. 2014) (optical character recognition)
The functions “receiving”, “extracting”, “loading” and “displaying” are recited at a high level of generality without details of technical implementation and thus are insignificant extra solution activity.
The additional element “data plane” applied at a high level to perform the operations “transforming …into data warehouse format” without technical details merely provides instructions (transformation layers) to perform a process which have been found to be insufficient to overcome abstract subject matter - as the focus of the limitation is not the transforming process but rather the expected outcome of formatting data for warehouse format, which is mere data manipulation. 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). Whether the transformation is extra-solution activity or a field-of-use (/.e., the extent to which (or how) the transformation imposes meaningful limits on the execution of the claimed method steps). A transformation that contributes only nominally or insignificantly to the execution of the claimed method (e.g., in a data gathering step or in a field-of-use limitation) would not provide significantly more (or integrate a judicial exception into a practical application). Mayo, 566 U.S. at 76, 101 USPQ2d at 1967. The Supreme Court disagreed, finding that this step was only a field-of-use limitation and did not provide significantly more than the judicial exception. /d. See MPEP § 2106.05(g) & (h).
The additional element “data plane” applied at a high level of generality for performing the data analysis process for performing the abstract idea of “determining a cost”, “determining average delay of payments” and mathematical calculations of “converting cost of delayed payments to a first Z-score and the average delay of payment to a second Z-score” and “determining a reliability score of the customer… determining…Euclidean distance of the first Z-score and second Z-score”. The specification discloses that the purpose of the calculation of the reliability score is for use by the vender to access the risk of a particular customer for customer reliability.
The additional element “cloud based analytics system, merely provides a field of use for performing the identified abstract idea.
The wherein clause does not further limit the system. The wherein clause does not tie the receiving of the model to the selection of the customer, instead the wherein clause limits the models received as part of the selecting customer step. The models received do not perform any of the method steps and are not incorporated in the method process beyond being deployed based on a determined criteria.
When the claims are taken as a whole, as an ordered combination, the combination of limitations 1-5 are directed toward collecting, organizing and manipulating data for loading (inputting) into storage for use in analysis for a business practice. The combination of limitations 6- 9 is to perform a mathematical process using the data collected, organized, manipulated and loaded/inputted in limitations 1-5. The combinations of parts is not directed toward any technical process or technological technique or technological solution to a problem rooted in technology.
In addition, when the claims are taken as a whole, as an ordered combination, 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 when considered as a whole is directed toward collecting, organizing and manipulating data that is loaded into a system for analysis where the analysis is a mathematical process for determining a reliability score and outputting the results. The recitation of the “computer readable medium” and the nominal mention of a “cloud based analytics system” which is a field of use environment and “transformation layer” applied to transform data, fails to provide sufficient additional elements or combination or elements to apply or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception. The functions recited in the claims recite the concept of receiving customer data, manipulating and loading collected data merely provides the variables for use in the mathematical process of determining cost of payment delay, determining average delay of payment, converting data into z-values which are applied to calculate a reliability score. The claim limitations as a whole are a process directed toward a business practice and mathematical concepts.
Because the claim limitations lack technical disclosure and merely mentions the environment where the method is performed (cloud based analytics system) and the tool (transformation layer) applied to “transform data” without technical details of implementation there is no integration of elements for improving upon technology or improve upon computer functionality or capability in how computers carry out one of their basic functions. This also applies to the “dimensional generation” and “aggregate generation” which in light of the specification has been interpreted as data manipulation and organization without details of technical implementation and so high level as to be implemented by any known means. There is no 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 instant application, therefore, still appears only to implement the abstract idea in a broadly claimed field of use environment for calculating values related to a business practice and mathematical concepts. The steps are still a combination made to perform a mathematical process to calculate a value measuring a business metric and does not provide any of the determined indications of patent eligibility set forth in the 2019 USPTO 101 guidance. The functions are is recited at a high-level of generality without any additional elements beyond the identified abstract idea. The claim limitations lacks technical disclosure and therefore fail to provide any indication of patent eligible subject matter under step 2A prong 2. Taking the claim elements separately, the operation performed by the method at each step of the process is purely in terms of results desired and devoid of technical implementation of the claimed process. Technology is not integral to the process as the claimed subject matter fails to mention any technology. 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 additional elements 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, which, when considered in the ordered combination with the other steps, could have transformed the nature of the abstract idea previously identified. 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 computer readable medium having instructions stored that when executed by one or more processors in a cloud based analytics system. The analytics system is nominally mentioned merely providing a field of use environment for the medium. The processor is applied to analyze a customer of an organization where the processor performs the operations of “selecting customer”, “receiving data”, “determining cost”, “determining average delay of payments”, “converting cost and average delay of payments to a first and second z-value” and “determining a reliability score” which are high level functions of the processor lacking technical details. As discussed above under step 2A prong 2, the processor is merely applied to perform the identified abstract idea. Taking the claim elements separately, the function performed by the processor at each step of the process is purely conventional. Using a processor to select data, receive data, determine/analyze data, convert data into values and determine scores ----are some of the most basic functions of a computer processor.
The received trained models do not perform any of the recited step of the method and therefore, do not provide any unconventional technological process or components to the system.
The claimed computer readable medium is analogous to a Beauregard claim. In the court decision, In re Beauregard, 53 F.3d 1583 (Fed.Cir.1995) is a claim to a computer readable medium (e.g., a disk, hard drive, or other data storage device) containing program instructions for a computer to perform a particular process. The claimed medium is analogous with the Beauregard claim, where the Federal Circuit held that 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 detecting credit card fraud over the Internet. Simply reciting the use of a computer to execute an algorithm that can be performed entirely in the human mind will not change the analysis. The Beauregard claim was then treated as a method claim. This claim was determined not to meet the Alice/May 2A and 2B test. Although the claim altered data, "[t]he mere manipulation or reorganization of data, however, does not satisfy the transformation prong." Furthermore, the "incidental use" of a computer did not allow the claim to meet the Alice 2A or 2B requirements. The court noted that even though the method may require the use of a computer, methods that can be performed mentally, or which are the equivalent of human mental work, are unpatentable abstract ideas "even when performed by a computer" has not met its burden to demonstrate that claim 2 is "truly drawn to a specific" computer readable medium, rather than to the underlying method of credit card fraud detection. Similar to the Beauregard decision, the current limitations, as a general matter, are not drawn to a specific computer, instead the claim limitations are directed toward programming a general purpose processor to perform an selecting a customer, receiving data, determining a cost, determining average delay of payments, converting determined cost and average payment delay to z-values and then using the z-values to determine a reliability score. Thus, claim recites a Beauregard claim format, and thus is patent ineligible under step 2B.
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 processor activities that are performed only for their conventional uses for performing the abstract idea. 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 “selecting”, “receiving”, “determining” and “converting”... are executed instructions that can be achieved by any general purpose processor 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 processor to perform generic processor 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-transmission is equally generic and conventional. See Ultramercial, Inc. v. Hulu, LLC, 772 F.3d 709, 715 (Fed. Cir. 2014) (sequence of receiving, selecting, offering for exchange, display, allowing access, and receiving payment 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:
The claimed “cloud based analytics system” is nominally mentioned in the preamble and is not tied to any of the limitations in the body of the claim. Accordingly the “cloud-based analytics system” is merely a field of use recitation (MPEP 2106.05 (h)). Therefore, the “cloud-based analytics system” fails to impose meaningful limits upon the identified conceptual idea discussed above. With respect to the application of the “transformation layer” to perform the step “transforming data” the claim limitation and specification lacks technical details on how the transformation layer performs the step and thus is broad enough to encompass the transformation layer transforming data in its ordinary capacity as such technology was designed to operation. Application of such transformation layer software is known in the art for use in formatting data -WO 2020/039198 A1 by Barnett-“ connect to one or more external databases or APIs and extract data of relevance to the model. These APIs or data sources could be open source or freely available and not in a data format which is readily usable by the model. Therefore, once extracted in raw format or in a format specific to the remote system, the data is transformed in to data structures compatible with the connected graph model representation via a data transformation layer. Once transformed, data is loaded into the model directly via an optional data service layer 17.” (FIG. 3); WO 2010/006187 A2 by Rajaraman et al – “The data transformation layer 204 may include code that forms the outlet for custom or platform-specific data manipulation and formatting. This layer 204 may be used for data in both inbound and outbound message Queues.”…(FIG. 2); US Pub No. 2022/0301031 A1 by Iyer-“ the data processing engine 202 instantiates a data transformation layer that maps and transforms data received from a source. For example, the data transformation layer transforms non-XML data format (e.g., of a data source 135) to XML data format for storage. In some implementations, the data processing engine 202 processes, correlates, integrates, and synchronizes the received data streams from disparate devices 115, servers 120, 140, and data sources 135 into a consolidated data stream to perform the functionalities as described herein:“ Using a data transformation layer to transform data----is the most basic functions of such software.
The specification discloses the determination of cost of delayed customer payment, average delay of payment for a given customer and the converting process as mathematical process without any details related to a technical process:
[0006]… Embodiments convert the cost of delayed payments to a first Z-score
and the average delay of payments to a second Z-score. Embodiments then determine
a reliability score of the customer comprising determining a Euclidean distance of the
first Z-score and the second Z-score.
[0063] At 602, the cost of a delayed payment from the customer is determined as
follows as a dynamic penalty:
Dynamic Cost of Late Paying Customer to Company =
PNG
media_image2.png
430
552
media_image2.png
Greyscale
[0066] At 604, the average delay for a given customer is determined as follow:
PNG
media_image3.png
88
298
media_image3.png
Greyscale
where "n" is the total number of invoices for a customer. This gives an amount of
weighted delay for the customer, including an overall average delay for the customer.
For example, if the customer has paid a large amount of $100 invoices early, even a
short delay on a $1 M invoice will dominate the average delay.
[0067] At 606, the cost from 602 and the delay from 604 is converted into a ZScore
(i.e., a statistical measurement of a score's relationship to the mean in a group of
scores). For the specific customer's average delay at 604, the Z-Score, Zd = (Specific
Customer's Avg. Delay - Avg of Customer Avg Delay)/Std Dev of Customer Avg. Delay.
This determines how far this customer's average delay is from their peers.
[0068] The Z-Score of Cost of a Specific Customer to the Company (from 602) =
Zc = (Specific Customer Cost to Company - Avg of Customer Cost to Company)/Std
Dev of Cost of Customer to Company. This determines how much more expensive is
this customer compared to their peers.
[0069] At 608, the Euclidean distance in the Z-score space is determined to
generate the Customer Relative Reliability Score ("CRRS") at 610 as follows:
PNG
media_image4.png
60
224
media_image4.png
Greyscale
If the score is close to 1, this is a good customer. If the score is beyond 2-3, then this is
a risky customer. If the score is greater than 4, then this is a bad customer that should
The claimed subject is nothing but a series of mathematical calculations based on selected information. The court also has “treated analyzing information by steps people go through in their minds, or by mathematical algorithms, without more, as essentially mental processes within the abstract-idea category. The courts do not distinguish between mental processes that are performed entirely in the human mind and mental processes that require a human to use a physical aid (e.g., pen and paper or a slide rule) to perform the claim limitation. See, e.g., Benson, 409 U.S. at 67, 65, 175 USPQ at 674-75, 674 (noting that the claimed "conversion of [binary-coded decimal] numerals to pure binary numerals can be done mentally," i.e., "as a person would do it by head and hand."); Synopsys, Inc. v. Mentor Graphics Corp., 839 F.3d 1138, 1139, 120 USPQ2d 1473, 1474 (Fed. Cir. 2016) (holding that claims to a mental process of "translating a functional description of a logic circuit into a hardware component description of the logic circuit" are directed to an abstract idea, because the claims "read on an individual performing the claimed steps mentally or with pencil and paper").
According to the Gottschalk v. Benson, 409 U. S. 63; Parker v., decision, a mathematical formula are patent ineligible. This was because the mathematical formula involved here has no substantial practical application except in connection with a computer, similarly, the determining of z-values and reliability scores as claimed using an algorithm that has no impact upon the computer, its functionality or field its functionality or field is patent ineligible. As discussed above, the claimed subject matter is directed toward mathematical concepts. Claims can recite a mental process even if they are claimed as being performed on a computer. The Supreme Court recognized this in Benson, determining that a mathematical algorithm for converting binary coded decimal to pure binary within a computer’s shift register was an abstract idea. The Court concluded that the algorithm could be performed purely mentally even though the claimed procedures "can be carried out in existing computers long in use, no new machinery being necessary." 409 U.S at 67, 175 USPQ at 675. See also Mortgage Grader, 811 F.3d at 1324, 117 USPQ2d at 1699 (concluding that concept of "anonymous loan shopping" recited in a computer system claim is an abstract idea because it could be "performed by humans without a computer"). The current limitations similarly recite as being executed by a process to perform mathematical process is an abstract idea because it can be performed by computers without a computer. 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 11-18 these dependent claim have also been reviewed with the same analysis as independent claim 10. The instructions of Dependent claim 11 corresponds to steps of method claim 2. Therefore, claim 11 has been analyzed and rejected as previously discussed with respect to claim 2. The instructions of Dependent claim 12 corresponds to steps of method claim 3. Therefore, claim 12 has been analyzed and rejected as previously discussed with respect to claim 3. The instructions of Dependent claim 13 corresponds to steps of method claim 4. Therefore, claim 13 has been analyzed and rejected as previously discussed with respect to claim 4. The instructions of Dependent claim 14 corresponds to steps of method claim 5. Therefore, claim 14 has been analyzed and rejected as previously discussed with respect to claim 5. The instructions of Dependent claim 15 corresponds to steps of method claim 6. Therefore, claim 15 has been analyzed and rejected as previously discussed with respect to claim 6. The instructions of Dependent claim 16 corresponds to steps of method claim 7. Therefore, claim 16 has been analyzed and rejected as previously discussed with respect to claim 7. The instructions of Dependent claim 17 corresponds to steps of method claim 8. Therefore, claim 17 has been analyzed and rejected as previously discussed with respect to claim 8. The instructions of Dependent claim 18 corresponds to steps of method claim 9. Therefore, claim 18 has been analyzed and rejected as previously discussed with respect to claim 9.
The dependent claim(s) have been examined individually and in combination with the preceding claims, however they do not cure the deficiencies of claim 10. 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 11-18 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 19-20:
STEP 1. Per Step 1 of the two-step analysis, the claims are determined to include a system, as in independent Claim 19 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 19 recites a functional process of (1) selecting customer (2) receive data (3) extract historical data to a data staging area (4) transforming historical data into a data warehouse format (5) load the transformed historical data into a data warehouse is directed toward data collection for use in a business process and for use in calculating values. The operations (6) determining cost of a delayed payment (7) determining average delay of payments (8) converting cost of delayed payment to a first z-score and average delay of payments to second z-score (9) determining reliability score comprising Euclidean distance of first Z-score and second Z-score (10) displaying score. The claimed subject matter is nothing but a series of mathematical steps and calculations based on selected information.
The limitations “selecting customer”, “receiving data”, “determining a cost of a delayed payment for each transaction”, “determining average daily delay of payments” and “converting cost of delayed payments and average delay of payment into a first and second z-value” are directed toward the mathematical process of establishing variables applied for determining a reliability score, which is a mathematical process. No mathematical equation can be used, as a practical matter, without establishing values for the variables expressed therein. The obtaining and determining of values dictated by the formula has thus been viewed as a form of mathematical step. If the steps of gathering and determining values were alone sufficient, every mathematical equation, formula, or algorithm having any practical use would be per se subject to patenting as a "process" under § 101. Consideration of whether the determination of specific values is enough to convert the disembodied ideas present in the formula into an embodiment of those ideas, or into an application of the formula, is foreclosed by the current state of the law. The recitation of “cloud based analytics system” merely claims a physical structure at a high level to perform the mental process. The “cloud-based analytics system is nominally mentions and merely automates functions that could reasonably be performed mathematical concepts, therefore acting as a generic computer to perform the abstract idea. The wherein clause further limits the selecting customer step by receiving a plurality of models, which is not a process that can reasonably be performed using mental processes. The additional limitation to the selecting step include “determining a Matthews’ Correlation Coefficient for the first model”, “determining the MCC for each …trained model” and based on a condition “deploying the first trained model”. The wherein clause therefore recites the abstract concept of a mathematical concept.(spec ¶ 0054).
Furthermore, when considered as a whole the claimed subject matter is directed toward the calculation of a reliability score. The specification makes clear that the focus of the invention is to receive customer historical data corresponding to transactions with an organization and targeting a variable including number of days of delayed payment for each transaction and the average delay of payment of the customer. (para 0006). The specification discloses that “reliability score” is calculated to measure variations of customers by distribution of delays in payment for each customer by incorporating grace periods for each customer (para 0015) where the determination of the customer reliability score is a result of analyzing customers based on accounts receivable (para 0061) and how much such delays cost companies when compared to their peers (para 0062). The specification makes clear that the purpose of the reliability score. Such concepts can be found in the abstract category of risk mitigation and sales activities/behaviors. The claim limitations do not focus on the technology for data formatting but instead focuses on the calculation of the score which is a mathematical concept. As discussed above, the specification that the purpose of the analysis and the calculation of the score is to analyze and measure human behavior as it related to cost which is a process directed toward commercial activity, a sub-category of the abstract category of methods of organizing human activity. 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 mathematical concepts and methods of organizing human activity.
STEP 2A Prong 2: The additional elements recited in the claim beyond the abstract idea include a cloud based system comprising a data plane, transformation layer and control panel. The “transformation layer” is software per se and amounts to no more than mere instructions to apply the abstract idea.
The “data plane” applied to perform the operations of “extract …data”, “loading …data”, and “control plane” applied to perform the “displaying …score of the customer”, which according to MPEP 2106.05(d) II (see also MPEP 2106.05(g)) 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)
Electronically scanning or extracting data from a physical document, Content Extraction and Transmission, LLC v. Wells Fargo Bank, 776 F.3d 1343, 1348, 113 USPQ2d 1354, 1358 (Fed. Cir. 2014) (optical character recognition)
The functions “extracting” and “loading” are recited at a high level of generality without details of technical implementation and thus are insignificant extra solution activity.
The additional element “data plane” applied at a high level to perform the operations “transforming …into data warehouse format” without technical details merely provides instructions (transformation layers) to perform a process which have been found to be insufficient to overcome abstract subject matter - as the focus of the limitation is not the transforming process but rather the expected outcome of formatting data for warehouse format, which is mere data manipulation. 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). Whether the transformation is extra-solution activity or a field-of-use (/.e., the extent to which (or how) the transformation imposes meaningful limits on the execution of the claimed method steps). A transformation that contributes only nominally or insignificantly to the execution of the claimed method (e.g., in a data gathering step or in a field-of-use limitation) would not provide significantly more (or integrate a judicial exception into a practical application). Mayo, 566 U.S. at 76, 101 USPQ2d at 1967. The Supreme Court disagreed, finding that this step was only a field-of-use limitation and did not provide significantly more than the judicial exception. /d. See MPEP § 2106.05(g) & (h).
The wherein clause does not further limit the system. The wherein clause does not tie the receiving of the model to the selection of the customer, instead the wherein clause limits the models received as part of the selecting customer step. The models received do not perform any of the method steps and are not incorporated in the method process beyond being deployed based on a determined criteria.
The additional element “data plane” applied at a high level of generality for performing the data analysis process for performing the abstract idea of “determining a cost”, “determining average delay of payments” and mathematical calculations of “converting cost of delayed payments to a first Z-score and the average delay of payment to a second Z-score” and “determining a reliability score of the customer… determining…Euclidean distance of the first Z-score and second Z-score”. The specification discloses that the purpose of the calculation of the reliability score is for use by the vender to access the risk of a particular customer for customer reliability.
The additional element “cloud based analytics system, merely provides a field of use for performing the identified abstract idea.
When the claims are taken as a whole, as an ordered combination, the combination of limitations 1-5 are directed toward collecting, organizing and manipulating data for loading (inputting) into storage for use in analysis for a business practice. The combination of limitations 6- 9 is to perform a mathematical process using the data collected, organized, manipulated and loaded/inputted in limitations 1-5. The combinations of parts is not directed toward any technical process or technological technique or technological solution to a problem rooted in technology.
In addition, when the claims are taken as a whole, as an ordered combination, 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 when considered as a whole is directed toward collecting, organizing and manipulating data that is loaded into a system for analysis where the analysis is a mathematical process for determining a reliability score and outputting the results. The nominal mention of a “cloud based analytics system” which is a field of use environment and “transformation layer” applied to transform data, fails to provide sufficient additional elements or combination or elements to apply or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception. The functions recited in the claims recite the concept of receiving customer data, manipulating and loading collected data merely provides the variables for use in the mathematical process of determining cost of payment delay, determining average delay of payment, converting data into z-values which are applied to calculate a reliability score. The claim limitations as a whole are a process directed toward a business practice and mathematical concepts.
Because the claim limitations lack technical disclosure and merely mentions the environment where the method is performed (cloud based analytics system) and the tool (transformation layer) applied to “transform data” without technical details of implementation there is no integration of elements for improving upon technology or improve upon computer functionality or capability in how computers carry out one of their basic functions. This also applies to the “dimensional generation” and “aggregate generation” which in light of the specification has been interpreted as data manipulation and organization without details of technical implementation and so high level as to be implemented by any known means. There is no 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 instant application, therefore, still appears only to implement the abstract idea in a broadly claimed field of use environment for calculating values related to a business practice and mathematical concepts. The steps are still a combination made to perform a mathematical process to calculate a value measuring a business metric and does not provide any of the determined indications of patent eligibility set forth in the 2019 USPTO 101 guidance. The functions are is recited at a high-level of generality without any additional elements beyond the identified abstract idea. The claim limitations lacks technical disclosure and therefore fail to provide any indication of patent eligible subject matter under step 2A prong 2. Taking the claim elements separately, the operation performed by the method at each step of the process is purely in terms of results desired and devoid of technical implementation of the claimed process. Technology is not integral to the process as the claimed subject matter fails to mention any technology. 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 additional elements 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, which, when considered in the ordered combination with the other steps, could have transformed the nature of the abstract idea previously identified. 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 one or more processors executing instructions, data plane and control panel to perform the operations corresponding to claim 10. The system processor is applied to analyze a customer of an organization where the processor performs the operations of “selecting customer”, “receiving data”, “extract data”, “transform data”, “load data”, “determining cost”, “determining average delay of payments”, “converting cost and average delay of payments to a first and second z-value”, “determining a reliability score” and “display score” which are high level functions of the processor lacking technical details. As discussed above under step 2A prong 2, the system processor is merely applied to perform the identified abstract idea (mathematical process). Taking the claim elements separately, the function performed by the system processor at each step of the process is purely conventional. Using a processor to select data, receive data, determine/analyze data, convert data into values and determine scores ----are some of the most basic functions of a computer processor.
The received trained models do not perform any of the recited step of the method and therefore, do not provide any unconventional technological process or components to the system.
The claim is not "truly drawn to a specific" system, but rather is directed toward applying a system processor as a tool for selecting a customer, receiving data, extract data, transform data, load data, determining a cost, determining average delay of payments, converting determined cost and average payment delay to z-values and then using the z-values to determine a reliability score for a business process. The functions of the system processor are recited at a high level of generality without any details as to technical implementation. The system processor amount to no more than using a system processor to perform outcome operations of “determining cost of delay of payments”, ‘determining average delay of payments from customers”, “converting” the determined cost and average delay to z-values which are then sum to provide a score. Although the claim altered data, “convert [data] to z-values, this, does not satisfy the transformation prong." This is because the “convert” (manipulation) is a basic mathematical construct. Such 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 In re Warmerdam, 33 F.3d 1354, 1355, 1360 (Fed. Cir. 1994). Whether the transformation is extra-solution activity or a field-of-use (i.e., the extent to which (or how) the transformation imposes meaningful limits on the execution of the claimed method steps). A transformation that contributes only nominally or insignificantly to the execution of the claimed method (e.g., in a data gathering step or in a field-of-use limitation) would not provide significantly more (or integrate a judicial exception into a practical application). Mayo, 566 U.S. at 76, 101 USPQ2d at 1967. The Supreme Court disagreed, finding that this step was only a field-of-use limitation and did not provide significantly more than the judicial exception. Id. See MPEP § 2106.05(g) & (h)
Furthermore, the "incidental use" of a system processor does not allow the claim to meet the Alice 2B requirements. The claim limitations do not recite any specific unconventional technical process, but rather applies the system process to perform the underlying determining a reliability score using z-values determined from customer payment data. The current limitations, as a general matter, are not drawn to a specific computer system, instead the claim limitations are directed toward programming a general purpose processor to perform an selecting a customer, receiving data, determining a cost, determining average delay of payments, converting determined cost and average payment delay to z-values and then using the z-values to determine a reliability score. Thus, claim is patent ineligible under step 2B.
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 processor activities that are performed only for their conventional uses for performing the abstract idea. 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 “selecting”, “receiving”, “extracting”, “transforming”, “loading”, “determining” and “converting”... are executed instructions that can be achieved by any general purpose processor 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 processor to perform generic processor 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-transmission is equally generic and conventional. See Ultramercial, Inc. v. Hulu, LLC, 772 F.3d 709, 715 (Fed. Cir. 2014) (sequence of receiving, selecting, offering for exchange, display, allowing access, and receiving payment 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:
The claimed “cloud based analytics system” is nominally mentioned in the preamble and is not tied to any of the limitations in the body of the claim. Accordingly the “cloud-based analytics system” is merely a field of use recitation (MPEP 2106.05 (h)). Therefore, the “cloud-based analytics system” fails to impose meaningful limits upon the identified conceptual idea discussed above. With respect to the application of the “transformation layer” to perform the step “transforming data” the claim limitation and specification lacks technical details on how the transformation layer performs the step and thus is broad enough to encompass the transformation layer transforming data in its ordinary capacity as such technology was designed to operation. Application of such transformation layer software is known in the art for use in formatting data -WO 2020/039198 A1 by Barnett-“ connect to one or more external databases or APIs and extract data of relevance to the model. These APIs or data sources could be open source or freely available and not in a data format which is readily usable by the model. Therefore, once extracted in raw format or in a format specific to the remote system, the data is transformed in to data structures compatible with the connected graph model representation via a data transformation layer. Once transformed, data is loaded into the model directly via an optional data service layer 17.” (FIG. 3); WO 2010/006187 A2 by Rajaraman et al – “The data transformation layer 204 may include code that forms the outlet for custom or platform-specific data manipulation and formatting. This layer 204 may be used for data in both inbound and outbound message Queues.”…(FIG. 2); US Pub No. 2022/0301031 A1 by Iyer-“ the data processing engine 202 instantiates a data transformation layer that maps and transforms data received from a source. For example, the data transformation layer transforms non-XML data format (e.g., of a data source 135) to XML data format for storage. In some implementations, the data processing engine 202 processes, correlates, integrates, and synchronizes the received data streams from disparate devices 115, servers 120, 140, and data sources 135 into a consolidated data stream to perform the functionalities as described herein:“ Using a data transformation layer to transform data----is the most basic functions of such software.
The specification discloses the determination of cost of delayed customer payment, average delay of payment for a given customer and the converting process as mathematical process without any details related to a technical process:
[0006]… Embodiments convert the cost of delayed payments to a first Z-score
and the average delay of payments to a second Z-score. Embodiments then determine
a reliability score of the customer comprising determining a Euclidean distance of the
first Z-score and the second Z-score.
[0063] At 602, the cost of a delayed payment from the customer is determined as
follows as a dynamic penalty:
Dynamic Cost of Late Paying Customer to Company =
PNG
media_image2.png
430
552
media_image2.png
Greyscale
[0066] At 604, the average delay for a given customer is determined as follow:
PNG
media_image3.png
88
298
media_image3.png
Greyscale
where "n" is the total number of invoices for a customer. This gives an amount of
weighted delay for the customer, including an overall average delay for the customer.
For example, if the customer has paid a large amount of $100 invoices early, even a
short delay on a $1 M invoice will dominate the average delay.
[0067] At 606, the cost from 602 and the delay from 604 is converted into a ZScore
(i.e., a statistical measurement of a score's relationship to the mean in a group of
scores). For the specific customer's average delay at 604, the Z-Score, Zd = (Specific
Customer's Avg. Delay - Avg of Customer Avg Delay)/Std Dev of Customer Avg. Delay.
This determines how far this customer's average delay is from their peers.
[0068] The Z-Score of Cost of a Specific Customer to the Company (from 602) =
Zc = (Specific Customer Cost to Company - Avg of Customer Cost to Company)/Std
Dev of Cost of Customer to Company. This determines how much more expensive is
this customer compared to their peers.
[0069] At 608, the Euclidean distance in the Z-score space is determined to
generate the Customer Relative Reliability Score ("CRRS") at 610 as follows:
PNG
media_image4.png
60
224
media_image4.png
Greyscale
If the score is close to 1, this is a good customer. If the score is beyond 2-3, then this is
a risky customer. If the score is greater than 4, then this is a bad customer that should
The claimed subject is nothing but a series of mathematical calculations based on selected information. The court also has “treated analyzing information by steps people go through in their minds, or by mathematical algorithms, without more, as essentially mental processes within the abstract-idea category. The courts do not distinguish between mental processes that are performed entirely in the human mind and mental processes that require a human to use a physical aid (e.g., pen and paper or a slide rule) to perform the claim limitation. See, e.g., Benson, 409 U.S. at 67, 65, 175 USPQ at 674-75, 674 (noting that the claimed "conversion of [binary-coded decimal] numerals to pure binary numerals can be done mentally," i.e., "as a person would do it by head and hand."); Synopsys, Inc. v. Mentor Graphics Corp., 839 F.3d 1138, 1139, 120 USPQ2d 1473, 1474 (Fed. Cir. 2016) (holding that claims to a mental process of "translating a functional description of a logic circuit into a hardware component description of the logic circuit" are directed to an abstract idea, because the claims "read on an individual performing the claimed steps mentally or with pencil and paper").
According to the Gottschalk v. Benson, 409 U. S. 63; Parker v., decision, a mathematical formula are patent ineligible. This was because the mathematical formula involved here has no substantial practical application except in connection with a computer, similarly, the determining of z-values and reliability scores as claimed using an algorithm that has no impact upon the computer, its functionality or field its functionality or field is patent ineligible. As discussed above, the claimed subject matter is directed toward mathematical concepts. Claims can recite a mental process even if they are claimed as being performed on a computer. The Supreme Court recognized this in Benson, determining that a mathematical algorithm for converting binary coded decimal to pure binary within a computer’s shift register was an abstract idea. The Court concluded that the algorithm could be performed purely mentally even though the claimed procedures "can be carried out in existing computers long in use, no new machinery being necessary." 409 U.S at 67, 175 USPQ at 675. See also Mortgage Grader, 811 F.3d at 1324, 117 USPQ2d at 1699 (concluding that concept of "anonymous loan shopping" recited in a computer system claim is an abstract idea because it could be "performed by humans without a computer"). The current limitations similarly recite as being executed by a process to perform mathematical process is an abstract idea because it can be performed by computers without a computer
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 claim 20 this dependent claim has also been reviewed with the same analysis as independent claim 19. The processor functions of claim 20 corresponds to steps of method claim 2. Therefore, claim 20 has been analyzed and rejected as previously discussed with respect to claim 2.
The dependent claim(s) has been examined individually and in combination with the preceding claims, however they do not cure the deficiencies of claim 19. 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 20 is 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.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. CA-3068264-C by BARASH; CA-3156785-A1 by Champion.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Christine Behncke can be reached at 571-272-8103. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MARY M GREGG/Examiner, Art Unit 3695
/CHRISTINE M Tran/Supervisory Patent Examiner, Art Unit 3695
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