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 .
Status of Claims
This action is in reply to the communication(s) filed on 24 May 2023.
Claim(s) 1-20 is/are currently pending and have been examined.
Claim Interpretation
Examiner is interpreting the phrase “cooperate” to be equivalent to the phrase “are used together” for purposes of examination.
Examiner notes that an “actionable feature” includes any feature upon which an action may be performed.
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.
Step 1 of the 101 Analysis:
Claims 19-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim(s) does/do not fall within at least one of the four categories of patent eligible subject matter because they encompass transitory signals or carrier waves in their scope. Products that do not have a physical or tangible form, such as information (often referred to as “data per se”) or a computer program per se (often referred to as “software per se”) are not directed to any of the statutory categories when claimed as a product without any structural recitations (See MPEP § 2106.03(I).) Therefore, the claims are not patent eligible.
The broadest reasonable interpretation of computer readable storage media based on common usage covers signals/carrier waves.
The applicant can choose other ways to amend the claim in accordance with the original disclosure.
It is not acceptable to just add “physical” or “tangible” - Nuijten’s ineligible signals were physical and tangible.
It is not acceptable to add “storage” absent support in original disclosure because the broadest reasonable interpretation of computer readable storage media based on common usage covers signals/carrier waves.
For the purposes of compact prosecution examiner will continue the 101 analysis as if the claims positively recite non-transitory computer-readable media.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claims recites a method, system and computer program product for outlier detection of transactions. These are a process, machine, and article of manufacture which are within the four categories of statutory subject matter.
Step 2A Prong 1 of the 101 Analysis:
The following limitations and/or similar versions are recited in claim(s) 1, 10 and 19:
Claim(s) 1, 10 and 19:
“receiving,…, transaction data from the plurality of transaction processing sites, the transaction data comprising at least one selected from the group of an insurance claim, a financial institution transaction, and an insurance claim disposition;”
“determining,… , transformed transaction data based on the transaction data,”
“determining one or more features from the transformed transaction data;”
“determining one or more actionable features from the one or more features;”
“generating an outlier transaction identification model from the one or more actionable features;”
“selecting a selected control policy for the outlier transaction identification model, wherein the outlier transaction identification model and the selected control policy cooperate…to determine an outlier transaction identification alert.”
These limitations, as drafted, are a process that, under its broadest reasonable interpretation, describes Fundamental Economic Principles or Practices but for the recitation of generic computer components. That is, other than reciting “a first server in the plurality of enterprise servers, the first server comprising a memory and a processor in communication with the memory, the processor configured to:” or “A computer program product comprising computer-readable instructions carried on a computer readable medium which, when executed by a processor, cause the processor to perform a method for generating an outlier transaction identification model and a selected control policy within an enterprise network comprising a plurality of transaction processing sites and a plurality of enterprise servers, the method comprising:” nothing in the claims’ elements precludes the steps from practically describing Fundamental Economic Principles or Practices. For example, but for the recited computer language, the limitations in the context of this claim describes Mitigating Risk. Mitigating Risk is described when identifying fraudulent transactions through outlier detection and selecting a control policy based on the identified transactions. If a claim limitations, under their broadest reasonable interpretation, describes Fundamental Economic Principles or Practices but for the recitation of generic computer components, then it falls within the “Certain Methods of Organizing Activity” grouping of abstract ideas.
Accordingly, the independent claims recite an abstract idea.
Step 2A Prong 2 of the 101 Analysis:
This judicial exception is not integrated into a practical application. In particular, the independent claim(s) recite the following (or similar) additional elements:
Claim 1:
“…at a first server of the plurality of enterprise servers…”
“…at the first server…”
“…with an intelligent agent…”
Claim 10:
“a first server in the plurality of enterprise servers, the first server comprising a memory and a processor in communication with the memory, the processor configured to:”
“…with an intelligent agent…”
Claim :
“A computer program product comprising computer-readable instructions carried on a computer readable medium which, when executed by a processor, cause the processor to perform a method for generating an outlier transaction identification model and a selected control policy within an enterprise network comprising a plurality of transaction processing sites and a plurality of enterprise servers, the method comprising:”
The computer components (servers, memory, processor and non-transitory computer-readable medium) are recited at a high level of generality (i.e. as a generic server, generic memory, generic processor, and generic non-transitory computer-readable medium) such that it amounts to no more than mere instructions to implement the judicial exception on a computer or by using a computer merely as a tool to perform an existing process. These element(s) in combination do not add anything that is not already present when the steps are considered separately. Simply implementing an abstract idea on a computer as a tool to perform an existing process is not indicative of integration into a practical application (See MPEP § 2106.05(f).)
The use of an intelligent agent is implemented at a high level of generality (i.e. as simply using the technology) such that it amounts to no more than generally linking the use of the judicial exception to a particular technological environment or field of use. These element(s) in combination do not add anything that is not already pre-sent when the steps are considered separately. Generally linking the use of the judicial exception to a particular technological environment or field of use is not indicative of integration into a practical application (See MPEP § 2106.05(h).)
Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
The independent claims are directed to an abstract idea.
Step 2B of the 101 Analysis:
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements identified in Step 2A Prong 2 (if any) amount to no more than mere instructions to implement the judicial exception on a computer or no more than mere data gathering or data outputting which only adds insignificant extra solution activity to the judicial exception. Accordingly, the Examiner:
• Carries over their identification of the additional element(s) in the claim from Step 2A Prong Two;
• Carries over their conclusions from Step 2A Prong Two on the considerations discussed in MPEP §§ 2106.05(a) - (c), (e) (f) and (h):
• Re-evaluates any additional element or combination of elements that was considered to be insignificant extra-solution activity per MPEP § 2106.05(g), because if such re-evaluation finds that the element is unconventional or otherwise more than what is well-understood, routine, conventional activity in the field, this finding may indicate that the additional element is no longer considered to be insignificant.
These element(s) in combination do not add anything that is not already present when the steps are considered separately. Adding insignificant extra-solution activity cannot provide an inventive concept when the activities are well-understood routine and conventional. The independent claims do not recite any limitations which are considered as insignificant extra-solution activity.
The independent claims are not patent eligible.
Dependent Claim(s) 2-9, 11-18 and 20 recite limitations that are similar to the abstract idea noted in the independent claims because they further narrow the independent claim(s) which recite one or more judicial exceptions. Accordingly, these claim elements do not serve to confer subject matter eligibility to the claims since they recite abstract ideas.
The claims are not patent eligible.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1, 8, 10, 17 and 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Mumma et al. (US 2022/0012604 A1 hereinafter Mumma) in view of Sangvhi et al. (US 2022/0036450 A1 hereinafter Sanghvi).
Claim 1
A method for generating an outlier transaction identification model and a selected control policy within an enterprise network comprising a plurality of transaction processing sites and a plurality of enterprise servers, the method comprising: (Mumma discloses AI engine creating alert triggers associated with transactions (i.e. outlier models) and actionable responses (i.e. selected control policies). See at least paragraph [0109]. Mumma discloses deploying engine in an interconnected network (i.e. transaction processing sites. See at least paragraphs [0104]-[0105]. Mumma discloses network deployed for corporate funds tracking (i.e. within an enterprise network). See at least paragraph [0013]. Mumma discloses deployment on servers. See at least paragraphs [0014] and [0042].)
receiving, at a first server of the plurality of enterprise servers, transaction data from the plurality of transaction processing sites, the transaction data comprising at least one selected from the group of an insurance claim, a financial institution transaction, and an insurance claim disposition; (Mumma discloses collection of transaction attributes from the transaction data. See at least paragraph [0052] and Table 1.
Although Mumma does disclose the above, they might not explicitly disclose the transaction data comprising at least one selected from the group of an insurance claim, a financial institution transaction, and an insurance claim disposition. Sanghvi teaches that transactions may include banking operations of a financial institution. See at least paragraph [0024].
It would be obvious to one of ordinary skill in the art before the effective filing date to including banking operations of a financial institution as taught by Sanghvi in the transaction data of Mumma because Sanghvi additionally teaches the motivation that this provides various enterprise and/or back-office computing functions for said institutions. See at least paragraph [0022].
Also, including banking operations of a financial institution as taught by Sanghvi in the transaction data of Mumma is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.)
determining, at the first server, transformed transaction data based on the transaction data, (Mumma discloses transformed data including change of data based on data attributes. See at least paragraph [0052] and Table 1. Examiner notes at least the user access history attributes may also be a set of transformed data based on the attributes.)
determining one or more features from the transformed transaction data; (Mumma discloses any of the data of Table 1 may qualify as a feature of a target transaction or may depend on another payment. See at least paragraph [0052] and Table 1. )
determining one or more actionable features from the one or more features; (Mumma discloses any of the data of Table 1 may result in actions taken (i.e. determining an actionable feature). See at least paragraph [0052] and Table 1.)
generating an outlier transaction identification model from the one or more actionable features; and (Mumma discloses AI engine creating alert triggers associated with transactions (i.e. outlier models) and actionable responses (i.e. selected control policies). See at least paragraph [0109]. Mumma discloses any of the data of Table 1 may result in actions taken (i.e. determining an actionable feature). See at least paragraph [0052] and Table 1.)
selecting a selected control policy for the outlier transaction identification model, wherein the outlier transaction identification model and the selected control policy cooperate with an intelligent agent to determine an outlier transaction identification alert. (Mumma discloses AI engine creating alert triggers associated with transactions (i.e. outlier models) and actionable responses (i.e. selected control policies). See at least paragraph [0109]. Mumma discloses any of the data of Table 1 may result in actions taken (i.e. determining an actionable feature). See at least paragraph [0052] and Table 1. Mumma discloses an AI engine applying the actionable response alert trigger based on unusual behavior (i.e. outlier) and based on target transaction and alert trigger (i.e. selected control policy). See at least paragraphs [0058]-[0063]. Mumma discloses the AI engine may formulate a notification based on the alert trigger. See at least paragraph [0032].)
Claim 8
The method of claim 1, wherein the feature determination comprises performing at least one selected from the group of a linear correlation, a principal components analysis, and least absolute shrinkage and selection operator (LASSO) regularized regression. (Although Mumma does disclose determining features using an AI engine, they might not explicitly disclose said determination comprising performing at least one selected from the group of a linear correlation, a principal components analysis, and least absolute shrinkage and selection operator (LASSO) regularized regression. Sanghvi teaches that attribute analysis may use unsupervised learning algorithms such as principal component analysis. See at least paragraph [0031].
It would be obvious to one of ordinary skill in the art before the effective filing date to utilize a principal component analysis learning algorithm as taught by Sanghvi for the AI engine in Mumma because Sanghvi additionally teaches the motivation that such algorithms may be utilized for attribute behavior determinations. See at least paragraph [0031].
Also, utilizing a principal component analysis learning algorithm as taught by Sangvhi for the AI engine in Mumma is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.)
Claim 10
A system for generating an outlier transaction identification model and a selected control policy within an enterprise network comprising a plurality of transaction processing sites and a plurality of enterprise servers, the system comprising: (Mumma discloses AI engine creating alert triggers associated with transactions (i.e. outlier models) and actionable responses (i.e. selected control policies). See at least paragraph [0109]. Mumma discloses deploying engine in an interconnected network (i.e. transaction processing sites. See at least paragraphs [0104]-[0105]. Mumma discloses network deployed for corporate funds tracking (i.e. within an enterprise network). See at least paragraph [0013]. Mumma discloses deployment on servers. See at least paragraphs [0014] and [0042].)
a first server in the plurality of enterprise servers, the first server comprising a memory and a processor in communication with the memory, the processor configured to: (Mumma discloses deploying engine in an interconnected network (i.e. transaction processing sites. See at least paragraphs [0104]-[0105]. Mumma discloses network deployed for corporate funds tracking (i.e. within an enterprise network). See at least paragraph [0013]. Mumma discloses deployment on servers. See at least paragraphs [0014] and [0042]. Mumma discloses embodiment with processor and memory. See at least paragraph [0019].)
…
The remainder of Claim 10 is substantially similar to or broader than the corresponding elements in Claim 1 and is therefore rejected using similar reasoning.
Claim 17
Claim 17 is substantially similar to or broader than the corresponding elements in Claim 8 and is therefore rejected using similar reasoning.
Claim 19
A computer program product comprising computer-readable instructions carried on a computer readable medium which, when executed by a processor, cause the processor to perform a method for generating an outlier transaction identification model and a selected control policy within an enterprise network comprising a plurality of transaction processing sites and a plurality of enterprise servers, the method comprising: (Mumma discloses AI engine creating alert triggers associated with transactions (i.e. outlier models) and actionable responses (i.e. selected control policies). See at least paragraph [0109]. Mumma discloses deploying engine in an interconnected network (i.e. transaction processing sites. See at least paragraphs [0104]-[0105]. Mumma discloses network deployed for corporate funds tracking (i.e. within an enterprise network). See at least paragraph [0013]. Mumma discloses deployment on servers. See at least paragraphs [0014] and [0042].)
…
The remainder of Claim 19 is substantially similar to or broader than the corresponding elements in Claim 1 and is therefore rejected using similar reasoning.
Claim(s) 6-7 and 15-16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Mumma et al. (US 2022/0012604 A1 hereinafter Mumma) in view of Sangvhi et al. (US 2022/0036450 A1 hereinafter Sanghvi) further in view of Walters et al. (US 2021/0150621 A1` hereinafter Walters).
Claim 6
The method of claim 1, further comprising performing a signal analysis to generate signal analysis data, wherein the transformed transaction data comprises the transaction data and the signal analysis data. (Although Mumma does disclose transformed transaction data, they might not explicitly disclose performing a signal analysis to generate signal analysis data, wherein the transformed transaction data comprises the transaction data and the signal analysis data. Walters teaches performing a Fast Fourier Transform on spending information (i.e. signal analysis) in order to obtain a power spectrum of the spending (i.e. signal analysis data). See at least paragraphs [0034]-[0036].
It would be obvious to one of ordinary skill in the art before the effective filing date to include a power spectrum of spending as taught by Walters in the system of Mumma because Walters additionally teaches the motivation that this determines the spending habits for a particular mental state of the user. See at least paragraphs [0034]-[0036].
Also, include a power spectrum of spending as taught by Walters in the system of Mumma is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.)
Claim 7
The method of claim 6, wherein the signal analysis data comprises a power spectrum. (This is taught by the combination with Walters as shown above.)
Claim 15
Claim 15 is substantially similar to or broader than the corresponding elements in Claim 6 and is therefore rejected using similar reasoning.
Claim 16
Claim 16 is substantially similar to or broader than the corresponding elements in Claim 7 and is therefore rejected using similar reasoning.
Claim(s) 9 and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Mumma et al. (US 2022/0012604 A1 hereinafter Mumma) in view of Sangvhi et al. (US 2022/0036450 A1 hereinafter Sanghvi) further in view of Shahidzadeh et al. (US 12,035,136 B1 hereinafter Shahidzadeh).
Claim 9
The method of claim 1, wherein the outlier transaction identification model and the selected control policy are provided to an operational computer system using an application programming interface (API). (Mumma discloses an AI engine applying (i.e. provided to an operational computer system) the actionable response alert trigger based on unusual behavior (i.e. outlier) and based on target transaction and alert trigger (i.e. selected control policy). See at least paragraphs [0058]-[0063].
Although Mumma does disclose providing the model and policy to an operational computer system, they might not explicitly disclose doing so using an API. Shahidzadeh teaches pulling an AI/ML model using API. See at least column 16, line 62 – column 7, line 49. Shahidzadeh teaches applying a policy engine via APIs. See at least column 16, line 62 – column 7, line 49 and column 24, lines 6-18.
It would be obvious to one of ordinary skill in the art before the effective filing date to apply the AI engines of Mumma via APIs as taught by Shahidzadeh because Shahidzadeh discloses APIs indicates that the claimed identity cannot be confirmed online or in person and has a low level of assurance score then an appropriate action such as access decline or step up authentication is enforced. See at least column 3, lines 23-36.
Also, applying the AI engines of Mumma via APIs as taught by Shahidzadeh is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.)
Claim 18
Claim 18 is substantially similar to or broader than the corresponding elements in Claim 9 and is therefore rejected using similar reasoning.
Examiner’s Note
Examiner notes a search was performed but did not result in a prior art rejection against Claims 2-5, 11-14 and 20.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Chiluka et al. (US 2021/0027218 A1) discloses the use of Gradient Descent to determine global minima of functions.
Agrawal et al. (EP 3706389 A1) discloses utilization of machine learning or other artificial intelligence for an electronic notification system used to flag fraud.
Zhang et al. (CN 110443618 A) discloses determining correlation coefficients for control policies.
Lin et al. (“Fraud Detection in Dynamic Interaction Network”) discloses the use of interaction matrices for fraud detection modelling.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ADAM J HILMANTEL whose telephone number is (571)272-8984. The examiner can normally be reached M-F 8:30AM-5:00PM.
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, Abhishek Vyas can be reached at (571) 270-1836. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ADAM HILMANTEL/Examiner, Art Unit 3691