DETAILED ACTION
Status of Application
This action is a Final Rejection. This action is in response to the amendment and response filed on April 30, 2026.
Claims 1 and 16 have been amended.
Claim 11 has been canceled.
Claims 1-10 and 12-16 are pending and rejected.
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . 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 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.
Response to Arguments
Regarding the rejection under 35 U.S.C. 101, Applicant argues that “[t]he claimed operations are not steps that can be practically performed in the human mind.” Remarks at 2. Applicant asserts that the claimed “operations are tied to computerized trade-surveillance data structures and machine-executed modules, an are not merely observation, evaluation, or judgment by a human analyst.” Id. However, the claimed steps could be performed mentally or on paper. For example, one could mentally or manually select raw stock-news, evaluate transaction alerts, collect transaction-alert related data points and form clusters of related data points, assign a priority to each data point, and pause a transaction. Additionally, Applicant should refer to the analysis of claim 2 of Example 47, which explains how that claim has steps which could be practically performed in the human mind.
Applicant further argues that “the claims are not directed merely to organizing human activity.” Remarks at 2. Applicant asserts that automatically pausing a transaction “is not a mere instruction to a human compliance officer to review information, nor is it merely the organization of human decision-making. It is a claimed system operation performed as part of the computerized trade-surveillance process.” Id. However, as explained in the rejection, the claims are directed to identifying and forwarding transaction alerts that may indicate suspicious activity like insider trading. This is a business process, i.e., a fundamental economic practice and a commercial interaction. Whether a transaction is paused manually or automatically is not relevant as to whether an abstract idea is recited here.
Applicant further argues that “the claim does not end at identifying, analyzing, ranking, or displaying information. The claimed pipeline changes the operative state of the trade-surveillance process by automatically pausing a transaction related to an above-threshold transaction-alert related data point. The automated transaction pause is not merely insignificant extra-solution activity. It is the claimed practical application of the preceding computerized processing steps.” Remarks at 3. However, automatically pausing a transaction is not a practical application because all it requires is a programmed general purpose computing device—i.e., a device that is used as a tool to perform the abstract idea of pausing a transaction. Additionally, the rejection does not allege that any of the limitations are insignificant extra-solution activity.
Applicant further argues that “[t]he pending claims therefore improve the operation of a computerized trade-surveillance system by reducing false-positive transaction-alerts through a specific news-alert correlation and clustering process, and by causing the system to take an automated action when the claimed priority threshold is satisfied.” Remarks at 3. However, Applicant is describing an alleged improvement to a business process, i.e., abstract idea, and not a technological improvement.
Applicant further argues that “[t]he ordered combination of Claim 1 is not a generic instruction to apply a business concept on a computer. Claim 1 recites a specific arrangement of computer-implemented modules that operate on particular types of data in a particular order….” Remarks at 4. Applicant asserts that the “ordered combination is significant. The automated transaction pause is not performed in isolation. It is triggered only after the claimed sequence [of steps].” Id. However, automatically pausing a transaction when the priority assigned to the transaction-alert related data point exceeds the preconfigured threshold is part of the abstract idea. Using a programmed general purpose computing device to pause a transaction does not amount to significantly more than the abstract idea. The claim as a whole is using a computer to implement an abstract idea.
As such, the rejection is maintained.
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 1-10 and 12-16 are rejected under 35 U.S.C. § 101 as being directed to non-statutory subject matter because the claimed invention is directed to an abstract idea without significantly more.
Step 1: Does the Claim Fall within a Statutory Category? (see MPEP 2106.03)
Yes, with respect to claims 1-10 and 12-15, which recite a method and, therefore, are directed to the statutory class of process.
Yes, with respect to claim 16, which recites a system and, therefore, is directed to the statutory class of machine or manufacture.
Step 2A, Prong One: Is a Judicial Exception Recited? (see MPEP 2106.04(a))
The following claims (Claims 1-10 and 12-15 are representative) identify the limitations that recite the abstract idea in regular text and that recite additional elements in bold:
1. A computerized-method for reducing false-positive transaction-alerts in a trade-surveillance system, said computerized-method comprising:
selecting raw input stock-news which are received from a platform of a source based on preconfigured one or more criteria by operating a raw-news-filtering module to yield filtered stock-news, wherein the raw input stock-news comprises one or more events which are related to stock market and wherein each event in the one or more events has associated news-metadata;
evaluating transaction-alerts received in a preconfigured date-range, by operating an alert-discovery module,
wherein the evaluation is based on the filtered stock-news, and
wherein the evaluation yields one or more transaction-alert related data points;
collecting the transaction-alert related data points and form one or more clusters of the transaction-alert related data points, by operating K-means-clustering module wherein each cluster of the one or more clusters is associated with a category;
assigning a priority to each transaction-alert related data point of the transaction-alert related data points, based on the associated category of the cluster of the transaction-alert related data point and a transaction-related risk, by operating a prioritization module; and
forwarding each transaction-alert related data point that is assigned a priority above a preconfigured threshold-to a compliance officer; and
automatically pausing a transaction that the transaction-alert related data point that is assigned to the priority above the preconfigured threshold related to, for each transaction-alert related data point that is assigned the priority above the preconfigured threshold, by operating an automated-actions module.
2. The computerized-method of claim 1, wherein the one or more criteria are selected from at least one of: (i) symbol; (ii) market; (iii) source; (iv) relevance-score; and (v) novelty.
3. The computerized-method of claim 1, wherein the platform of the source is a platform of a news provider.
4. The computerized-method of claim 1, wherein said news-metadata comprises at least one of: (i) stock symbol; (ii) Market Identifier Code (MIC); (iii) company information.
5. The computerized-method of claim 1, wherein said K-means-clustering module is matching transaction-alerts and news-metadata of the one or more events to assign transaction-alert data points to a cluster by using a regular expressions language.
6. The computerized-method of claim 5, wherein the assigning of each transaction-alert data point to a cluster is by finding centroid assignment.
7. The computerized method of claim 6, wherein the finding of the centroid assignment is by calculating Euclidean distance, said Euclidean distance is calculated by formula I:
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94
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whereby: p,q are two random data points in an Euclidean n-space,
qi, pi are Euclidean vectors, starting from an origin of the space, and
n=n-space.
8. The computerized-method of claim 1, wherein the preconfigured one or more criteria are selected in real-time.
9. The computerized-method of claim 1, wherein the category is one of: (i) low; (ii) medium; and (iii) high.
10. The computerized-method of claim 1, wherein a notification is sent as to each transaction-alert related data point that is assigned a priority above the preconfigured threshold to a compliance officer for investigation.
12. The computerized-method of claim 1, wherein for each transaction-alert related data point that is assigned the priority above the preconfigured threshold putting at least one of: (i) financial institution; (ii) trader; (iii) account, that a transaction that is related to the transaction-alert related data point that is assigned the priority above the preconfigured threshold has been conducted through, under a watchlist.
13. The computerized-method of claim 1, wherein each transaction-alert related data point that is assigned the priority above the preconfigured threshold is presented via a display unit with related details.
14. The computerized-method of claim 1, wherein the transaction-alerts are generated by analytics modules which comprise a set of detection algorithms.
15. The computerized-method of claim 1, wherein the alert-discovery module is evaluating the transaction-alerts by operating a set of Application Programming Interfaces (API)s which fetch the transaction-alerts that have matching news metadata as in the filtered stock-news, from a database.
Yes. But for the recited additional elements as shown above in bold, the remaining limitations of the claims recite certain methods of organizing human activity. The claims are directed to identifying and forwarding transaction alerts that may indicate suspicious activity like insider trading. This type of method of organizing human activity is a fundamental economic practice because it involves mitigating risk and a commercial interaction such as legal obligations, sales activities or behaviors, and business relations. The claims also recite mental processes. For example, the functions of the raw news filtering module involve observation and evaluation, the functions of the alert discovery module involve evaluation, the functions of the k-means-clustering module involve observation and evaluation, and the functions of the prioritization module involve judgment. Thus, the claims recite an abstract idea.
Step 2A, Prong Two: Is the Abstract Idea Integrated into a Practical Application? (see MPEP 2106.04(d))
No. The claims as a whole merely use a computer as a tool to perform the abstract idea. The computing components (i.e., additional elements that are in bold above) are recited at a high level of generality and are merely invoked as a tool to implement the steps. For example, only a programmed general purpose computing device is needed to implement the claimed process. Simply implementing the abstract idea on a generic computer is not a practical application of the abstract idea. Additionally, there is no improvement to the functioning of a computer or technology. Therefore, the abstract idea is not integrated into a practical application.
Step 2B: Does the Claim Provide an Inventive Concept? (see MPEP 2106.05)
No. As discussed with respect to Step 2A, Prong 2, the additional elements in the claims, both individually and in combination, amount to no more than tools to perform the abstract idea. Merely performing the abstract idea using a computer cannot provide an inventive concept. Therefore, the claims do not provide an inventive concept.
As such, the claims are not patent eligible.
Relevant Prior Art
The following references are relevant to Applicant’s invention:
Butvinik, U.S. Patent Application Publication Number 2021/0256538 A1. This reference teaches clustering of financial data.
Katzenelson et al., U.S. Patent Application Publication Number 2021/0241072 A1. This reference teaches a clustering module. See paragraph 0036.
Soceanu et al., U.S. Patent Application Publication Number 2018/0329977 A1. This reference teaches K-means clustering (see paragraph 0066) and clustering data to identify a level of volatility indicating insider trading (see paragraph 0026).
Smith, U.S. Patent Application Publication Number 2016/0048914 A1. This reference teaches trade surveillance and monitoring.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/ELIZABETH H ROSEN/Primary Examiner, 3693
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