DETAILED ACTION
Notice of 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 first amendment to non-final filed on March 26, 2026.
Claims 1, 10 19, and 20 have been amended and are hereby entered.
Claims 21–23 have been added.
Claims 1–23 are currently pending and have been examined.
This action is made FINAL.
Response to Amendment
The amendment filed March 26, 2026 has been entered. Claims 1–23 remain pending in the application. Applicant’s amendments to the claims have overcome each and every objection and 112(b) rejection previously set forth in the Non-Final Office Action mailed March 12, 2026.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
Claims 1–20 are rejected under 35 U.S.C. 112(a) as failing to comply with the written description requirement. The claims contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, at the time the application was filed, had possession of the claimed invention.
For claim 1, a conversation analysis engine on an associate’s device with an AI/ML engine is discussed in the original disclosure in specification paragraphs 30, 34, 112, 114, and 116. The disclosure fails, however, to set forth that this is without requiring network transmission of audio during the live interaction. Claiming that this is without requiring network transmission of audio during the live interaction must therefore be cancelled for the claims. Claims 2–9 are also rejected due to their dependency on claim 1.
For claim 10, a conversation analysis engine on an associate’s device with an AI/ML engine is discussed in the original disclosure in specification paragraphs 30, 34, 112, 114, and 116. The disclosure fails, however, to set forth that this is without requiring network transmission of audio during the live interaction. Claiming that this is without requiring network transmission of audio during the live interaction must therefore be cancelled for the claims. Claims 11–18 are also rejected due to their dependency on claim 10.
For claim 19, a conversation analysis engine on an associate’s device with an AI/ML engine is discussed in the original disclosure in specification paragraphs 30, 34, 112, 114, and 116. The disclosure fails, however, to set forth that this is without requiring network transmission of audio during the live interaction. Claiming that this is without requiring network transmission of audio during the live interaction must therefore be cancelled for the claims. Claim 20 is also rejected due to its dependency on claim 19.
Claim Rejections - 35 USC § 101
The following is a quotation of 35 U.S.C. 101:
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 claimed invention is directed to an abstract idea without significantly more.
First of all, claims must be directed to one or more of the following statutory categories: a process, a machine, a manufacture, or a composition of matter. Claims 1–9, 19, and 20 are directed to a process (“An information-security method”), and claims 10–18 are directed to a machine (“An information-security system”). Thus, claims 1–20 satisfy Step One because they are all within one of the four statutory categories of eligible subject matter.
Claims 1–20, however, are directed to an abstract idea without significantly more. For claim 1, the specific limitations that recite an abstract idea are:
entering a customer’s application details . . ., wherein the application details include personal identification information, account numbers, transaction requests, to initiate a fraud detection process;
analyzing application data . . . to identify inconsistencies, falsified information, and unusual requests that might indicate potential fraud, by comparing the application data against a database of legitimate and fraudulent transactions to detect patterns such as mismatched information, unusually large transactions, and requests that deviate from customer typical banking behavior, ensuring comprehensive scrutiny of the application data;
simultaneously running a real-time conversation analysis . . . to monitor live conversation between a bank associate and a customer for signs of deceit or fraudulent intent . . .;
converting spoken dialogue between the bank associate and the customer into text . . ., wherein . . . performs real-time transcription of the conversation to facilitate detailed examination of verbal interactions;
analyzing conversation text . . . to detect suspicious speech patterns, hesitations, inconsistencies in a story, or the use of high-pressure tactics, and identifying keywords and phrases commonly associated with fraudulent activities, including urgent requests for immediate action and reluctance to provide certain information, thereby enhancing the ability to identify potential fraud through linguistic analysis;
combining the analysis results from both the application data and the conversation to create a comprehensive risk assessment, wherein dual analysis ensures that both verbal and non-verbal cues are considered to provide a holistic view of the potential fraud, enhancing accuracy and reliability of a fraud detection system;
triggering an alert if a high probability of fraud is detected, wherein the alert is sent to the bank associate, security personnel, and other relevant individuals within a bank and wherein the alert includes a detailed fraud analysis report summarizing detected inconsistencies in the application data, suspicious speech patterns identified in the conversation, and any relevant historical customer data, and includes detailed information about reasons for suspicion to help staff make informed decisions about how to proceed, ensuring timely and effective response to potential fraud;
empowering associates to take immediate action based on the alert to prevent fraudulent transactions, including verifying additional details with the customer, consulting with security personnel, or denying the transaction if necessary, thereby mitigating the risk of fraud and protecting both the bank and the customer from potential financial losses, and enhancing overall security of banking operations;
continuously updating the system with new data and threat patterns to enhance detection capabilities . . ., improving its accuracy and detection capabilities over time through a continuous learning process that allows the system to adapt to new fraud tactics, ensuring the system remains effective against evolving fraud techniques;
monitoring subsequent activities on the account if a transaction is flagged but allowed to proceed, including tracking movement of funds, monitoring for unusual withdrawals, and analyzing further interactions with the bank, and alerting a security team if any additional suspicious activities are detected to ensure ongoing protection against fraud, thereby providing a multi-layered defense mechanism that extends beyond initial transaction to safeguard the customer’s account continuously; and
identifying, . . . customers who may be vulnerable to manipulation or coercion by analyzing speech patterns and behavior to flag situations where a customer appears to be under duress or is being influenced by a third party.
The claims, therefore, recite detecting and mitigating fraud for a transaction, which is the abstract idea of certain methods of organizing human activity because they recite a commercial interaction and the fundamental economic practice of mitigating risk. The claims also recite transcribing and analyzing conversations, which is the abstract idea of mental processes because it involves observations and evaluations that can be performed by the human mind.
The judicial exception recited above is not integrated into a practical application. The additional elements of the claims are various generic technologies and computer components to implement this abstract idea (“artificial intelligence and machine learning (AI/ML) engine”, “conversation analysis engine”, “associate device”, “advanced speech recognition algorithms”, “supervised learning techniques”, “customer relationship management (CRM) system”, “encrypted communication channels”, “data input module”, “speech analysis module”, “risk assessment module”, “alert generation module”, “action module”, “continuous learning module”, “post-transaction monitoring module”, “centralized database”, “natural language processing (NLP)”, “end-to-end encryption”, and “secure messaging protocols”). The claims also recite “wherein the AI/ML engine is specifically trained”, “wherein the real-time conversation analysis engine operates locally on the associate device during an in-person transaction at a bank branch and runs simultaneously with the AI/ML engine analysis of the application data without requiring network transmission of audio during the live interaction”, and “wherein the AI/ML engine learns from each interaction”. These additional elements are not integrated into a practical application because the invention merely applies the abstract idea to generic computer technology, using the computer to determine fraudulent activity and modify a transaction. Because the invention is using the computer simply as a tool to perform the abstract idea on, the judicial exception is not integrated into a practical application.
Finally, the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, as discussed above, the additional elements in combination are at a high level of generality such that they amount to no more than mere instructions to apply the abstract idea using generic components. Because merely “applying” the exception using generic computer components cannot provide an inventive concept, the additional elements do not recite significantly more than the judicial exception. Thus, claim 1 is not patent eligible.
Independent claims 10 and 19 are rejected as ineligible subject matter under 35 U.S.C. 101 for substantially the same reasons as independent method claim 1. There are no additional elements recited in these claims other than the generic technology and computer parts discussed above (“AI/ML engine”, “conversation analysis engine”, “associate device”, “advanced speech recognition algorithms”, “data input module”, “speech analysis module”, “risk assessment module”, “alert generation module”, “action module”, “continuous learning module”, “post-transaction monitoring module”). The only differences are that the steps of claim 1 are performed by a system in claim 10 and implemented by a broader method in claim 19. Thus, because the same analysis should be used for all categories of claims, claims 10 and 19 are also not patent eligible. See Alice Corp. Pty. Ltd. v. CLS Bank Int’l, 134 S. Ct. 2347, 2354 (2014).
Dependent claims 2–9, 11–18, and 20 have been given the full two part analysis, analyzing the additional limitations both individually and in combination. The dependent claims, when analyzed individually and in combination, are also held to be patent ineligible under 35 U.S.C. 101.
For claims 2, 5, 6, 11, 14, and 15, the additional recited limitations of these claims merely further narrow the abstract idea discussed above. These dependent claims only narrow the fraud detection recited in claims 1 and 10 by further specifying how the detection is improved—“uses supervised learning techniques trained on a dataset comprising known legitimate and fraudulent transactions”, “logs all alerts and actions taken by the bank associates for audit and review purposes”, and “feedback from bank associates on the effectiveness of the fraud detection and prevention measures”. The limitations of these claims fail to integrate the abstract idea into a practical application because these claims do not introduce additional elements other than the generic components discussed above (“AI/ML”). These claims do recite supervised learning techniques, but again, this is also merely being used as a tool to detect the fraud. These dependent claims, therefore, also amount to merely using a computer, in its ordinary capacity, as a tool to perform the abstract idea. Finally, the additional recited limitations of these dependent claims fail to establish that the claims provide an inventive concept because claims that merely use a computer, in its ordinary capacity, as a tool to perform the abstract idea cannot provide an inventive concept.
For claims 3 and 12, the additional recited limitations of these claims merely further narrow the abstract idea discussed above. These dependent claims only narrow the fraud detection recited in claims 1 and 10 by further specifying how the conversation fraud is detected—“speech patterns associated with stress or nervousness”. The limitations of these claims fail to integrate the abstract idea into a practical application because these claims do not introduce additional elements other than the generic components discussed above (“conversation analysis engine”). These dependent claims, therefore, also amount to merely using a computer, in its ordinary capacity, as a tool to perform the abstract idea. Finally, the additional recited limitations of these dependent claims fail to establish that the claims provide an inventive concept because claims that merely use a computer, in its ordinary capacity, as a tool to perform the abstract idea cannot provide an inventive concept.
For claims 4, 7, 13, and 16, the additional recited limitations of these claims merely further narrow the abstract idea discussed above. These dependent claims only narrow the fraud detection recited in claims 1 and 10 by further specifying the alert presented—“includes suggested actions” and “unified view of customer interactions and potential fraud alerts”. The limitations of these claims fail to integrate the abstract idea into a practical application because these claims do not introduce additional elements other than the generic components discussed above (“alert generation module”). These claims do recite a customer relationship management (CRM) system, but again, this is also merely being used as a tool to present information to a user. These dependent claims, therefore, also amount to merely using a computer, in its ordinary capacity, as a tool to perform the abstract idea. Finally, the additional recited limitations of these dependent claims fail to establish that the claims provide an inventive concept because claims that merely use a computer, in its ordinary capacity, as a tool to perform the abstract idea cannot provide an inventive concept.
For claims 8, 9, 17, and 18, the additional recited limitations of these claims merely further narrow the abstract idea discussed above. These dependent claims only narrow the fraud detection recited in claims 1 and 10 by further specifying how information is accessed—“multi-factor authentication” and “encrypted communication channels”. The limitations of these claims fail to integrate the abstract idea into a practical application because these claims do not introduce additional elements other than the generic components discussed above. These claims do recite encrypted communication channels, but again, these are also merely being used as a tool to communicate information. These dependent claims, therefore, also amount to merely using a computer, in its ordinary capacity, as a tool to perform the abstract idea. Finally, the additional recited limitations of these dependent claims fail to establish that the claims provide an inventive concept because claims that merely use a computer, in its ordinary capacity, as a tool to perform the abstract idea cannot provide an inventive concept.
For claim 20, the additional recited limitations of this claim merely further narrow the abstract idea discussed above. This dependent claim only narrows the fraud detection recited in claim 19 by further specifying the data aggregated—“from multiple branches and external sources”; how the detection is improved—“feedback from bank associates and security personnel”; how the conversation fraud is detected—“utilizing advanced natural language processing (NLP) techniques . . . to detect nuanced linguistic indicators of deception”; the alert presented—“detailed fraud analysis report”; how information is communicated—“secure communication channels . . . utilizing end-to-end encryption”; and how the fraud is mitigated—“conducting periodic training sessions for bank associates”, “dedicated fraud investigation unit . . . collaborate with external law enforcement agencies”, and “deploying automated fraud prevention measures”. The limitations of this claim fail to integrate the abstract idea into a practical application because this claim does not introduce additional elements other than the generic components discussed above (“AI/ML engine” and “conversation analysis engine”). This claim does recite a centralized database, natural language processing (NLP), end-to-end encryption, and secure messaging protocols, but again, these are also merely being used as tools to implement the abstract ideas above. The centralized database is merely being used as a tool to store data, the NLP techniques are merely being used as a tool to detect fraud, and the encryption and secure messaging are merely being used as tools to communicate information more securely. This dependent claim, therefore, also amounts to merely using a computer, in its ordinary capacity, as a tool to perform the abstract idea. Finally, the additional recited limitations of this dependent claim fails to establish that the claim provides an inventive concept because claims that merely use a computer, in its ordinary capacity, as a tool to perform the abstract idea cannot provide an inventive concept.
Response to Arguments
Claim Rejections Under 35 U.S.C. § 101
Applicant’s arguments filed on March 26, 2026 have been fully considered but they are not persuasive.
First, Applicant argues that the claims are not directed to an abstract idea because they recite a dual AI/ML and conversation analysis engine analyzing live speech, which cannot be performed in real-time. Applicant explains that bank associates cannot match analytical capabilities of these advanced systems in identifying subtle indicators of fraud. The claims, however, do still recite analyzing conversations and mitigating fraud, even if they further apply these systems to do so. The use of conversation analysis and machine learning systems in the claimed invention is an implementation of this abstract idea through the use of technology, and is therefore addressed under the next steps of the analysis. Thus, claims 1–23 do recite an abstract idea.
Next, Applicant argues that the claims are integrated into a practical application because they provide specific technical improvements to a specific technical problem. Applicant explains that current bank systems cannot analyze the complexities of in-person interactions because they lack real-time analysis tools. The claims therefore provide a conversation analysis engine on a local device, a simultaneously combined AI/ML engine analysis, and an alert with a detailed fraud analysis report. Applicant argues that the claimed invention here is similar to the claim in Example 47 of the 2024 Subject Matter Eligibility Examples, which was integrated into a practical application because it recited an improvement to network security. See 2024 AI Examples 47 through 49, at p. 10, https://www.uspto.gov/sites/default/files/documents/2024-AI-SMEUpdateExamples47-49.pdf (effective July 17, 2024). These improvements cited by Applicant, however, are merely improvements to the bank fraud analysis. Applicant explains that the conversation analysis and machine learning engines perform analyses that cannot be performed by a human, but the claims do not further expand on how the machine learning or conversational analyses are performed. The claims are instead merely making the fraud detection analysis more efficient, improving the abstract ideas themselves, rather than improving the technology itself in any way. In contrast, claim 3 of Example 47 was determined to be patent eligible because the claim was directed to detecting sources associated with malicious network packets and dropping the network packets in real time. See id. at 12–13. The claims here, on the other hand, as discussed above, are directed to merely applying the machine learning to improve the abstract idea. Thus, claims 1–23 do not include additional elements sufficient to integrate the claims into a practical application.
Finally, Applicant argues that the technical features discussed above recite significantly more than the judicial exception because they are not well-understood, routine, or conventional. As discussed above, however, these additional elements are merely applied to the judicial exception, rather than the claims reciting any technological improvement. And, merely applying an abstract idea to a computer, as established in Step 2A Prong Two, cannot provide an inventive concept, as required under Step 2B. See MPEP 2106.05(f). Thus, claims 1–23 do not include additional elements sufficient to recite significantly more than the judicial exception.
Claim Rejections Under 35 U.S.C. § 103
The rejections of claims 1 under 35 U.S.C. 103 have been withdrawn in light of Applicant’s amendments and arguments. The following limitations of claim 1 are not taught by the previously cited prior art:
simultaneously running a real-time conversation analysis engine on an associate device, wherein the conversation analysis engine is equipped with advanced speech recognition algorithms to monitor live conversation between a bank associate and a customer for signs of deceit or fraudulent intent and wherein the real-time conversation analysis engine operates locally on the associate device during an in-person transaction at a bank branch and runs simultaneously with the AI/ML engine analysis of the application data without requiring network transmission of audio during the live interaction.
The prior art reference of record that is most closely related to the claim limitation recited above is Laird et al., U.S. Patent App. No. 2021/0407514 (“Laird”), which discusses analyzing conversation for deception. Laird, however, discusses determining fraud from conversation deception, but does not disclose running this analysis simultaneously with an AI engine analysis of application data without requiring network transmission of audio during the live interaction, as in the claimed invention. And, no reference could be found for determining fraud in this way, nor would it necessarily have been obvious to combine such a reference with the existing references, or to combine so many references, to disclose the claimed limitations. Independent claims 10 and 19 include substantially the same features as claim 1. Accordingly, the prior rejections of claims 1–20 under 35 U.S.C. 103 have been withdrawn.
Prior Art Not Relied Upon
The prior art made of record and not relied upon is considered pertinent to Applicant’s disclosure. Those prior art references are as follows:
Kramme et al., U.S. Patent App. No. 2023/0316285, discloses determining fraud through machine learning.
Cousins, U.S. Patent App. No. 2022/0245639, discloses fraud detection through natural language processing.
Motaharian et al., U.S. Patent App. No. 2020/0320619, discloses detecting and preventing fraud using machine learning models.
Conclusion
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.
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/DIVESH PATEL/Examiner, Art Unit 3696
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