Prosecution Insights
Last updated: October 02, 2026
Application No. 19/222,381

METHOD AND SYSTEM FOR REAL-TIME SCAM DETECTION USING MACHINE LEARNING TECHNIQUES

Non-Final OA §102§103
Filed
May 29, 2025
Priority
Jun 21, 2024 — IN 202411047781
Examiner
POE, KEVIN T
Art Unit
3692
Tech Center
3600 — Transportation & Electronic Commerce
Assignee
JPMorgan Chase Bank, N.A.
OA Round
1 (Non-Final)
39%
Grant Probability
At Risk
1-2
OA Rounds
2y 10m
Est. Remaining
56%
With Interview

Examiner Intelligence

Grants only 39% of cases
39%
Career Allowance Rate
208 granted / 528 resolved
-12.6% vs TC avg
Strong +16% interview lift
Without
With
+16.4%
Interview Lift
resolved cases with interview
Typical timeline
4y 2m
Avg Prosecution
42 currently pending
Career history
592
Total Applications
across all art units

Statute-Specific Performance

§101
36.8%
-3.2% vs TC avg
§103
33.8%
-6.2% vs TC avg
§102
11.0%
-29.0% vs TC avg
§112
14.8%
-25.2% vs TC avg
Black line = Tech Center average estimate • Based on career data from 528 resolved cases

Office Action

§102 §103
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 . This office action is in response to applicant's communication of May 29, 2025. The rejections are stated below. Claims 1-20 are pending and have been examined. Claim Rejections – 35 USC 102 The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the rejections under this section made in this Office action. A person shall be entitled to a patent unless - (a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention. Claims 1, 8-11, and 18-19 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Taneja et al. [US Pub No. 2024/0420146 A1]. Regarding claim 1, Taneja discloses a method for performing real-time fraud detection by proactively identifying fraudulent activity before executing a transaction, the method being implemented by at least one processor, the method comprising: receiving, from a user, first information that relates to a proposed transaction (0012-0013); providing, as an input to a first machine learning (ML) model, the first information (0009, 0103, claim 7); using the first ML model to generate a first output that relates to potentially fraudulent activity associated with the first information (0009, 0012-0013); generating, based on the first output, an alert message that includes second information that relates to notifying the user about the potentially fraudulent activity (0015, 0112); and transmitting, to the user, the alert message (0010, 0012 and 112). Claims 11 and 19 are rejected for the same reasons as claim 1 because each claim recites the same substantive limitations in different statutory categories without adding patentably distinct subject matter. Regarding claims 8 and 18, Taneja discloses wherein the first information includes at least one from among a name of the user, a geographical address of the user, an email address of the user, a telephone number of the user, a proposed date for the proposed transaction, a proposed time of execution for the proposed transaction, an amount of money to be transferred in the proposed transaction, and a recipient of the money to be transferred (0035). Regarding claim 9, Taneja discloses wherein the first ML model is initially trained by using first historical information that relates to previously executed transactions and second historical information that relates to scams and fraudulent activity (0042 and 0045). Regarding claim 10, Taneja discloses further comprising updating a training of the first ML model by using additional information that relates to recently executed transactions that have been executed after the initial training of the ML model is completed (0099). Claim Rejections - 35 USC § 103 The following is a quotation of 35 U.S.C. 103(a) which forms the basis for all obviousness rejections set forth in this Office action: (a) A patent may not be obtained though the invention is not identically disclosed or described as set forth in section 102 of this title, if the differences between the subject matter sought to be patented and the prior art are such that the subject matter as a whole would have been obvious at the time the invention was made to a person having ordinary skill in the art to which said subject matter pertains. Patentability shall not be negatived by the manner in which the invention was made. Claims 2, 12, and 20 are rejected under 35 U.S.C. 103(a) as being unpatentable over Taneja et al. [US Pub No. 2024/0420146 A1] in view of Godfrey et al. [US Pub No. 2020/0279192 A1]. Regarding claims 2, 12, and 20, Taneja does not disclose however Godfrey teaches discloses wherein the first output includes a first score that relates to a likelihood that the first information is associated with actual fraudulent activity, and wherein the score falls in a range of between zero (0) and ten (10) (0045-0046, 0051, 0053). Before the effective filing, date it would have been obvious to a person of ordinary skill in the art to modify the disclosure of Taneja to include the teachings of Godfrey. The rationale to combine the teachings because a range of 0 to 10 would simplify the outputs to smaller range. Claims 3, and 13 are rejected under 35 U.S.C. 103(a) as being unpatentable over Taneja et al. [US Pub No. 2024/0420146 A1] in view of Kolchin [US Pub No. 2024/0202687 A1]. Regarding claims 3 and 13, Taneja does not disclose however Kolchin teaches further comprising: providing, as an input to a second ML model that is a large language model (LLM), the first information and the alert message; and using the second ML model to generate a second output that includes third information that relates to educating the user about the potentially fraudulent activity (0006-0007, 0010-0011, 0284). Before the effective filing, date it would have been obvious to a person of ordinary skill in the art to modify the disclosure of Taneja to include the teachings of Kolchin. The rationale to combine the teachings is both address the same problem of fraud detection. Claims 4 and 14 are rejected under 35 U.S.C. 103(a) as being unpatentable over Taneja et al. [US Pub No. 2024/0420146 A1] in view of Kolchin [US Pub No. 2024/0202687 A1] and further in view of Perrie “Scammers impersonate Aussie dog breeder in new ‘money muling’ ploy”. Regarding claims 4 and 14, Taneja does not disclose however Perrie teaches wherein the third information includes information that relates to at least one from among an online puppy scam, an animal sale scam, a merchandise and services scam, a fake property for sale scam, a fake investment scam, a company impersonator scam, a government agency impersonator scam, and a bank impersonator scam (Perrie’s full disclosure). Before the effective filing, date it would have been obvious to a person of ordinary skill in the art to modify the disclosure of Taneja to include the teachings of Perrie. The rationale to combine the teachings is using known scam categories to populate educational content in a fraud alert system would have been obvious to a person of ordinary skill in the art as a routine application of existing alert generation technology. Claims 5, 7, 15, and 17 are rejected under 35 U.S.C. 103(a) as being unpatentable over Taneja et al. [US Pub No. 2024/0420146 A1] in view of Kolchin [US Pub No. 2024/0202687 A1] and further in view of Lim Kwang [WO 2011119976 A1]. Regarding claims 5 and 15, Taneja does not, however Lim Kwang discloses wherein the third information includes information that relates to prompting the user to provide an input relating to a reason for sending a payment in connection with the proposed transaction (0024). Before the effective filing, date it would have been obvious to a person of ordinary skill in the art to modify the disclosure of Taneja to include the teachings of Lim Kwang. The rationale to combine the teachings to predict potential future fraud and to identify locations, groups of similar users, types of merchants, or other patterns which may predict potential future fraud which informs whether a transaction should proceed. Regarding claims 7 and 17, Taneja does not, however Lim Kwang discloses wherein the third information includes information that relates to prompting the user to provide an input relating to one from among proceeding with sending a payment in connection with the proposed transaction and not proceeding with sending the payment in connection with the proposed transaction (0024). Before the effective filing, date it would have been obvious to a person of ordinary skill in the art to modify the disclosure of Taneja to include the teachings of Lim Kwang. The rationale to combine the teachings to predict potential future fraud and to identify locations, groups of similar users, types of merchants, or other patterns which may predict potential future fraud which informs whether a transaction should proceed. Claims 6 and 16 are rejected under 35 U.S.C. 103(a) as being unpatentable over Taneja et al. [US Pub No. 2024/0420146 A1] in view of Kolchin [US Pub No. 2024/0202687 A1], Lim Kwang [WO 2011119976 A1] and further in view of Kumar et al. [US Pub No. 2014/0310160 A1]. Regarding claims 6 and 16, neither Taneja, Kolchin, nor Lim Kwang teach however Kumar discloses wherein the third information further includes a plurality of user-selectable candidate explanations for the sending of the payment. However, providing user-selectable candidate explanations was a well-known user interface technique in fraud detection systems before the priority date (Abstract). Before the effective filing, date it would have been obvious to a person of ordinary skill in the art to modify the disclosure of Taneja to include the teachings of Kumar. The rationale to combine the teachings is a benefit form incorporating the user-selectable option interface to improve user engagement and data collection. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to KEVIN T POE whose telephone number is (571)272-9789. The examiner can normally be reached on Monday-Friday 9:30 am through 6pm EST. 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, Ryan Donlon can be reached on 571-270-3602. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see https://ppair-my.uspto.gov/pair/PrivatePair. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /K.T.P/Examiner, Art Unit 3692 /KEVIN T POE/ /RYAN D DONLON/Supervisory Patent Examiner, Art Unit 3692 August 11, 2026
Read full office action

Prosecution Timeline

May 29, 2025
Application Filed
May 25, 2026
Non-Final Rejection (signed) — §102, §103
Aug 18, 2026
Non-Final Rejection mailed — §102, §103 (current)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

1-2
Expected OA Rounds
39%
Grant Probability
56%
With Interview (+16.4%)
4y 2m (~2y 10m remaining)
Median Time to Grant
Low
PTA Risk
Based on 528 resolved cases by this examiner. Grant probability derived from career allowance rate.

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