DETAILED ACTION
Status of Claims
This action is in reply to amendment and response filed on 5/4/26. Claims 8 and 17 were cancelled. Claims 1, 10 and 19 were amended. Claims 1-7, 9-16 and 18-20 are pending and examined.
Response to Arguments
101: The Applicant’s amendments and arguments have been fully considered but are not persuasive.
pp. 10. prong one, step 2A,
The Applicant essentially argues that the claims do not recite an abstract idea in the organizing human activity grouping.
The Examiner disagrees.
As stated in the previous rejection and reiterated in the current rejection, at least the following claim limitations recite the abstract idea of selecting a loan agent based on loan context information and providing the loan context information to the selected loan agent:
“retrieve, using the identifier, a secure loan dataset for the user, the secure loan dataset comprising at least a triggering employment status attribute [that causes execution] of a transaction associated with the secure loan dataset and one or more loan-state attributes associated with the transaction”,
“generate a feature vector from the triggering employment status attribute and the one or more loan-state attributes”,
“query an agent mapping table [that maps digital] product classifications …”
generating a feature vector is abstract idea because it amounts to creation of structured loan information from loan context information.
pp. 9, 11-12 prong two, step 2A, step 2B,
The Applicant essentially argues that the claims recite additional elements that integrate the abstract idea into a practical application specifically the additional elements directed to establishing a communication session with a loan officer.
The Examiner disagrees.
executing a machine learning model trained on historical loan information on loan context information based on learned correlations to determine loan product does not integrate the abstract idea into a practical application as it is no more than “apply it” because the claims fail to recite the technological details of how the machine learning predict model is trained based on loan context information, how it is executed using structured loan information and how it is trained based on learned correlations, see MPEP 2106.05(f)(1).
“[query an agent mapping table that] maps digital [product classifications] to agent communication queues or agent computing devices to identify a selected agent communication queue or a selected agent computing device” does not integrate the abstract idea into a practical application as it is no more than “apply it” because it is mere “[u]se of a computer or other machinery in its ordinary capacity for economic or other tasks”, see MPEP 2106.05(f)(2). Furthermore, mapping loan product to agent communication queue does not integrate the abstract idea into a practical application as it is no more than “apply it” because the claims fail to recite the technological details of how the loan product is mapped to the agent communication queue.
“generate a session-context data structure [comprising the] digital [product classification …]”. Generating a session-context data structure from loan classification does not integrate the abstract idea into a practical application as it is no more than “apply it” because the claims fail to recite the technological details of how the session-context data structure is generated from the loan classification.
“route the first electronic communication session to the selected agent communication queue or the selected agent computing device [identified from an the agent mapping table], thereby establishing a second electronic communication session between the user computing device and the agent computing device operated by the agent, wherein the server further transmits the session-context data structure to the selected agent computing device in association with establishment of the second electronic communication session”. Routing a communication session to loan agent computer and sending the loan context information to the agent computer do not integrate the abstract idea into a practical application as they are no more than “apply it” because they are mere “[u]se of a computer or other machinery in its ordinary capacity for economic or other tasks”, see MPEP 2106.05(f)(2).
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 into a practical application, the additional elements do no more than provide mere instructions to apply the abstract idea using “a computer or other machinery in its ordinary capacity for economic or other tasks”, see MPEP 2106.05(f)(2), and/or the claim fails to recite the technological details of “how a solution to a problem is accomplished”, see MPEP 2106.05(f)(1). Therefore, the claim elements when considered separately and in an ordered combination, do not add significantly more than implementing the abstract idea of selecting a loan agent based on loan context information and providing the loan context information to the selected loan agent.
As such, the rejection is maintained and an updated rejection addressing the amended claims is provided.
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 1-7, 9-16 and 18-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. (Step 1) The claims recite a process (claims 1-7 and 9), an apparatus (claims 10-16 and 18), and another apparatus (claims 19-20). For the purposes of this analysis, representative claim 19 is addressed (from claims 1, 10 and 19). (Step 2A, prong 1) Abstract ideas are in bold below, and represent organizing human activity as a method of selecting a loan agent based on loan context information and providing the loan context information to the selected loan agent, as are all a form of commercial or legal interactions and managing personal behavior or relationships or interactions between people.
A system for automated routing of electronic communication sessions between computing devices, the system comprising:
a plurality of agent computing devices; and
a server in communication with the plurality of agent computing devices, the server configured to:
receive an indication of a first electronic communication session with a user computing device;
retrieve an identifier of a user operating the user computing device;
retrieve, using the identifier, a secure loan dataset for the user, the secure loan dataset comprising at least a triggering employment status attribute that causes execution of a transaction associated with the secure loan dataset and one or more loan-state attributes associated with the transaction;
generate a feature vector from the triggering employment status attribute and the one or more loan-state attributes;
execute, using the feature vector, a machine learning predictive model having been trained on historical secure loan datasets, employment status changes, and prior transaction outcomes to determine a digital product classification for the user based on learned correlations; and
query an agent mapping table that maps digital product classifications to agent communication queues or agent computing devices to identify a selected agent communication queue or a selected agent computing device;
generate a session-context data structure comprising the digital product classification and at least a portion of the secure loan dataset; and
route the first electronic communication session to the selected agent communication queue or the selected agent computing device identified from an the agent mapping table, thereby establishing a second electronic communication session between the user computing device and the agent computing device operated by the agent, wherein the server further transmits the session-context data structure to the selected agent computing device in association with establishment of the second electronic communication session.
(Step 2A prong 2) The additional elements are as follows:
“A system for automated routing of electronic communication sessions between computing devices, the system comprising”, “a plurality of agent computing devices”, “a server in communication with the plurality of agent computing devices, the server configured”. These additional elements do not integrate the abstract idea into a practical application as they are no more than “apply it” because they are mere “[u]se of a computer or other machinery in its ordinary capacity for economic or other tasks”, see MPEP 2106.05(f)(2). Furthermore, “automated routing of electronic communication sessions between computing devices” does not integrate the abstract idea into a practical application as it is no more than “apply it” because the claims fail to recite the technological details of how the “electronic communication sessions” are automatically routed “between computing devices”, see MPEP 2106.05(f)(1).
“[receive an indication] of a first electronic communication session with a user computing device”. This additional elements does not integrate the abstract idea into a practical application as it is no more than “apply it” because it is mere “[u]se of a computer or other machinery in its ordinary capacity for economic or other tasks”, see MPEP 2106.05(f)(2).
“[retrieve an identifier of a user] operating the user computing device”. “[a user] operating the user computing device” does not integrate the abstract idea into a practical application as it is no more than “apply it” because it is mere “[u]se of a computer or other machinery in its ordinary capacity for economic or other tasks”, see MPEP 2106.05(f)(2).
“[retrieve … a triggering employment status attribute] that causes execution of [a transaction]”. Information (e.g.: the triggering employment status attribute) causing execution of “a transaction” does not integrate the abstract idea into a practical application as it is no more than “apply it” because the claims fail to recite the technological details of how information causes execution of “a transaction”, see MPEP 2106.05(f)(1).
“execute, using [the feature vector], a machine learning predictive model having been trained [on historical secure loan datasets, …] to determine [a] digital [product classification] for the user based on learned correlations”. Executing, using structured loan information, a machine learning predictive model trained on loan context information based on learned correlations does not integrate the abstract idea into a practical application as it is no more than “apply it” because the claims fail to recite the technological details of how the machine learning predict model is trained based on loan context information, how it is executed using structured loan information and how it is trained based on learned correlations, see MPEP 2106.05(f)(1).
“[query an agent mapping table that] maps digital [product classifications] to agent communication queues or agent computing devices to identify a selected agent communication queue or a selected agent computing device” does not integrate the abstract idea into a practical application as it is no more than “apply it” because it is mere “[u]se of a computer or other machinery in its ordinary capacity for economic or other tasks”, see MPEP 2106.05(f)(2). Furthermore, mapping loan product to agent communication queue does not integrate the abstract idea into a practical application as it is no more than “apply it” because the claims fail to recite the technological details of how the loan product is mapped to the agent communication queue.
“generate a session-context data structure [comprising the] digital [product classification …]”. Generating a session-context data structure from loan classification does not integrate the abstract idea into a practical application as it is no more than “apply it” because the claims fail to recite the technological details of how the session-context data structure is generated from the loan classification.
“route the first electronic communication session to the selected agent communication queue or the selected agent computing device [identified from an the agent mapping table], thereby establishing a second electronic communication session between the user computing device and the agent computing device operated by the agent, wherein the server further transmits the session-context data structure to the selected agent computing device in association with establishment of the second electronic communication session”. Routing a communication session to loan agent computer and sending the loan context information to the agent computer do not integrate the abstract idea into a practical application as they are no more than “apply it” because they are mere “[u]se of a computer or other machinery in its ordinary capacity for economic or other tasks”, see MPEP 2106.05(f)(2).
(Step 2B) 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 into a practical application, the additional elements do no more than provide mere instructions to apply the abstract idea using “a computer or other machinery in its ordinary capacity for economic or other tasks”, see MPEP 2106.05(f)(2), and/or the claim fails to recite the technological details of “how a solution to a problem is accomplished”, see MPEP 2106.05(f)(1). Therefore, the claim elements when considered separately and in an ordered combination, do not add significantly more than implementing the abstract idea of selecting a loan agent based on loan context information and providing the loan context information to the selected loan agent.
Continuing the analysis with dependent claims 2-7, 9, 11-16, 18 and 20, the claims recite additional details which only further narrow the abstract idea and do not add any additional features, alone or in combination, that would provide a practical application or provide significantly more.
Conclusion
Reference made of record, not relied upon, pertinent to Applicant’s disclosure includes:
US 20200273098 A1 (Marr) disclosing Integrating Loan Information and Real Estate Listing that teaches selecting a loan officer and transmitting loan information to the selected officer in para. 10.
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 BROCK E TURK whose telephone number is (571)272-5626. The examiner can normally be reached Monday-Friday 9AM-5PM 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 at 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 published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/BROCK E TURK/Examiner, Art Unit 3692
/RYAN D DONLON/Supervisory Patent Examiner, Art Unit 3692
August 21, 2026
Prosecution Insights