DETAILED ACTION
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 10/17/25 has been entered.
Status of Claims
This action is in reply to RCE, amendment and response filed on 10/17/25. Claims 1, 10 and 19 were amended. Claims 8 and 17 were cancelled. 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.
Applicant essentially argues that the amended claims do not recite an abstract idea.
The Examiner disagrees.
The Applicant’s arguments are moot because the RCE filed and the claims that were amended substantively. Per example, the amended claim 1 recites “executing, by the server using at least one of the attribute or data associated with the secure loan dataset, 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 attribute for the user based on learned correlations” which includes an additional element necessitating reconsideration of the claims.
As such, an updated rejection is provided that addresses the amended claims.
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.
In the instant case, claims 1-7 and 9 are directed to a process, claims 10-16 and 18 are directed to a machine and claims 19-20 are directed to another machine.
When analyzed under prong one of step 2A, see MPEP 2106.04(a), claim 1 recites loan product determination which is a form of organizing human activity (e.g. commercial or legal interaction) and an abstract idea, see MPEP 2106.04(a)(2)(II). Specifically, the claim recites:
receiving, …, an indication of …;
retrieving, …, an identifier of a user operating …;
retrieving, …, a secure loan dataset for the user, the secure loan dataset comprising at least a triggering employment status attribute … a transaction associated with the secure loan dataset;
…, … using at least one of the attribute or data associated with the secure loan dataset, a … model to determine a … product attribute for the user based on learned correlations;
…
Additionally, “[executing …] a […] model […] to determine a […] product attribute for the user based on learned correlations” and “[routing … to an agent computing device] identified from an agent mapping table that associates agents with specific […] product attributes output by the […] model, […]” represents the mathematical concept of generating and using a loan product model, and it has been held that merely adding one abstract idea (math) to another abstract idea (loan product determination) does not provide a practical application (MPEP 2106.04 II 2, RecogniCorp, LLC v. Nintendo Co., 855 F.3d 1322, 1327, 122 USPQ2d 1377 (Fed. Cir. 2017)).
When analyzed under prong 2 of step 2A, see MPEP 2106.04(d), claim 1 includes additional elements. The additional elements are:
“a server”,
“a first electronic communication session with a user computing device”,
“… a triggering employment status attribute that causes execution of a transaction …,
“executing, by the server […], a machine learning predictive computer model having been trained on historical secure loan datasets, employment status changes, and prior transaction outcomes […] digital […]”.
“routing, by the server, the first electronic communication session to an agent computing device identified from an agent mapping table that associates agents with specific digital product attributes output by the machine learning predictive model, thereby establishing a second electronic communication session between the user computing device and the agent computing device operated by the agent”.
The additional elements represent use of a computer as a tool to perform the abstract idea, see MPEP 2106.05(f), and/or do no more than link the use of the abstract idea to a particular technological environment or field of use, see MPEP 2106.05(h), and therefore, do not integrate loan product determination by generating and using a loan product model into a practical application, see MPEP 2106.04(d).
With respect to “a triggering employment status attribute that causes execution of a transaction”, the claim lacks technological details on what “a triggering employment status attribute that causes execution of a transaction” comprises, and as a result is no more than “apply it” (MPEP 2106.05(f)(1)).
With respect to “executing, by the server […], a machine learning predictive computer model having been trained on historical secure loan datasets, employment status changes, and prior transaction outcomes”, the claims lacks technological details on what “executing, …, a machine learning predictive computer model having been trained on historical secure loan datasets, employment status changes, and prior transaction outcomes” comprises, and as a result is no more than “apply it” (MPEP 2106.05(f)(1)).
With respect to “routing, by the server, the first electronic communication session to an agent computing device identified from an agent mapping table that associates agents with specific digital product attributes output by the machine learning predictive model, thereby establishing a second electronic communication session between the user computing device and the agent computing device operated by the agent”, this is no more than transmitting information such as the first communication session to an agent and it has been held that using a computer to perform an economic or other task does not provide a practical application (MPEP 2106.05(f)(2)). Furthermore, the claim lacks technological details on what “routing, …, the first electronic communication session to an agent computing device identified from an agent mapping table that associates agents with specific digital product attributes output by the machine learning predictive model” comprises, and as a result is no more than “apply it” (MPEP 2106.05(f)(1)).
With respect to “establishing a second electronic communication session between the user computing device and the agent computing device operated by the agent”, this is no more than transmitting information such as the second communication session and it has been held that using a computer to perform an economic or other task does not provide a practical application (MPEP 2106.05(f)(2)).
When analyzed under step 2B, see MPEP 2106.05, the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception, itself because the additional elements do no more than automate or implement loan product determination by generating and using a loan product model and do not improve computer functionality or improve another technology or related technical field, see MPEP 2106.05(a).
As to claim 10, the claim also recites the abstract idea of loan product determination by generating and using a loan product model, see MPEP 2106.04(a)(2)(I & II). The claim recites the additional elements of:
“a system, […] the system comprising”,
“a non-transitory machine-readable memory configured to store a set of instructions that when executed, cause a processor to”,
“a first electronic communication session with a user computing device”,
“[…] a triggering employment status attribute that causes execution of a transaction …”
“execute, […] a machine learning predictive computer model having been trained on historical secure loan datasets, employment status changes, and prior transaction outcomes […] digital […]”.
“route the first electronic communication session to an agent computing device identified from an agent mapping table that associates agents with specific digital product attributes output by the machine learning predictive model, thereby establishing a second electronic communication session between the user computing device and the agent computing device operated by the agent”.
The additional elements represent use of a computer as a tool to perform the abstract idea, see MPEP 2106.05(f), and/or do no more than link the use of the abstract idea to a particular technological environment or field of use, see MPEP 2106.05(h), and therefore, do not integrate loan product determination by generating and using a loan product model into a practical application, see MPEP 2106.04(d).
With respect to “a triggering employment status attribute that causes execution of a transaction”, the claim lacks technological details on what “a triggering employment status attribute that causes execution of a transaction” comprises, and as a result is no more than “apply it” (MPEP 2106.05(f)(1)).
With respect to “execute, […] a machine learning predictive computer model having been trained on historical secure loan datasets, employment status changes, and prior transaction outcomes”, the claims technological lacks details on what “execute, […] a machine learning predictive computer model having been trained on historical secure loan datasets, employment status changes, and prior transaction outcomes” comprises, and as a result is no more than “apply it” (MPEP 2106.05(f)(1)).
With respect to “route the first electronic communication session to an agent computing device identified from an agent mapping table that associates agents with specific digital product attributes output by the machine learning predictive model”, this is no more than transmitting information such as the first communication session and it has been held that using a computer to perform an economic or other task does not provide a practical application (MPEP 2106.05(f)(2)). Furthermore, the claim lacks technological details on what “route the first electronic communication session to an agent computing device identified from an agent mapping table that associates agents with specific digital product attributes output by the machine learning predictive model” comprises, and as a result is no more than “apply it” (MPEP 2106.05(f)(1)).
With respect to “establishing a second electronic communication session between the user computing device and the agent computing device operated by the agent”, this is no more than transmitting information such as the second communication session and it has been held that using a computer to perform an economic or other task does not provide a practical application (MPEP 2106.05(f)(2)).
When analyzed under step 2B, see MPEP 2106.05, the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception, itself because the additional elements do no more than automate or implement loan product determination by generating and using a loan product model and do not improve computer functionality or improve another technology or related technical field, see MPEP 2106.05(a).
As to claim 19, the claim also recites the abstract idea of loan product determination by generating and using a loan product model , see MPEP 2106.04(a)(2)(I & II). The claim recites the additional elements of:
“a system, […] the system comprising”,
”an agent computing device operated by an agent”,
“a server in communication with the agent computing device, the server configured to”,
“a first electronic communication session with a user computing device”,
“[…] a triggering employment status attribute that causes execution of a transaction […]”,
“execute, […] a machine learning predictive computer model having been trained on historical secure loan datasets, employment status changes, and prior transaction outcomes […] digital […]”,
“route the first electronic communication session to an agent computing device identified from an agent mapping table that associates agents with specific digital product attributes output by the machine learning predictive model, thereby establishing a second electronic communication session between the user computing device and the agent computing device operated by the agent”.
The additional elements represent use of a computer as a tool to perform the abstract idea, see MPEP 2106.05(f), and/or do no more than link the use of the abstract idea to a particular technological environment or field of use, see MPEP 2106.05(h), and therefore, do not integrate loan product determination by generating and using a loan product model into a practical application, see MPEP 2106.04(d).
With respect to “a triggering employment status attribute that causes execution of a transaction”, the claim lacks technological details on what “a triggering employment status attribute that causes execution of a transaction” comprises, and as a result is no more than “apply it” (MPEP 2106.05(f)(1)).
With respect to “execute, […] a machine learning predictive computer model having been trained on historical secure loan datasets, employment status changes, and prior transaction outcomes”, the claim lacks technological details on what “execute, […] a machine learning predictive computer model having been trained on historical secure loan datasets, employment status changes, and prior transaction outcomes” comprises, and as a result is no more than “apply it” (MPEP 2106.05(f)(1)).
With respect to “route the first electronic communication session to an agent computing device identified from an agent mapping table that associates agents with specific digital product attributes output by the machine learning predictive model”, this is no more than transmitting information such as the first communication session and it has been held that using a computer to perform an economic or other task does not provide a practical application (MPEP 2106.05(f)(2)). Furthermore, the claim lacks technological details on what “route the first electronic communication session to an agent computing device identified from an agent mapping table that associates agents with specific digital product attributes output by the machine learning predictive model” comprises, and as a result is no more than “apply it” (MPEP 2106.05(f)(1)).
With respect to “establishing a second electronic communication session between the user computing device and the agent computing device operated by the agent”, this is no more than transmitting information such as the second communication session and it has been held that using a computer to perform an economic or other task does not provide a practical application (MPEP 2106.05(f)(2)).
When analyzed under step 2B, see MPEP 2106.05, the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception, itself because the additional elements do no more than automate or implement loan product determination by generating and using a loan product model and do not improve computer functionality or improve another technology or related technical field, see MPEP 2106.05(a).
Hence, claims 1, 10 and 19 are not patent eligible.
Dependent claims 2, 11 and 20 recite additional elements.
The additional elements of “the first electronic communication session or the second electronic communication session is a telephonic communication session” represent use of a computer as a tool to perform the abstract idea, see MPEP 2106.05(f), and/or do no more than link the use of the abstract idea to a particular technological environment or field of use, see MPEP 2106.05(h), and therefore, do not integrate loan product determination by generating and using a loan product model into a practical application, see MPEP 2106.04(d).
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception, itself because the additional elements do no more than automate or implement loan product determination by generating and using a loan product model and do not improve computer functionality or improve another technology or related technical field, see MPEP 2106.05(a).
Dependent claims 3 and 12 recite additional elements.
The additional elements of “establishing the second electronic communication session comprises routing the telephonic communication session to the agent computing device” represent use of a computer as a tool to perform the abstract idea, see MPEP 2106.05(f), and/or do no more than link the use of the abstract idea to a particular technological environment or field of use, see MPEP 2106.05(h), and therefore, do not integrate loan product determination by generating and using a loan product model into a practical application, see MPEP 2106.04(d).
With respect to the additional element of “establishing the second electronic communication session”, this is no more than transmitting information such as the second communication session and it has been held that using a computer to perform an economic or other task does not provide a practical application (MPEP 2106.05(f)(2)).
With respect to the additional element of “routing the telephonic communication session to the agent computing device”, this is no more than transmitting information such as the telephonic communication session and it has been held that using a computer to perform an economic or other task does not provide a practical application (MPEP 2106.05(f)(2)).
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception, itself because the additional elements do no more than automate or implement loan product determination by generating and using a loan product model and do not improve computer functionality or improve another technology or related technical field, see MPEP 2106.05(a).
Dependent claims 4 and 13 recite “the identifier is a telephone number, media access control address, or internet protocol address”, and therefore, further describes loan product determination by generating and using a loan product model.
Dependent claims 5 and 14 recite additional elements.
The additional elements of “the first electronic communication session or the second electronic communication session is a chat session or a video communication session” represent use of a computer as a tool to perform the abstract idea, see MPEP 2106.05(f), and/or do no more than link the use of the abstract idea to a particular technological environment or field of use, see MPEP 2106.05(h), and therefore, do not integrate loan product determination by generating and using a loan product model into a practical application, see MPEP 2106.04(d).
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception, itself because the additional elements do no more than automate or implement loan product determination by generating and using a loan product model and do not improve computer functionality or improve another technology or related technical field, see MPEP 2106.05(a).
Dependent claims 6 and 15 recite “the … product attribute for the user indicates a subsequent purchase of the user”, and therefore, further describe loan product determination by generating and using a loan product model.
The additional elements of “the digital product attribute” represent use of a computer as a tool to perform the abstract idea, see MPEP 2106.05(f), and/or do no more than link the use of the abstract idea to a particular technological environment or field of use, see MPEP 2106.05(h), and therefore, do not integrate loan product determination by generating and using a loan product model into a practical application, see MPEP 2106.04(d).
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception, itself because the additional elements do no more than automate or implement loan product determination by generating and using a loan product model and do not improve computer functionality or improve another technology or related technical field, see MPEP 2106.05(a).
Dependent claims 7 and 16 recite “the agent is specialized in the subsequent purchase”, and therefore, further describe loan product determination by generating and using a loan product model.
Dependent claims 9 and 18 recite additional elements.
The additional elements of “displaying, by the server on the agent computing device, the digital product attribute for the user” represent use of a computer as a tool to perform the abstract idea, see MPEP 2106.05(f), and/or do no more than link the use of the abstract idea to a particular technological environment or field of use, see MPEP 2106.05(h), and therefore, do not integrate loan product determination by generating and using a loan product model into a practical application, see MPEP 2106.04(d).
With respect to “displaying, by the server on the agent computing device, the digital product attribute for the user”, this is no more than displaying information such as the second communication session and it has been held that using a computer to perform an economic or other task does not provide a practical application (MPEP 2106.05(f)(2)).
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception, itself because the additional elements do no more than automate or implement loan product determination by generating and using a loan product model and do not improve computer functionality or improve another technology or related technical field, see MPEP 2106.05(a).
Conclusion
References made of record, not relied upon, pertinent to Applicant’s disclosure, includes:
US 20050137968 A1 (Mitchell) disclosing internet based marketing and information management for mortgage loans,
US 20130185189 A1 (Stewart) disclosing using online social footprint for affecting lending performance and credit scoring.
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/BROCK E TURK/Examiner, Art Unit 3692 /DAVID P SHARVIN/Primary Examiner, Art Unit 3692