The Toronto-Dominion Bank patent applications on April 10th, 2025
Patent Applications by The Toronto-Dominion Bank on April 10th, 2025
The Toronto-Dominion Bank: 18 patent applications
The Toronto-Dominion Bank has applied for patents in the areas of G06N3/0475 (5), G06Q40/06 (4), G06F40/40 (4), H04L51/02 (3), G06F40/35 (3) G06Q40/06 (4), G06F40/40 (2), G06N3/0475 (2), G06F16/3329 (1), G06N3/045 (1)
With keywords such as: user, device, portfolio, within, receiving, payment, chat, example, via, and data in patent application abstracts.
Patent Applications by The Toronto-Dominion Bank
Inventor(s): Shahzad Mohammed of Ontario CA for the toronto-dominion bank
IPC Code(s): G06F16/332, H04L51/02, H04L67/02, H04L67/30
CPC Code(s): G06F16/3329
Abstract: the present disclosure relates to computer-implemented methods, software, and systems for transferring contexts from a generic chatbot to a domain-specific chatbot. in one example, a registration at a first conversational interface is received that identifies at least one endpoint associated with a first entity that is separate from the first conversational interface and is associated with a domain-specific conversational interface. the first conversational interface can interact with a user through a natural language search interaction. the interface can identify at least one response associated with one of the at least one endpoints associated with the first entity, and can provide the response and an interactive response associated with initiating a transfer of the interaction from the first conversational interface to a domain-specific conversational interface of the first entity. once accepted, the interaction is transferred to the first entity and its domain-specific conversational interface.
Inventor(s): Shahriar Taheri of Newmarket CA for the toronto-dominion bank
IPC Code(s): G06F40/40, G06F40/35
CPC Code(s): G06F40/40
Abstract: an example operation may include one or more of receiving a sequence of inputs from a user during a conversation between the user and a chatbot within a chat window of a software application, executing a large language model (llm) on each input from the user to determine a next prompt to output via the chatbot, respectively, wherein each execution of the llm includes a new chat input from the user and a most-recent state of the conversation between the user and the chatbot within the chat window, and displaying the next prompt within a chat window on a user device.
Inventor(s): Shahriar Taheri of Newmarket CA for the toronto-dominion bank
IPC Code(s): G06F40/40, G06F40/35, G06N3/091
CPC Code(s): G06F40/40
Abstract: an example operation may include one or more of training a large language model (llm) to learn credit card data via execution of the llm on content from one or more credit card documents, executing the llm to generate a sequence of prompts which are output to a user via a chatbot within a chat window of a software application, receiving responses to the sequence of prompts for the user via the chat window of the software application, and retraining the llm model to further learn credit card data via execution of the llm on a combination of the sequence of prompts and the received responses.
Inventor(s): Bharathvaj Devarajan of Ontario CA for the toronto-dominion bank, Sagar Purkayasth of Calgary CA for the toronto-dominion bank, Wenjia Zhu of Vancouver CA for the toronto-dominion bank
IPC Code(s): G06N3/045, G06N3/091, G06Q30/0204
CPC Code(s): G06N3/045
Abstract: an example method includes receiving a set of features representing attributes for a user and receiving data for multiple digital campaigns. the set of features can be processed using a propensity machine learning model to determine whether the first user is expected to perform an affirmative action in response to the digital campaign. a subset of contributing features that are indicative of a likelihood of the first user performing the affirmative action can be generated using a feature importance model for each digital campaign. for each digital campaign, a respective output indicating a likelihood that the first user will perform an affirmative action in response to the respective digital campaign can be obtained using a respective trained student-teacher neural network. these outputs can be compared to identify a particular digital campaign and one or more digital components associated with this campaign can be transmitted to the first user.
Inventor(s): Anand Pandey of Toronto CA for the toronto-dominion bank, Prerak Trivedi of Toronto CA for the toronto-dominion bank, Linda Ling Tao of Toronto CA for the toronto-dominion bank, John Jong-Suk Lee of Toronto CA for the toronto-dominion bank
IPC Code(s): G06N3/0475, G06N3/08
CPC Code(s): G06N3/0475
Abstract: an example operation may include one or more of receiving a conversation of a user, identifying a goal of the user from the conversation, identifying a different user that is associated with the identified goal of the conversation, generating a call script comprising a description of content therein to be discussed with a different user based on execution of a generative artificial intelligence (genai) model on the identified goal, and integrating the call script into a digital calendar of the different user.
Inventor(s): Shahriar Taheri of Newmarket CA for the toronto-dominion bank
IPC Code(s): G06N3/0475, G06N3/0895
CPC Code(s): G06N3/0475
Abstract: an example operation may include one or more of receiving an input from a user during a conversation that includes a plurality of prompts between the user and a chatbot within a chat window of a software application, converting text content within the received input into a vector, executing a large language model (llm) on the vector and a database of vectorized responses to identify a vectorized response to output from among the plurality of vectorized responses within the database, converting the vectorized response into a text response, and displaying the text response output by the chatbot within the chat window of the software application.
Inventor(s): Shahriar Taheri of Newmarket CA for the toronto-dominion bank
IPC Code(s): G06Q20/24, G06F40/20
CPC Code(s): G06Q20/24
Abstract: an example operation may include one or more of storing a data store of credit card documentation, conversing with a user via a chatbot within a chat window of a software application, wherein the conversing comprises receiving natural language inputs with requests for information about a payment card, identifying a benefit obtained by the user based on the conversation, executing a large language model (llm) on the identified benefit and the data store of the credit card documentation to generate a letter of confirmation, and generating an electronic message with the letter of confirmation attached, and transmitting the electronic message to a user device.
Inventor(s): Jeffrey Aaron Ecker of Toronto CA for the toronto-dominion bank, Dinshaw Bharucha of Toronto CA for the toronto-dominion bank, Igor Elkhinovich of Vaughan CA for the toronto-dominion bank
IPC Code(s): G06Q20/38, G06Q20/40, G06Q30/0226
CPC Code(s): G06Q20/3829
Abstract: an authorization network includes a payment terminal and a loyalty program server. the payment terminal receives a preliminary transaction value, receives an account number from an emv-compliant payment device, and determines an authorization value from a difference between the preliminary transaction value and a redemption value. the terminal initiates a funds transfer from a customer account associated with the account number in an amount equal to the authorization value by at least transmitting the account number and the authorization value to the payment device, receiving a cryptogram from the payment device, and confirming that the cryptogram was generated from the authorization value and from a cryptographic key uniquely associated with the payment device. the terminal initiates a funds transfer from a funding account to a merchant account by transmitting to the server a redemption request that includes the account number.
Inventor(s): Venkata Balasubramanyam MALISETTY of Welland CA for the toronto-dominion bank, Sajid PATHAN of Mississauga CA for the toronto-dominion bank
IPC Code(s): G06Q20/40, G06F9/54
CPC Code(s): G06Q20/4016
Abstract: a computer-implemented method is disclosed. the method includes: receiving, via a computing system, a message in connection with at least one transaction processed and flagged by the computing system as potentially being associated with a fraud status; creating a robotic process automation (rpa) software bot for collecting related data associated with the at least one flagged transaction; providing, by the rpa software bot using api calls, collected data to an application such that the data is actionable using the application; and updating a cloud-based database by creating a database record associated with the transaction responsive to determining that neither rpa nor manual tasks in connection with the transaction performed using the application raises a runtime exception.
20250117836. PROACTIVE BENEFIT SCAN_simplified_abstract_(the toronto-dominion bank)
Inventor(s): Shahriar Taheri of Newmarket CA for the toronto-dominion bank, Ashkan Alavi-Harati of Markham CA for the toronto-dominion bank
IPC Code(s): G06Q30/0601, G06F40/35, G06F40/40, G06Q20/22, G06Q30/0207
CPC Code(s): G06Q30/0613
Abstract: an example operation may include one or more of receiving an identifier of a product from a digital wallet on a user device, identifying one or more payment cards stored within the digital wallet on the user device, determining benefits that will be obtained by using each of the one or more payment cards to purchase the product via execution of an llm on the identifier of the product and a corpus of credit card documents, and displaying a chat message within a chat window on the user device with a description of the determined benefits that will be obtained.
Inventor(s): Anand Pandey of Toronto CA for the toronto-dominion bank, Prerak Trivedi of Toronto CA for the toronto-dominion bank, Linda Ling Tao of Toronto CA for the toronto-dominion bank, John Jong-Suk Lee of Toronto CA for the toronto-dominion bank
IPC Code(s): G06Q40/06, G06N3/0475
CPC Code(s): G06Q40/06
Abstract: an example operation may include one or more of storing a portfolio of assets of a user in memory, receiving contextual data of the user from a user device of the user, identifying an asset of interest that is not included in the portfolio of assets of the user based on execution of a generative artificial intelligence (genai) model on the portfolio of assets of the user and the received contextual data of the user, generating a different portfolio of assets based on the asset of interest that is not included in the portfolio of assets of the user, and displaying the different portfolio of assets via a user interface.
Inventor(s): Anand Pandey of Toronto CA for the toronto-dominion bank, Prerak Trivedi of Toronto CA for the toronto-dominion bank, Linda Ling Tao of Toronto CA for the toronto-dominion bank, John Jong-Suk Lee of Toronto CA for the toronto-dominion bank
IPC Code(s): G06Q40/06, G06N3/0455, G06N3/0475
CPC Code(s): G06Q40/06
Abstract: an example operation may include one or more of storing a portfolio of assets of a user in memory, receiving text from a conversation between the user on a first device and a second user on a second device, identifying an upcoming life event of the user based on execution of a generative artificial intelligence (genai) model on the received text from the conversation, determining a change to the portfolio of assets of the user based on the upcoming life event and existing assets within the portfolio of assets, and displaying the change to the portfolio of assets of the user via a user interface.
Inventor(s): Anand Pandey of Toronto CA for the toronto-dominion bank, Prerak Trivedi of Toronto CA for the toronto-dominion bank, Linda Ling Tao of Toronto CA for the toronto-dominion bank, John Jong-Suk Lee of Toronto CA for the toronto-dominion bank
IPC Code(s): G06Q40/06
CPC Code(s): G06Q40/06
Abstract: an example operation may include one or more of storing a current portfolio of a user in memory, receiving contextual data of the user from a user device of the user, identifying an asset of interest of the user based on execution of a generative artificial intelligence (genai) model based on the received contextual data of the user and the current portfolio of the user stored in memory, predicting a performance of the current portfolio with the identified asset of interest included therein at a future point in time, and displaying the predicted performance of the current portfolio with the identified asset of interest included therein on a user interface.
Inventor(s): Anand Pandey of Toronto CA for the toronto-dominion bank, Prerak Trivedi of Toronto CA for the toronto-dominion bank, Linda Ling Tao of Toronto CA for the toronto-dominion bank, John Jong-Suk Lee of Toronto CA for the toronto-dominion bank
IPC Code(s): G06Q40/06, G06F40/40
CPC Code(s): G06Q40/06
Abstract: an example operation may include one or more of receiving a current status of a portfolio of a user and previous actions taken on the portfolio of the user over a predetermined period of time, determining a goal for the user based on execution of a generative artificial intelligence (genai) model on the current status of the portfolio of the user and the previous actions taken, receiving a request for the portfolio of the user via a user device, and in response to the request, generating a text-based description of the goal and displaying the text-based description of the goal with portfolio content from the portfolio of the user on a user interface of the user device.
20250119396. CHARGE CARD KNOWLEDGE CHATBOT_simplified_abstract_(the toronto-dominion bank)
Inventor(s): Shahriar Taheri of Newmarket CA for the toronto-dominion bank
IPC Code(s): H04L51/02, G06F40/20
CPC Code(s): H04L51/02
Abstract: an example operation may include one or more of storing a database of payment card data, conversing with a user via a chatbot within a chat window of a software application, wherein the conversing comprises receiving a query from the user about a payment card during a chat session between the user and the chatbot, executing a large language model (llm) on the query about the payment card and the database of payment card data to generate a chatbot response, and displaying the generated chatbot response via the chatbot within the chat window of the software application during the chat session.
20250119479. DYNAMIC PUSH NOTIFICATIONS_simplified_abstract_(the toronto-dominion bank)
Inventor(s): Shahriar Taheri of Newmarket CA for the toronto-dominion bank, Ashkan Alavi-Harati of Markham CA for the toronto-dominion bank
IPC Code(s): H04L67/55, G06Q30/0601, H04L51/02, H04W4/029
CPC Code(s): H04L67/55
Abstract: an example operation may include one or more of storing a database of payment card data, receiving an identifier of a product from a digital wallet on a user device, identifying one or more payment cards stored within the digital wallet on the user device, determining the benefits that will be obtained by using each of the one or more payment cards to purchase the product via execution of an llm on the identifier of the product and the database of payment card data; and displaying a chat message within a chat window on the user device with a description of the determined benefits that will be obtained.
Inventor(s): Anand Pandey of Toronto CA for the toronto-dominion bank, Prerak Trivedi of Toronto CA for the toronto-dominion bank, Linda Ling Tao of Toronto CA for the toronto-dominion bank, John Jong-Suk Lee of Toronto CA for the toronto-dominion bank
IPC Code(s): H04M3/22, G10L15/08, G10L15/18, G10L15/26
CPC Code(s): H04M3/2218
Abstract: an example operation may include one or more of receiving content from a conversation between a user on a user device and a second user on a second user device that is connected to the user device via a network, identifying a topic of the conversation based on execution of a generative artificial intelligence (genai) model on the received content from the conversation, identifying a call list that is previously stored in memory that is associated with the topic of the conversation based on keywords included in the identified topic of the conversation, and adding an identifier of the user to the call list stored in memory.
Inventor(s): Anand Pandey of Toronto CA for the toronto-dominion bank, Prerak Trivedi of Toronto CA for the toronto-dominion bank, Linda Ling Tao of Toronto CA for the toronto-dominion bank, John Jong-Suk Lee of Toronto CA for the toronto-dominion bank
IPC Code(s): H04M3/42, G06N3/0475
CPC Code(s): H04M3/42221
Abstract: an example operation may include one or more of displaying a report on a user interface of a software application on a user device, listening to a call between a user on the user device and a different user on a second user device that is connected to the user device via a network, executing a generative artificial intelligence (genai) model based on content that is heard during the call and content within the report displayed on the user interface to identify content within the displayed report that is discussed during the call, and modifying the displayed report to emphasize the identified content within the displayed report on the user interface.
The Toronto-Dominion Bank patent applications on April 10th, 2025
- The Toronto-Dominion Bank
- G06F16/332
- H04L51/02
- H04L67/02
- H04L67/30
- CPC G06F16/3329
- The toronto-dominion bank
- G06F40/40
- G06F40/35
- CPC G06F40/40
- G06N3/091
- G06N3/045
- G06Q30/0204
- CPC G06N3/045
- G06N3/0475
- G06N3/08
- CPC G06N3/0475
- G06N3/0895
- G06Q20/24
- G06F40/20
- CPC G06Q20/24
- G06Q20/38
- G06Q20/40
- G06Q30/0226
- CPC G06Q20/3829
- G06F9/54
- CPC G06Q20/4016
- G06Q30/0601
- G06Q20/22
- G06Q30/0207
- CPC G06Q30/0613
- G06Q40/06
- CPC G06Q40/06
- G06N3/0455
- CPC H04L51/02
- H04L67/55
- H04W4/029
- CPC H04L67/55
- H04M3/22
- G10L15/08
- G10L15/18
- G10L15/26
- CPC H04M3/2218
- H04M3/42
- CPC H04M3/42221
