IP Library › Granted Patent US 11,182,860
Granted Patent B2
US 11,182,860 · App. 16/153,076 · Granted Nov 23, 2021

System and method for providing photo-based estimation

Inventors: Denny Devasia Kuruvilla (Toronto, CA); Esli Gjini (Etobicoke, CA); Sarah Reeve (Toronto, CA); Harjot Singh Panag (Brampton, CA); Justin Seto (Markham, CA); Naomi Sarah Feth (Toronto, CA); Anurag Thakur (Toronto, CA)
Assignee: THE TORONTO-DOMINION BANK
G06Q40/08G06Q30/016H04L51/02H04L51/046
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 11,182,860
App. No.
16/153,076
Filed
Oct 5, 2018
Granted
Nov 23, 2021
Kind
B2
Art Unit
3697
USPC
705/4
Abstract

Methods and systems for facilitating photo-based estimation are described. In an aspect, a server is configured to send via a communications module to a remote computing device a first signal comprising a chat interface. The server may receive, via the communications module and from the remote computing device, a second signal representing input received at the remote computing device through the chat interface. The server may identify an account associated with the remote computing device and retrieve policy data associated with the identified account from the data store. The server may automatically evaluate the input and policy data against predetermined criteria to determine whether a claim has a low risk level and, when the claim is determined to have a low risk level, engage a photo-based estimation module.

Claims (67)

1. A server comprising:

a communications module;

a data store;

a processor coupled to the communications module and the data store; and

a memory coupled to the processor, the memory storing processor-executable instructions which, when executed by the processor, configure the processor to:

send, via the communications module to a remote computing device, a first signal comprising a chat interface allowing a user of the remote computing device to send instant text messages to a chat-bot module during a chat session;

receive, via the communications module and from the remote computing device, a second signal representing one or more instant text messages sent through the chat interface;

identify an account associated with the remote computing device;

retrieve policy data associated with the identified account from the data store;

engage an artificial intelligence risk detection component to evaluate the one or more instant text messages and policy data to determine whether a claim has a risk level below a threshold risk level, the artificial intelligence risk detection component trained to detect indicators of risk using previous text messages received during previous chat sessions with other users and risk information associated with the previous chat sessions; and

responsive to determining that the claim has the risk level below the threshold risk level, engage a photo-based estimation module and enable image capture at the remote computing device within the chat interface, the photo-based estimation module configured to remotely receive a third signal representing image data of a damaged vehicle captured at the remote computing device, automatically analyze the image data to obtain an indicator quantifying an amount of damage to the vehicle and provide a real-time estimate within the chat interface based on the indicator.

2. The server of claim 1 , wherein the instructions further configure the processor to:

receive a location from the remote computing device, the location obtained at the remote computing device from a location subsystem; and

compare the received location to a location specified in the policy data.

3. The server of claim 2 , wherein the instructions further configure the processor to:

determine that the received location does not correspond to the location specified in the policy data; and

when it is determined that the received location does not correspond to the location specified in the policy data, determine that the claim does not have the risk level below the risk level threshold.

4. The server of claim 1 , wherein the instructions further configure the processor to:

determine that a vehicle is expensive to repair by comparing a make or model specified in the policy data to a predefined set of makes or models in the data store; and

when it is determined that the vehicle is expensive to repair, determine that the claim does not have the risk level below the risk level threshold.

5. The server of claim 1 , wherein the indicators of risk include determining that an airbag has been deployed and the artificial intelligence risk detection component determines that the claim does not have the risk level below the risk threshold when the one or more instant text messages indicate that the airbag has been deployed.

6. The server of claim 1 , wherein the indicators of risk include determining that a vehicle is not drivable and the artificial intelligence risk detection component determines that the claim does not have the risk level below the risk threshold when the one or more instant text messages indicate that the vehicle is not drivable.

7. The server of claim 1 , wherein engaging a photo-based estimation module comprises:

sending, to the remote computing device via the communications module, a user interface having a selectable option to send image data to the server.

8. The server of claim 1 , wherein automatically analyzing the image data to obtain the indicator comprises:

identifying a damaged component on the vehicle; and

performing a lookup of the indicator in the data store based on the identified damaged component.

9. The server of claim 1 , wherein engaging the photo-based estimation module further comprises:

receiving, from the remote computing device, a fourth signal representing further image data;

automatically analyzing the further image data to update the indicator; and

provide an updated real-time estimate within the chat interface based on the updated indicator.

10. The server of claim 1 , wherein the instructions further configure the processor to:

responsive to determining that the claim does not have the risk level below the threshold risk level, engage a manual estimation module by handing off the chat session between the user and the chat-bot to a chat session between the user and an operator device.

11. A method comprising:

sending, via a communications module to a remote computing device, a first signal comprising a chat interface allowing a user of the remote computing device to send instant text messages to a chat-bot module during a chat session;

receiving, via the communications module and from the remote computing device, a second signal representing one or more instant text messages sent through the chat interface;

identifying an account associated with the remote computing device;

retrieving policy data associated with the identified account from a data store;

engaging an artificial intelligence risk detection component to evaluate the one or more instant text messages and policy data to determine whether a claim has a risk level below a threshold risk level, the artificial intelligence risk detection component trained to detect indicators of risk using previous text messages received during previous chat sessions with other users and risk information associated with the previous chat sessions; and

responsive to determining that the claim has the risk level below the threshold risk level, engaging a photo-based estimation module within the chat interface and enabling image capture at the remote computing device, the photo-based estimation module configured to remotely receive a third signal representing image data of a damaged vehicle captured at the remote computing device, automatically analyzing the image data to obtain an indicator quantifying an amount of damage to the vehicle and provide a real-time estimate within the chat interface based on the indicator.

12. The method of claim 11 , further comprising:

receiving a location from the remote computing device, the location obtained at the remote computing device from a location subsystem; and

comparing the received location to a location specified in the policy data.

13. The method of claim 12 , further comprising:

determining that the received location does not correspond to the location specified in the policy data; and

when it is determined that the received location does not correspond to the location specified in the policy data, determining that the claim does not have the risk level below the risk level threshold.

14. The method of claim 11 , further comprising:

determining that a vehicle is expensive to repair by comparing a make or model specified in the policy data to a predefined set of makes or models in the data store; and

when it is determined that the vehicle is expensive to repair, determining that the claim does not have the risk level below the risk threshold.

15. The method of claim 11 , wherein the indicators of risk include determining that an airbag has been deployed and the artificial intelligence risk detection component determines that the claim does not have the risk level below the risk threshold when the one or more instant text messages indicate that the airbag has been deployed.

16. The method of claim 11 wherein the indicators of risk include determining that a vehicle is not drivable and the artificial intelligence risk detection component determines that the claim does not have the risk level below the risk threshold when the one or more instant text messages indicate that the vehicle is not drivable.

17. The method of claim 11 , wherein engaging the photo-based estimation module comprises:

sending, to the remote computing device via the communications module, a third signal including a user interface having a selectable option to send image data to a server.

18. The method of claim 11 , wherein automatically analyzing the image data to obtain the indicator comprises:

identifying a damaged component on the vehicle; and

performing a lookup of the indicator in the data store based on the identified damaged component.

19. The method of claim 11 , wherein engaging the photo-based estimation module further comprises:

receiving, from the remote computing device, a fourth signal representing further image data;

automatically analyzing the further image data to update the indicator; and

provide an updated real-time estimate within the chat interface based on the updated indicator.

20. A non-transitory computer readable storage medium comprising computer-executable instructions which, when executed, configure a computing device to:

send, via the communications module to a remote computing device, a first signal comprising a chat interface allowing a user of the remote computing device to send instant text messages to a chat-bot module during a chat session;

receive, via the communications module and from the remote computing device, a second signal representing one or more instant text messages sent through the chat interface;

identify an account associated with the remote computing device;

retrieve policy data associated with the identified account from a data store;

engage an artificial intelligence risk detection component to evaluate the one or more instant text messages and policy data to determine whether a claim has a risk level below a threshold risk level, the artificial intelligence risk detection component trained to detect indicators of risk using previous text messages received during previous chat sessions with other users and risk information associated with the previous chat sessions; and

responsive to determining that the claim has the risk level below the threshold risk level, engage a photo-based estimation module and enable image capture at the remote computing device within the chat interface, the photo-based estimation module configured to remotely receive a third signal representing image data of a damaged vehicle captured at the remote computing device, automatically analyze the image data to obtain an indicator quantifying an amount of damage to the vehicle and provide a real-time estimate within the chat interface based on the indicator.

Assignments (7)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 14, 2019
From: KURUVILLA, DENNY DEVASIA
To: THE TORONTO-DOMINION BANK
Reel/Frame 049172/0950 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 14, 2019
From: GJINI, ESLI
To: THE TORONTO-DOMINION BANK
Reel/Frame 049173/0044 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 14, 2019
From: REEVE, SARAH
To: THE TORONTO-DOMINION BANK
Reel/Frame 049173/0111 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 14, 2019
From: PANAG, HARJOT SINGH
To: THE TORONTO-DOMINION BANK
Reel/Frame 049173/0158 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 14, 2019
From: SETO, JUSTIN
To: THE TORONTO-DOMINION BANK
Reel/Frame 049173/0212 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 14, 2019
From: FETH, NAOMI SARAH
To: THE TORONTO-DOMINION BANK
Reel/Frame 049173/0347 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 14, 2019
From: THAKUR, ANURAG
To: THE TORONTO-DOMINION BANK
Reel/Frame 049173/0468 →
Continuity (1)
Related Publication 20200111167A1 · Apr 9, 2020
Cited By (28)
US 12,316,715 US 12,399,687 US 12,417,086 US 12,499,241 US 12,517,812 US 12,536,264 US 12,541,544 US 12,541,894 US 12,566,541 US 12,585,435 US 12,591,559 US 12,592,301 US 12,625,680 US 12,641,178 US 12,645,429 US 12,645,689 US 12,645,838 US 12,646,051 US 12,650,836 US 12,657,566 US 12,670,334 US 12,670,640 US 12,688,620 US 12,693,842 US 12,699,556 US 12,705,398 US 12,711,683 US 12,725,152