公开(公告)号：US12298949B2

公开(公告)日：2025-05-13

申请号：US18464814

申请日：2023-09-11

Applicant: The Toronto-Dominion Bank

Inventor： Vidhi Arora ,  Jennifer Bouchard ,  Jorge Alberto Caicedo ,  Yu Gu ,  Hoi Sing Mak ,  Jennifer Dawn Miguez ,  Kevin Shao ,  Andriy Shcherbatyuk ,  Tan Vu Vuong

IPC: G06F16/215 ,  G06F16/23

Abstract: False data entities attempt to evade getting caught by changing their information repeatedly over time. Systems and methods are provided to detect false data entities. A computing system ingests a plurality of data files respectively from a plurality of external data sources using the network interface within a current specified time period. It consolidates a plurality of data entries of false data entities from the plurality of data files into a consolidated list for the current specified time period. It compares the consolidated list for the current specified time period with a previous consolidated list corresponding to a previous specified time period to identify one or more differences. It then updates a database, which comprises a current list of false data entities, with the one or more differences.

公开(公告)号：US12223549B2

公开(公告)日：2025-02-11

申请号：US17747819

申请日：2022-05-18

Applicant: THE TORONTO-DOMINION BANK

Inventor： Jean-Christophe Bouëtté ,  Jimmy Lévesque ,  Marc Poulin ,  Satya Krishna Gorti ,  Keyu Long ,  Nicolas Gervais ,  Jennifer Bouchard

IPC: G06Q40/08 ,  G06V10/26 ,  G06V10/80 ,  G06V10/82 ,  G06V20/64

Abstract: A data processing system comprising: inputting a tiled image of a vehicle including four different angle views of the vehicle combined into a single image to a first machine learning model (e.g. CNN), the model trained based on historical image data to predict a first likelihood of total loss vehicle; inputting a multi-fusion of images each into a second set of machine learning models; the multi-fusion of images including a set of separate and distinct images for each of the views input separately into the second set of machine learning models, and extracting features to predict a second likelihood of total loss vehicle; inputting tabular data relating to the vehicle into a third machine learning model to predict a third likelihood of total loss vehicle for the vehicle; and aggregating the first, second and third likelihood of total loss vehicle to determine the overall likelihood of total loss.

公开(公告)号：US20250086151A1

公开(公告)日：2025-03-13

申请号：US18464814

申请日：2023-09-11

Applicant: The Toronto-Dominion Bank

Inventor： Vidhi Arora ,  Jennifer Bouchard ,  Jorge Alberto Caicedo ,  Yu Gu ,  Hoi Sing Mak ,  Jennifer Dawn Miguez ,  Kevin Shao ,  Andriy Shcherbatyuk ,  Tan Vu Vuong

IPC: G06F16/215 ,  G06F16/23

Abstract: False data entities attempt to evade getting caught by changing their information repeatedly over time. Systems and methods are provided to detect false data entities. A computing system ingests a plurality of data files respectively from a plurality of external data sources using the network interface within a current specified time period. It consolidates a plurality of data entries of false data entities from the plurality of data files into a consolidated list for the current specified time period. It compares the consolidated list for the current specified time period with a previous consolidated list corresponding to a previous specified time period to identify one or more differences. It then updates a database, which comprises a current list of false data entities, with the one or more differences.