Granted Patent B2

US 12,602,637 · App. 17/716,791 · Granted Apr 14, 2026

Inventors: Ahmed Farouk Shaaban (South Barrington, IL); Venkat Thandra (South Barrington, IL); Dino Eliopulos (South Barrington, IL); Andrew Kenneth Blazaitis (Rochester, MN); Kennedy Muthukrishnan (South Barrington, IL)

Assignee: ACI Holdings Ltd.

G06Q10/0635G06F16/282G06F16/9035G06Q50/18

Abstract

Claims (47)

1 . A method for client intake and management by a first party, the method comprising:

presenting, on a user terminal, a user interface enabling a user to enter a name of a second party that is a potential client;

receiving, via the user interface, user input of initial client data including the name of the second party;

transmitting the initial client data from the user terminal to a central server including a memory storing an extraction algorithm including a neural network and a matter database;

searching the name of the second party in the matter database using a hierarchal searching system to calculate a risk assessment for the second party based at least partially on past hierarchal searching results;

determining a conflict rating code based on subsequent search results from the searching the name of the second party and the past hierarchal searching results;

determining a litigiousness factor weighted as part of the risk assessment for the second party by matching the user input of initial client data against the matter database on the central server;

in response to not finding the name of the second party in the matter database, retrieving a document or website including additional client data regarding the second party from an existing second party database or a third party data source;

based on classification of the document or website, using the extraction algorithm including the neural network to extract target data from the additional client data based on x and y coordinates defining a location on the document or website;

receiving input regarding whether the target data at the x and y coordinates is accurate;

when the input indicates that the extracted target data is accurate, using the extracted target data to further train the extraction algorithm including the neural network as a positive example of a location of x and y coordinates where target information is found on the classified document or website;

when the input indicates that the extracted target data is not accurate, using the extracted target data to further train the extraction algorithm including the neural network as a negative example of the location of x and y coordinates where target information is found on the classified document or website;

generating at least one risk parameter based on the target data;

determining a risk associated with the second party based on the at least one risk parameter;

updating the conflict rating code; and

presenting the risk to the user using the user interface of the user terminal.

2 . The method of claim 1 , wherein

retrieving additional client data includes retrieving additional client data from the existing second party database.

3 . The method of claim 1 , wherein

retrieving additional client data includes retrieving additional client data from the third party data source.

4 . The method of claim 1 , comprising

generating the at least one risk parameter includes using at least one reliability weight.

5 . The method of claim 4 , comprising

adjusting the at least one reliability weight based on cross-referencing the additional client data and the initial client data.

6 . The method of claim 1 , wherein

generating the at least one risk parameter includes using at least one category weight.

7 . The method of claim 1 , wherein

the at least one risk parameter includes a numerical value.

8 . The method of claim 1 , wherein

approving or rejecting the second party as a client based on the at least one risk parameter.

9 . A system for client intake and management by a first party, the system comprising:

at least one user terminal including a user input device configured to receive initial client data regarding a second party, the at least one user terminal configured to present a user interface enabling a user to enter a name of a second party that is a potential client; and

a central server including a processor and a memory, the memory storing an extraction algorithm including a neural network and a matter database, the processor programmed to execute instructions stored on the memory to cause the central server to: (i) receive the initial client data including the name of the second party from the at least one user terminal; (ii) searching the name of the second party in the matter database using a hierarchal searching system of conflict rating codes to calculate a risk assessment for the second party based at least partially on past hierarchal searching results; (iii) in response to not finding the name of the second party in the matter database, retrieve a document or website including additional client data regarding the second party from an existing second party database or a third party data source; (iv) based on classification of the document or website, using the extraction algorithm including the neural network to extract target data from the additional client data based on x and y coordinates defining a location on the document or website; (v) receive input regarding whether the target data at the x and y coordinates is accurate; (vi) when the input indicates that the extracted target data is accurate, use the extracted target data to further train the extraction algorithm including the neural network as a positive example of a location of x and y coordinates where target information is found on the classified document or website; (vii) when the input indicates that the extracted target data is not accurate, using the extracted target data to further train the extraction algorithm including the neural network as a negative example of the location of x and y coordinates where target information is found on the classified document or website; (viii) generate at least one risk parameter based on the target data; (ix) determine a risk associated with the second party based on the at least one risk parameter; (x) update a conflict rating code; and (xi) cause the risk to be presented to the user using the user interface of the at least one user terminal.

10 . The system of claim 9 , wherein

the processor is programmed to retrieve the additional client data from the existing second party database.

11 . The system of claim 9 , wherein

the processor is programmed to retrieve the additional client data from the third party data source.

12 . The system of claim 9 , wherein

the processor is programmed to generate the at least one risk parameter using at least one reliability weight.

13 . The system of claim 12 , wherein

the processor is programmed to adjust the at least one reliability weight based on cross-referencing the additional client data and the initial client data.

14 . The system of claim 9 , wherein

the processor is programmed to generate the at least one risk parameter using at least one category weight.

15 . The system of claim 9 , wherein

the at least one risk parameter includes a numerical value.

16 . The system of claim 9 , wherein

the processor is programmed to approve or reject the second party as a client based on the risk parameter.

Assignments (1)

Continuity (2)

References Cited (56)